Let’s get into it.

First, something free 👇

The founders winning in 2026 are everywhere: LinkedIn, newsletters, podcasts, investor DMs. They run on a system that publishes for them, rather than carving out time they rarely have.

We built that system into a free AI Creator Kit: one Notion workspace with AI agents, templates, a creator CRM, and partner credits worth thousands.

Grab it here, no paywall:

Free AI Creator Kit

In-Depth Insights 🔍

• Top 20 VC Matches in 30 Seconds 🎯
  A free tool screens 293 active VCs, angels, and family offices by stage, sector, geography, check size, and thesis to surface relevant investors fast. Founders pitching at VC Pitch Conf on September 17 also get 20 guaranteed seven-minute meetings matched from the same investor pool.

  

• Delay Your First Engineering Hire 🧑‍💻
  AI-assisted development is pushing the point where startups need their next engineer, with some teams reaching $1M ARR using only one or two technical hires. The better hiring playbook starts with trusted networks and evaluates candidates on ownership and AI-assisted reasoning instead of traditional whiteboard performance.

  

• A Nine-Prompt Stack for Closing Funding Rounds 🤝
  The system covers investor research, objection handling, data-room analysis, and term-sheet review, beginning with context that frames Claude as a skeptical senior partner. The prompts are designed to pressure-test fundraising decisions, though the full stack and supporting libraries sit behind a paid subscription.

  

• Build AI Systems That Improve Themselves 🔄
  A nine-part framework combines goals, evaluations, memory, guardrails, escalation, and stopping conditions to turn isolated prompts into repeatable feedback loops. The Self-Improving Champion Loop tests changes against holdout data before deployment, alongside three other patterns, five failure modes, and a practical build specification.

  

• The NRR-GRR Gap Reveals Hidden Churn 📊
  NRR includes expansion while GRR excludes it, making the difference a useful signal for whether growth reflects broad customer retention or a handful of expanding accounts masking churn. The framework breaks SaaS businesses into four segments and highlights dunning improvements that can recover 70% to 80% of failed-payment churn. []

  

• Investors Are Losing Faith in Startup Metrics 🤔
  Fifteen VCs flagged ARR as especially unreliable because companies increasingly use it for run-rate, GMV, and consumption revenue without consistent definitions. CARR, gross margin, POC-driven NRR, and physical AI autonomy rates also drew scrutiny when underlying costs or ideal testing conditions are excluded. []

  

• From $8M ARR to Rebuilding From Scratch 🛍️
  Ruslan Leteyski built Checkout X to $8M ARR before a Shopify platform change eliminated the product overnight, forcing a complete reset. His new company Zipchat sells AI-powered sales agents to e-commerce stores through usage-based pricing, now processing 700K conversations monthly while growing 10% week over week. [Indie Hackers]

Social Media Gems 💎

• Thrive Capital’s Fund Returns Show the Exit Gap 📊
  Net IRRs range from 12% to 17.5%, while DPI stays below 0.3x for every fund younger than 10 years. The portfolio spans Instagram, Stripe, OpenAI, SpaceX and Anduril, giving each vintage a different path to realized returns. [Restructuring]

  

• Worst Value Cities: London, New York, LA and San Francisco 🌆
  A 100-city comparison finds these markets combine high living and housing costs with weaker quality-of-life value. Porto, Valencia and Prague have led the value rankings for seven years, while costs are rising fastest in several migration-heavy cities.

  

• FatFIRE’s Case for Buying Back Your Time 💰
  The argument is that once housing and core expenses are covered, additional wealth delivers smaller gains in day-to-day quality of life. Financial independence matters most when it creates room for health, family, good food and the freedom to spend time outside the balance sheet.

  

• The 2013 Excel File Still Has a Job 📊
  A meme captures a familiar enterprise reality: AI can replace workflows faster than companies can replace the spreadsheets built around them.

  

Trending News ⚡

• Stripe to Acquire OpenRouter for $7B+ 💳
  Stripe is set to acquire AI gateway OpenRouter for more than $7 billion, giving it infrastructure that routes workloads across 400+ models based on cost and performance. OpenRouter had 8 million users and raised $113 million at a $1.3 billion valuation just months ago, making the deal a major repricing of model-routing infrastructure. [TechCrunch]
  

• Amodei Says AI Backlash Is Really a Trust Problem ⚠️
  Anthropic CEO Dario Amodei pushed back on claims that AI leaders created today’s backlash, arguing that his warnings have consistently covered both risks and benefits. He sees the deeper issue as decades of declining trust in companies, governments, and technology, with AI now becoming the latest target of that broader distrust. [TechCrunch]

  

• Brockman Warns Companies to Move Fast on AI Security 🛡️
  OpenAI president Greg Brockman says the latest AI-driven security incidents show attackers will soon use agents to discover vulnerabilities at machine speed. His playbook calls for immediate assessments, AI-equipped security teams, faster forensics, and executive buy-in before the advantage shifts further toward attackers. [Business Insider]

  

• a16z Could Make Nearly $1.5B From OpenRouter Exit 🤝
  Andreessen Horowitz could turn roughly $20 million invested in OpenRouter into nearly $1.5 billion if Stripe closes its reported acquisition above $8 billion. Menlo Ventures could also clear more than $500 million, showing how quickly early-stage ownership can compound when infrastructure companies become strategic assets. [Business Insider]

• Cursor Launches Origin as GitHub Faces Outages 🖥️
  Cursor launched Origin as a collaborative code-hosting platform that syncs with GitHub, giving developers another layer for repositories, pull requests, and team workflows. The timing is notable: GitHub suffered a major outage the same day, highlighting the opportunity for developer platforms to reduce dependence on a single infrastructure provider. [TechCrunch]

• Sebastian Thrun Launches Robotics Startup Dulo 🤖
  Waymo pioneer Sebastian Thrun has unveiled Dulo, a stealth startup building foundation models for hardware design with talent from Waymo, Google Brain, and Stanford. The bet arrives as physical AI funding accelerates, with robotics startups raising $16.3 billion across 492 deals in Q1 2026 alone. [Business Insider]

• Flock Says Drones Are Its Fastest-Growing Business 🚁
  Flock Safety says drone response now accounts for nearly half of its forward-looking revenue, with more than 200 customers using drones as first responders to 911 calls. The growth is shifting the company’s center of gravity beyond license-plate readers, even as that core business faces scrutiny over accuracy, retention, and law-enforcement use. [Business Insider]

• Uber COO Predicts a Leaner Workforce From AI 🚗
  Uber COO Andrew Macdonald said the company could potentially operate its current business with fewer employees within five years as AI takes over more support, sales, content, and analytics work. The harder variable is new demand: AI may reduce headcount in existing functions while simultaneously making it economical for Uber to pursue work that previously required more people. [Business Insider]

• Anthropic’s IPO Is Being Priced on 2028 💰
  Anthropic is asking investors to underwrite roughly $190 billion to $200 billion in 2028 revenue, far beyond its $47 billion run rate disclosed in May. The valuation math is shifting from current earnings to future scale, with investors benchmarking the company against high-multiple names like Palantir, SpaceX, and Cloudflare. [Reuters]

New Funds 💰

• Reach Capital closed its fifth venture fund at $265M to back early-stage companies applying technology and AI across learning, health, and work.

• GD1 held a NZ$56.7M first close of its second venture fund to invest in Pre-Seed through Series B companies across deep tech, connected hardware, health tech, SaaS, and marketplaces.

• Third Mind is raising a $25M first venture capital fund to invest in early-stage technology companies.

• BlueHill Capital closed its inaugural venture fund at $41.8M to back Seed and Series A companies across energy, semiconductors, defence, space, robotics, and advanced materials.

• Odyssey Ventures secured a £10M commitment toward its $50M Discovery I venture fund, targeting seed and pre-seed AI and DeepTech companies.

That’s a wrap for this week.

If you want to stay ahead of the curve, make sure you're subscribed. No fluff, just real startup insights delivered straight to your inbox.

See you next time 🚀

This series is a preview of a new book I’ve written with my partners Richard Blundell and Paul Watson — The Selling Software Algorithm: The Go-to-Market Navigation System for B2B Software Leaders.

It isn’t a strategy deck dressed up as a book. Between the three of us we’ve spent close to seven decades inside B2B software as founders, operators, investors and coaches — building companies, exiting some, and quietly breaking a few along the way, which is where most of the real learning lives. Through our work at Vencha we’ve now supported hundreds of founders trying to do the single hardest thing in software: turn a clever product into predictable commercial traction in a market that’s noisy, cautious, and more crowded than it has ever been.

One pattern shows up again and again. Companies rarely struggle because the product is bad. They struggle because they have no navigation system for going to market. This book is that system.

Get my Copy

Most founders know their product is different. The problem is that their homepage often doesn’t make that difference obvious.

That matters more than it used to. Buyers are moving quickly, they have seen hundreds of versions of the same claims, and they are not going to spend five minutes working out what makes you different.

There is a very simple way to find out whether your message is doing its job. Take the hero message off your homepage and put it on your closest competitor’s. Then ask yourself a slightly uncomfortable question: would anyone notice?

That is where we’ll start.

Table of Contents

• A Simple Test: Swap Your Homepage With a Competitor’s

• Seven Seconds, and Not a Second More

• Why “Why” Beats “What” and “How”

• One Armour-Piercing Message, Not Five Soft Ones

• Strip Away the Algorithms and the Platforms

• The Modern Messaging Stack

• Matching Your Message to the Curve You Just Mapped

A Simple Test: Swap Your Homepage With a Competitor’s

Take the hero message off your website. Paste it onto your closest competitor’s homepage. Now ask your team whether anyone would notice.

If nobody would, the message isn’t yours. It’s category wallpaper, and it’s costing you every visitor who arrives without already knowing who you are.

The test works because it strips out everything you know about your own product and leaves only what the buyer can see. You know your architecture is different. They don’t, and they aren’t going to burn the mental calories finding out.

Seven Seconds, and Not a Second More

Buyers scroll the way everyone now scrolls. You have roughly seven seconds, often less, to produce the small internal jolt of recognition that says “that’s me.”

They don’t owe you patience. They don’t owe you curiosity. They certainly don’t owe you a meeting. Your messaging has to earn its place before it earns their attention, and most of it never does, because it was written to satisfy the founder’s pride rather than the buyer’s need.

There’s a deeper version of this too. Most software companies write messaging about operational pain: time saved, cost reduced, workflow streamlined. All true, all useful later as a convincer. But the great ones go one layer down, to the reputational risk, the internal politics, the recurring problem that keeps surfacing in leadership conversations. You’re not only selling operational improvement. You’re selling relief, credibility, and a better leadership story.

Why “Why” Beats “What” and “How”

“We are an AI-powered platform that uses machine learning to optimise X” isn’t a message. It’s a product description, and it forces the buyer to do the interpretation. Buyers no longer interpret. They discard.

Lead with “how” and you’ll lose even faster. “We unify data across systems using our proprietary engine” may be entirely true, and it’s still not the reason anyone will care.

Lead with why it matters, which usually means pain, consequence and outcome, in plain English, in the Economic Buyer’s own voice. If a twelve-year-old can’t read your homepage and explain what you do, the language is too complicated. Complexity isn’t sophistication. It’s usually fear, because vague language lets you hide and clear language forces you to commit.

From the book: what great hero messages sound like

One Armour-Piercing Message, Not Five Soft Ones

The most common failure here is the multi-message compromise. A company tries to speak to everyone, writes five value statements, dilutes each one slightly, and hopes the buyer will pick the one that fits.

Buyers don’t do that. They glance, they judge, and they leave.

You need one armour-piercing message, anchored in your number one pain. The second and third pains can sit underneath it, but the hero line leads with the sharpest blade you have: the knife in your product, the thing that changes their world most urgently.

If you’re unsure what that knife is, go back to your pain wheel rankings and ask a brutally simple question. Which pain, if removed, would make the Economic Buyer feel the greatest relief? That’s usually the knife.

Strip Away the Algorithms and the Platforms

There is a time to explain how you do it. It isn’t in the first seven seconds of someone reading your website.

Words like “platform”, “algorithm”, “proprietary engine”, “next generation” and “AI-powered” are, in early messaging, a form of hiding. They signal sophistication without stating meaning. Economic Buyers don’t buy sophistication. They buy business outcomes they can defend in a room full of people who weren’t on your demo.

Removing that decorative language isn’t dumbing down. It’s respecting their time.

The Modern Messaging Stack

Once your algorithm is clear, the structure that follows is straightforward, and it forces your language to stay buyer-first.

The hero message carries the top pain and the outcome. One line names who it’s for, narrow and specific, ideally naming the Economic Buyer outright. Three supporting proofs follow: a metric, a case study outcome, a time-to-value claim. Then a calm call to action, not “book a demo” but something that feels like the next logical step, such as “see how it works in your world”.

That sequence mirrors how buyers actually process information. Fast emotional recognition first, then credibility, then action.

From the book: the Modern Messaging Stack

Matching Your Message to the Curve You Just Mapped

Last time we mapped readiness, and the same discipline applies here. Not everyone inside your perfect customer profile is ready to hear the same thing.

Late adopters, particularly around AI, arrive nervous and unsure what to ask. They fear hallucinations, compliance exposure and reputational fallout, and they want proof, references and reassurance. Innovators and early adopters respond to clarity, urgency and an ambitious outcome, but they respond to honesty just as strongly. They want to know what’s possible, what’s proven, and what’s safe.

Your messaging should be built for the part of the curve you’re targeting first, which early on should almost always be that front section of your perfect customer profile.

This is exactly what Builder Step 5 exists to check: whether your hero message, your named buyer and your three proofs actually hold together, or whether you’ve written five soft messages and hoped one of them lands.

Selling Software Algorithm Builder, Step 5: Messaging (recreated illustrative mockup based on the tool’s documented output; a fictional example company is shown)

Next in the series, we look at what happens when the algorithm stops being a document and becomes behaviour, and why this is the one piece of work a founder cannot delegate.

-Chris Tottman

Most hero messages could sit on a competitor’s website without anyone noticing, because they were written to describe the product rather than change the buyer’s world.

The Selling Software Algorithm Builder Step 5 tests your messaging against your Economic Buyer and your three pains, and shows you exactly where it goes soft.

Start your 7-day free trial → Cancel anytime.

Test Your Messaging

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Two founders walk into two different partner meetings this month. Both put up the exact same slide: 112% Net Revenue Retention. Same font, same green arrow, same confident pause after the number lands.

One of them keeps 94% of existing revenue and grows the rest through expansion. The other keeps 78% and covers the hole with aggressive upsell on two or three big accounts.

Same headline. One is a compounding business. The other is a leaky bucket that hasn’t sprung its last leak yet.

The partner in the room knows which is which within about ninety seconds, because they were never looking at the number on the slide. They were calculating the one you didn’t show them.

The gap between the two numbers is the signal. The number on the slide never was.

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The number hiding behind your number

The slide number is NRR, Net Revenue Retention: what you keep from existing customers, plus everything they grew into. Upgrades, seats, usage. Because expansion gets added back in, NRR is uncapped. You can print 130% with zero new logos.

The number the partner is calculating in their head is GRR, Gross Revenue Retention: the same base with expansion stripped back out. Churn and downgrades only. It can never go above 100%, which is exactly what makes it honest. It’s the floor of what you keep before anyone upsells anything.

Put both founders through the math:

▫️ Founder one: $4M ARR, loses $240K to churn, adds $720K in expansion. GRR 94%, NRR 112%. Gap: 18 points.

▫️ Founder two: $4M ARR, loses $880K to churn, adds $1.36M in expansion. GRR 78%, NRR 112%. Gap: 34 points.

A healthy gap sits between 15 and 25 points. Under 15 and you’re durable but leaving money on the table, which is a pricing problem, not a churn problem. Over 25 and you’re masking a leak with a handful of accounts that could all walk in the same quarter.

Most founders have never calculated GRR separately. They’ve only ever seen the blended number, and that’s rarely an accident. NRR is the number that goes up when you sell harder to the customers you already have, so it’s the one every dashboard defaults to and every board deck leads with. GRR just sits quietly underneath, refusing to be flattered.

What “good” looks like in 2026

Retention benchmarks are close to useless blended, because they move hard by segment. A 97% NRR is a red flag for an enterprise vendor and roughly average for an SMB one.

▫️ Enterprise (ACV $100K+): median NRR ~118%

▫️ Mid-market ($25K–$100K ACV): median NRR ~108%

▫️ SMB (under $25K ACV): median NRR ~97%

▫️ B2B blended: median NRR ~108%, GRR ~88%

▫️ Bootstrapped, $3M–$20M ARR: median NRR ~103%, GRR ~91%

▫️ Top quartile, any segment: NRR 125%+, GRR 94%+

This isn’t a vanity metric. Public SaaS companies above 120% NRR have traded at roughly 9.3x median EV/revenue, against 3.1x for those below 100%, according to Software Equity Group. Retention isn’t a line on your deck. It’s a multiplier on the entire company.

And it’s usually the first thing a partner sanity-checks against your growth story. A founder who shows up with 40% year-over-year growth and a soft GRR underneath it is telling the room, without meaning to, that the growth is bought rather than earned. The multiple follows the retention, not the other way around.

Your GRR is a fundraising number before it’s ever a retention number

A partner doesn’t ask about churn out of curiosity. It’s one input into a bigger judgment about whether you’re ready to raise at all, and it rarely travels alone. If retention is on your mind right now, these are worth reading next:

▫️ The Number That Kills More Fundraises Than Any Bad Idea: one slide, one metric, quietly killing raises without founders ever knowing it.

▫️ The Way VCs Actually Calculate Your Valuation: they already have a number in their head before you walk in. What is it, and how do you hit it?

▫️ How Investors Decide If You’re Ready to Raise: it’s not timing, it’s not luck. The exact criteria investors use.

▫️ The Quiet Filter That Decides Your Entire Fundraise: every investor runs this before you open your mouth.

Which of the four quadrants are you in

Plot yourself. GRR on one axis, the gap on the other. There are only four places to land, and each one gets a different verdict in a partner meeting.

▫️ GRR 90%+, gap under 15 points, durable and under-monetised. People stay, you’re just not capturing the value yet. Fastest fix here: move to usage- or seat-based pricing so revenue climbs alongside the customer’s own success.

▫️ GRR 90%+, gap 15 to 25 points, the compounding machine. Broad retention, broad expansion. This is the profile that earns the premium multiple, and the only quadrant where churn genuinely stops being a worry.

▫️ GRR under 85%, gap 25+ points, the masked leak. The headline looks fine. The base is bleeding and a handful of accounts are carrying the whole story. Partners are trained to find this quadrant, and them finding it is far worse for you than you disclosing it first.

▫️ GRR under 85%, gap under 15 points, honest and broken. No expansion mechanic, real churn. Painful, but the cleanest diagnosis on the board: you know exactly what to fix, and nobody can accuse you of hiding it.

Most founders assume they’re in quadrant two and have simply never run the GRR math to check.

The fix you can start this week, before touching the product

Here’s the part almost nobody acts on, because it doesn’t feel like a growth initiative.

Across analyses from ProfitWell, Recurly and Paddle, failed payments account for 20 to 40% of all SaaS churn. Expired cards. Bank declines. Customers who never chose to leave and, in a lot of cases, never even noticed they’d gone. A proper dunning setup recovers 70 to 80% of them, per Chargebee’s research on the subject.

This is the highest-leverage fix on the list, because it’s a technical problem with nobody’s opinion attached. You’re not persuading anyone to stay. You’re just catching the ones who wanted to.

▫️ Retry on a schedule, not once. Days 1, 3, 5 and 10 beats a single attempt at the moment of failure, since most declines are timing issues that clear within a week.

▫️ Email before the card expires, not after. Pre-dunning recovers far more cheaply than chasing a failure after the fact.

▫️ Turn on the account updater. Stripe and Adyen will refresh reissued card details automatically. Most teams have simply never flipped the switch.

▫️ Put it in the app, not just the inbox. Billing emails land in a finance address nobody checks. The person who can fix it is the one logged in.

▫️ Split the number in your own reporting. Report voluntary and involuntary churn separately from here on. If you can’t split them yet, that’s the tell you don’t know which problem you actually have.

▫️ Report GRR trailing twelve months, not last month. A single bad month reads as a crisis. Twelve months reads as a trend, which is the only version a partner actually trusts.

One to two weeks of engineering. Zero new customers acquired. Several points back on the number that was carrying the real signal the whole time.

🔒 This is exactly the kind of asset we built Premium for

You now have the diagnostic and the fastest fix. What you don’t have yet is the other side of the table, and that’s the part that actually decides your round.

Behind the paywall is The Retention Diligence Pack. The nine questions a partner asks about your retention, in the exact order they ask them, with the answer that lands and the answer that quietly ends the process, including the one about your largest customer that catches out almost every founder who hasn’t rehearsed it. The cohort table format built for a data room, the one that makes a partner stop probing instead of asking twenty more questions. And the three ways founders accidentally disclose a churn problem they don’t actually have, one of which is a single word in an investor update that has cost people term sheets.

Plus the NRR/GRR gap calculator itself, pre-built so you can drop in your own numbers and know which quadrant you’re actually in before anyone else tells you.

Premium subscribers get:

✅ The Retention Diligence Pack: nine diligence questions with model answers, the cohort table template, and the three silent disclosure mistakes

✅ The NRR/GRR gap calculator, ready to drop your own numbers into

✅ Every past and future proprietary framework, model and swipe file we publish

✅ Early access to new research before it goes out to the free list

Paid subscribers also get:

✅ 60+ additional tools across every stage of fundraising and company building: investor research, pitch deck screening, meeting prep, term sheet analysis, financial models, and the full investor database library.

Start your 7-day free trial → Cancel anytime.

Unlock the Full Retention Diligence Pack

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One number in it should change how you run your raise.

87.5% of all US venture dollars in the quarter went to AI companies. Every other sector in technology, fintech, healthtech, climate, marketplaces, consumer, devtools, logistics, split the remaining 12.5% between them.

It is the most skewed AI-versus-everything split PitchBook has ever recorded.

The single week the report covers makes it concrete. Lovable raised $400 million at a $13.3 billion valuation. River AI raised $1.1 billion across seed and Series A, two months after leaving stealth. CodeRabbit closed $143 million at $1.5 billion. Cognition opened talks on a round that could value it above $40 billion.

Four companies. One week. All AI.

Zoom out and it gets stranger. Global venture funding hit a record $510 billion in the first half of 2026, more than all of 2025 combined. OpenAI and Anthropic alone took more than 40% of it. In Q1, roughly 65% of every venture dollar on earth went to four companies.

If you are not building AI, you have spent the last eighteen months being told, in a hundred small ways, that the money left the room.

It didn’t. But where it went is not where you have been looking.

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The number nobody did the math on

Percentages are designed to make you feel something. Absolute numbers are designed to tell you something.

Crunchbase puts total Q2 2026 investment into US and Canadian startups at $137.2 billion.

Run 12.5% against that and you get roughly $17 billion. Deployed into non-AI companies. In ninety days.

For scale: that is more capital than the entire US venture market deployed in some full years of the early 2010s. It is not a rounding error. It is a functioning market that happens to be standing next to a much louder one.

(The two datasets do not measure identically, so treat $17 billion as an order of magnitude rather than a decimal point. The direction is not in dispute.)

Here is what actually changed, and it is not “there is no money for you.”

The money didn’t shrink. The default search path broke.

The generalist multi-stage funds that used to be the obvious first fifty names on a non-AI target list are now under enormous LP pressure to show AI exposure. They will still take your meeting. They are far less likely to lead your round. Founders keep pitching that list, keep getting warm passes, and conclude the market is closed.

The $17 billion did not come from that list. It came from nine other places.

If you’re raising right now, you’ll need to read these:

• The Number That Kills More Fundraises Than Any Bad Idea: one slide, one metric, quietly killing raises before founders even notice.

• The Quiet Filter That Decides Your Entire Fundraise: every investor runs this before you open your mouth.

• The Way VCs Actually Calculate Your Valuation: they have a number in their head before you walk in.

• How Investors Decide If You’re Ready to Raise: it’s not timing, it’s not luck, it’s a checklist.

Which of the three buckets you are actually in

Before you touch your target list, be honest about which market you are raising in. There are three positions and only two of them are viable.

Bucket 1: genuinely AI-native. The model is the product. Remove AI and there is no company. You are competing in the 87.5% market, and the bar there is brutal but the capital is limitless.

Bucket 2: honestly non-AI. You use AI internally, like everyone does, but you sell software, hardware, or a service that would exist without it. You are competing in the 12.5% market, where there is $17 billion a quarter and considerably less noise.

Bucket 3: AI-washed. AI is in the deck. It is not really in the product.

Bucket 3 is the one that kills raises, and it is the most crowded bucket in the market right now.

The logic is simple and most founders get it backwards. By putting AI at the front of your narrative, you volunteer for the 87.5% market. Once you are in it, you get measured against companies where the model is the product. “We use GPT” raised money in 2023 and raises nothing in 2026. Investors now ask one question in the first meeting: what happens when OpenAI ships this? If your AI is a feature, you have no answer, and you lose a race you never needed to enter.

Meanwhile the 12.5% market, where you would have been a credible category leader with real margins and a defensible customer relationship, never got to see you.

Being honestly non-AI is a stronger position than being unconvincingly AI. That sentence is worth more than most fundraising advice published this year.

The 9 investor categories still writing non-AI checks

These are the nine places the $17 billion actually came from. Two of them, in full, below.

Category 1: Vertical sector specialists

Funds whose entire thesis is a non-AI sector: industrials, insurance, construction, food systems, logistics, marine, energy retail. Their LPs did not give them money to chase foundation models, and they are quietly delighted that the generalists have vacated their patch.

What they screen for: domain credibility over technology novelty. They want to know you have sold into this industry before, or that someone on your cap table has. They will forgive a slower growth curve for a customer relationship they understand.

How to reach them: they are almost never on the standard “top VCs” lists your peers are working through. They show up as sponsors at industry conferences, not tech conferences. That is the search term.

Category 2: Family offices

Single-family and multi-family offices are structurally the best-positioned buyer in this market. No LP to answer to, no fund cycle forcing deployment into whatever is hot, and often an operating business in exactly the sector you are selling into.

What they screen for: durability and downside. They ask what the business looks like if it never raises again. Answer that credibly and the conversation moves faster than any VC process you have run.

How to reach them: they do not have a submission form and they do not want one. Access runs through the operating business, the wealth manager, or a portfolio founder. Warm-intro discipline matters more here than anywhere else on this list.

Categories 3 through 9, including the two that write the largest non-AI checks in the market right now and the one most founders have never seriously considered, are below.

🔒 You now know the market exists. Here is the map to it.

Everything above tells you the $17 billion is real and which bucket you are raising in. What follows is the part you can put to work tomorrow morning. Here is exactly what is waiting below:

✅ The full 9-category investor map, as a single reference table: who they are, the check size band they actually write, what each one screens for, and the specific route in. Categories 3 to 9 include corporate venture arms, revenue-based and non-dilutive capital, regional and sovereign-backed funds, lower-mid-market growth equity, operator holdcos, Fund I and Fund II emerging managers, and strategic customer-funded development.

✅ The one line that decides which market you are raising in. There is a single sentence near the top of your deck and the top of your outreach email that sorts you into the 87.5% market or the 12.5% market. Most founders write it wrong and never find out why the meetings went cold. The corrected four-part frame, with a worked before-and-after example.

✅ Three copy-paste Claude prompts: one that audits your existing deck for accidental AI-washing, one that rebuilds your positioning line against the frame, and one that generates a ranked non-AI investor target list from your actual sector and stage.

✅ The capital sequencing rule for a 12.5% raise, which is a different order of operations to a standard venture process and the reason most non-AI raises stall at week six.

Paid subscribers also get:

✅ 60+ additional tools across every stage of fundraising and company building: investor research, pitch deck screening, meeting prep, term sheet analysis, financial models, and the full investor database library.

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The one line that decides which market you are raising in

Open your deck. Find the sentence that describes what your company is. It is usually on slide one or slide three, and it is the same sentence you use in the first line of every cold email.

That sentence is doing the sorting.

The 9-category map

Read more

Let’s get into it.

First, something free 👇

The founders winning in 2026 are everywhere: LinkedIn, newsletters, podcasts, investor DMs. They run on a system that publishes for them, rather than carving out time they rarely have.

We built that system into a free AI Creator Kit: one Notion workspace with AI agents, templates, a creator CRM, and partner credits worth thousands.

Grab it here, no paywall:

Free AI Creator Kit

In-Depth Insights 🔍

• The Claude Prompt Stack for Closing Rounds in 2026 📊
  9 Claude prompts for investor research, objection handling, data-room audits, term sheets, and fundraising outreach. With the seed-to-Series-A gap at 616 days, the prompts are designed to make fundraising work more rigorous and less dependent on guesswork.

• Inside Vanta: compliance without the spreadsheet chaos 🤝
  Vanta connects 400+ integrations to automated evidence collection across SOC 2, GDPR, and ISO 27001. The platform also handles policies, risks, vendors, audits, and Trust Centers where companies can publish compliance status to customers.

• How to Build AI Loops That Improve Their Own Work 🔁
  Google’s Shubham Saboo breaks down nine components of reliable AI loops, from goals and context to evals, memory, guardrails, and stopping conditions. They also show practical loop patterns and the failure modes that matter most, including drift, weak evaluations, and runaway costs.

  

• A Tool That Matches Founders to 156 Grants in 10 Seconds 💰
  VC Pitch Conf’s grant radar scans 156 active US, UK, and EU programs against a founder’s region, sector, and stage. The database covers options from SBIR and EIC Accelerator funding to R&D tax credits and cloud credits, alongside a September investor-pitching event.

  

• A Database of 2,000+ European Family Offices 📇🔍
  The database lists more than 2,000 European family offices with named decision-makers, direct emails, LinkedIn profiles, and searchable investment criteria. The outreach strategy focuses on filtering for fit, finding operator overlap, and matching a family’s longer investment horizon instead of forcing a VC-style pitch.

• Why Software Engineers Need to Keep Thinking Slowly 🤔
  Sean Goedecke argues that constant AI-assisted context switching can crowd out the deliberate thinking engineers need to understand complex systems. His answer is writing in his own words and reading dense nonfiction, keeping the mental muscles that AI tools cannot replace. [Sean Goedecke]

• How to Find an Audience and Sell Without Ads 🎯
  Chris’s process starts by defining one specific person, then validating that profile through real Instagram followers, Reddit discussions, and audience behavior. From there, he builds hooks, titles, retention feedback, and eventually automation around the parts that have already worked manually. [Chris]

  

Social Media Gems 💎

• Silicon Valley’s Fake Prophet Called It First 😅
  Russ Hanneman joked in 2016 that revealing revenue turns a 1000x pitch into a 2x business once investors ask how much, while pre-revenue keeps the story pure. Rubén argues that satire now looks less fictional, with a large chunk of the 2026 AI market operating on the same logic.

• Google Search Now Buries the Web It Built 🌀
  Linas argues that search has shifted from finding websites to navigating Google’s own results, AI summaries, and ads before reaching the page users wanted. The irony is that Google built the system people used to explore the web, then increasingly became the destination itself. [Linas Beliūnas’]

  

• Deel’s COO Breaks Down Seven Years to $1.5B ARR 🚀
  Dan Westgarth breaks down Deel’s path from zero to $1.5B ARR and three years of EBITDA profitability across enterprise sales, acquisitions, product expansion, and global operations. He also outlines Deel’s three AI adoption phases, ending with Akai, a system designed to keep token costs under control. [Dan Westgarth]

  

• Anthropic Pulls Founders Off Their Own Startups 😳
  Rubén highlights a wave of founders and technical leaders joining Anthropic, including Andrej Karpathy, Mike Krieger, Peter Bailis, Jarred Sumner, and others.
  Most joined as Members of Technical Staff, a notable shift from running companies to spending their time building directly.

  

Trending News ⚡

• OpenAI Employees Cash Out at $852B Valuation 💰
  OpenAI closed a $7B tender offer allowing current and former employees to sell shares at an $852B valuation, its third employee liquidity deal since 2024. The timing matters as OpenAI has confidentially filed for an IPO, giving employees liquidity while the company prepares for a potential public-market debut. [CNBC]

  

• Accel Raises $550M for Its Next India Bet 📈
  Accel closed its new India fund in weeks after attracting more demand than it could take, just 19 months after its previous $650M vehicle. More than 55% of the prior fund is still uninvested, while the new capital starts deploying in 2027 across AI, fintech, consumer internet and advanced manufacturing. [TechCrunch]

• Anthropic Watermarks Claude’s Writing Without Changing It 📝
  New Claude models embed an invisible watermark that can survive copying and some edits, giving third parties a way to identify AI-generated text. Anthropic says the system supports EU transparency requirements, but heavy rewriting can remove the signal and detection alone cannot prove Claude wrote the original. [Business Insider]

• CoreWeave Raises Spending as Compute Sells Out 📈
  CoreWeave lifted its 2026 capex forecast to $35B-$39B after Q2 revenue more than doubled to $2.58B and its backlog reached $104.2B. Management says near-term capacity is effectively sold out, with more than $25B in new commitments already added this quarter as customers lock in AI compute. [Reuters]

  

• Nvidia’s Cash Is Becoming an Infrastructure Weapon 💰
  Nvidia has more than $80B in cash and marketable investments plus $50B in quarterly operating cash flow, giving it unusual room to finance the ecosystem around its chips. That capital is now funding infrastructure partnerships, chip buyers and strategic investments, letting Nvidia share both the upside and risk of AI expansion with outside investors. [Business Insider]

  

• Groq Is Putting Nvidia Chips Into Its Own Data Centers 🤝
  Groq will add Nvidia systems to its data centers, giving GroqCloud customers access to Nvidia hardware alongside Groq’s own language processing units. The move turns a former competitive threat into another Nvidia customer, following Nvidia’s $20B Groq technology deal and Groq’s continued operation as an independent company. [Business Insider]

• DeepSeek Charges a Premium for Its Stronger V4 Pro 💰
  DeepSeek priced V4 Pro at up to 14 times V4 Flash for output, reflecting a sharper split between cheaper throughput and more capable reasoning. Artificial Analysis scored V4 Pro’s reasoning model at 53 versus 40 for V4 Flash, as DeepSeek pushes to close ground with China’s leading AI labs. [Reuters]

  

New Funds 💰

• Accel raised $3.5B across four venture vehicles to back technology companies globally across early and growth stages.

• Elephant is targeting up to $700M for its sixth flagship venture capital fund to invest in software, internet, and technology companies from Seed through Series B.

• K2 Global raised $200M for a venture fund focused on investing in AI companies across foundational technology, infrastructure, and applications.

That’s a wrap for this week.

If you want to stay ahead of the curve, make sure you're subscribed. No fluff, just real startup insights delivered straight to your inbox.

See you next time 🚀

This series is a preview of a new book I’ve written with my partners Richard Blundell and Paul Watson — The Selling Software Algorithm: The Go-to-Market Navigation System for B2B Software Leaders.

It isn’t a strategy deck dressed up as a book. Between the three of us we’ve spent close to seven decades inside B2B software as founders, operators, investors and coaches — building companies, exiting some, and quietly breaking a few along the way, which is where most of the real learning lives. Through our work at Vencha we’ve now supported hundreds of founders trying to do the single hardest thing in software: turn a clever product into predictable commercial traction in a market that’s noisy, cautious, and more crowded than it has ever been.

One pattern shows up again and again. Companies rarely struggle because the product is bad. They struggle because they have no navigation system for going to market. This book is that system.

Get my Copy

Last time, we built the Solution Slide and tested it until Economic Buyers started telling us, unprompted, what would be politically difficult about buying from us. That gave you a playback they could recognise and a map of the internal resistance still ahead.

This time, we step back from the individual and look at the organisation around them again.

Table of Contents

• Why Every Deal Needs a Door, and a Doorkeeper

• Champion and Economic Buyer Are Not the Same Job

• The Wooden Spoon Test: How to Know You’re Stirring, Not Cooking

• What to Actually Ask a Champion

• When a Champion Becomes a Red Flag

• Equipping Your Champion to Sell Internally, Without You in the Room

• From Ten Testing Calls to Your Finished Algorithm

Why Every Deal Needs a Door, and a Doorkeeper

No Founder gets a straight line to the person who signs. Between you and the Economic Buyer sits someone who noticed the problem first, felt it personally, and got excited enough to take your call, forward your email, or book the second meeting. That person is your Champion, and without them, most deals never start.

The mistake isn’t having a Champion. The mistake is stopping there. A Champion can open a door. They cannot, on their own, walk you through it, sign what’s on the other side, or defend the decision when someone senior asks hard questions about it later.

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Champion and Economic Buyer Are Not the Same Job

It helps to be blunt about what each of these people actually wants, because it’s rarely the same thing.

The Champion cares about their day getting easier. They’re close to the workflow, close to the friction, and close enough to the pain that they recognise it the moment you describe it back to them. They speak your language fluently because they live the problem daily. That’s exactly why they’re so easy to mistake for the person who can say yes.

The Economic Buyer cares about something different: whether the decision is defensible. Not whether the software is clever, not whether the demo went well, but whether buying it can be justified to a CEO, a Board, or a Finance team asking why this and why now. They carry the budget line and the accountability that comes with it, and no amount of Champion enthusiasm transfers that accountability to them by osmosis.

Frameworks like MEDDICC exist precisely because this confusion is so common and so costly. Metrics, Decision Criteria, Decision Process, Identify Pain, Champion, Competition, all matter, but early in a deal, it’s the gap between Champion and Economic Buyer that tells you whether an opportunity has a pulse or is just warm noise.

The Wooden Spoon Test: How to Know You’re Stirring, Not Cooking

Keep a wooden spoon somewhere visible. Not as a gimmick, as a diagnostic.

If you can build a strong relationship with a Champion, run excellent demos for their team, gather positive feedback, and refine proposals for weeks, and still find yourself unable to answer the simple question “who signs this,” you are stirring the same pot over and over. Adding ingredients. Adjusting the seasoning. Convincing yourself something is cooking, when nothing is ever going to come to the boil.

This isn’t usually because your Champion misled you. It’s because enthusiasm without authority does not create sales, however genuine the enthusiasm is.

What to Actually Ask a Champion

Once you can name your Champion clearly, the second testing discipline begins: using them properly, rather than just liking them.

Ask what would be politically difficult about this internally. Ask who else needs to be comfortable before a decision like this gets made. Ask what’s happened before when a similar project stalled, and why. A good Champion, treated as a research partner rather than a warm lead, will tell you almost everything you need to know about the real shape of the deal, including the parts that never show up in a demo.

Ask, too, for access. Not access for a pitch, access for accuracy. Framing a request for time with the Economic Buyer as necessary to avoid recommending the wrong thing internally lands very differently to a vague ask for “alignment,” and it rarely feels like an imposition to a Champion who genuinely wants the project to succeed.

If you’re raising right now, don’t skip these

• The Number That Kills More Fundraises Than Any Bad Idea: one slide, one metric, and it’s quietly killing raises without founders ever knowing it.

• The Quiet Filter That Decides Your Entire Fundraise: every investor runs this before you even open your mouth. Learn it now, not after the “no.”

• The Way VCs Actually Calculate Your Valuation: they already have a number in their head before you walk in. Here’s how to hit it.

• How Investors Decide If You’re Ready to Raise: it’s not timing, it’s not luck. These are the exact criteria they’re using on you right now.

• The Pitch Deck Test Investors Use: the same test gets applied to every deck that crosses their desk, including yours.

When a Champion Becomes a Red Flag

Access delayed once is normal. Diaries are difficult and priorities shift. Access delayed repeatedly, deflected, or quietly discouraged is a signal, and it’s usually not a technology signal, it’s a confidence signal.

Champions who resist involving the ultimate decision-maker are often protecting uncertainty rather than protecting progress. Sometimes they’re not yet sure the project will get funded. Sometimes they’re worried about how it will look if they’ve championed something that goes nowhere. Either way, the earlier you notice this pattern, the more months of wasted proposal-writing and feature-adjusting you save yourself.

Be prepared, at least mentally, to walk away from deals that never clear this bar. A Champion who cannot or will not open the door to the Economic Buyer, after several professional attempts, is telling you something true about how real this opportunity is.

Equipping Your Champion to Sell Internally, Without You in the Room

Assuming access does open up, your job shifts. A good Champion will be in rooms you’re never invited to, explaining your solution to people who’ve never met you, using language you didn’t choose. Your responsibility is to make that easier for them, not harder.

Give them a version of your Pain and Solution Slides they can present themselves, stripped of anything that only makes sense with you narrating it. Give them a short, plain-English summary of the business case, written the way an Economic Buyer talks, not the way a software company talks. Give them the proof points, the reference customer, the metric, the before-and-after, so that when someone senior pushes back, they’re not improvising.

Champions who feel equipped advocate with more confidence. Champions who feel exposed go quiet exactly when you need them to speak up.

From Ten Testing Calls to Your Finished Algorithm

Across ten or more of these conversations, the same pattern starts repeating. The Champions who move fastest are the ones who name the Economic Buyer early, without being asked twice. The ones who stall are almost always protecting something, usually uncertainty about whether this will actually happen. That repetition is the evidence. It turns a founder’s instinct into a commercial discipline the whole team can run without you in the room.

This is exactly what Builder Step 3 exists to hold: the Champion Profile, assembled from who opened the door, what they told you about the politics behind it, and how quickly they got you to the person who signs.

Next in the series, we look at what happens once the Champion and the Economic Buyer are both engaged, and turn to the Mutual Success Plan: the document that quietly does the work of making procurement feel like a formality rather than a fight.

-Chris Tottman

Most founders build a Solution Slide from what they wish were true rather than what ten buyers actually told them.

That’s the gap the Selling Software Algorithm Builder exists to close. Step 3 assembles your algorithm sentence from what you’ve already tested, so your whole team can repeat it word for word. Built your algorithm sentence below:

Start your 7-day free trial → Cancel anytime.

Read more

One cold email to a partner. One warm intro request to a portfolio founder. One investor update. One follow-up after a meeting that went quiet. One data room answer at 11pm because a diligence associate found something in your metrics that doesn’t match what you said three weeks ago.

None of these are hard on their own. The problem is volume. A typical seed or Series A raise runs eight to twelve weeks and touches thirty to eighty investors. That’s not one pitch - it’s the same pitch, retold with slightly different words, dozens of times, usually while you’re also trying to run the company you’re raising for.

Most founders handle this by opening Claude or ChatGPT fresh every time and re-explaining their traction, their tone, their numbers, their ask. That works fine for one email. It falls apart at email forty, when fatigue creeps in and the story starts to drift - a slightly different ARR number here, a softer answer to the competition question there. Diligence teams compare notes. Drift is the tell that gets a deal killed quietly, without anyone telling you why.

Claude Skills fix the drift.

Table of contents

1. Skill 1 - Investor Fit Decoder

2. Skill 2 - Cold Outreach Email Builder

3. Skill 3 - Warm Intro Request Drafter

4. Skill 4 - Pitch Narrative Architect

5. Skill 5 - Adversarial Pitch Stress-Test

6. Skill 6 - One-Pager Generator

7. Skill 7 - Metrics Definition Auditor

8. Skill 8 - Data Room Q&A Responder

9. Skill 9 - Reference Call Prep Brief

10. Skill 10 - Investor Update Writer

11. Skill 11 - Board Deck Summarizer

12. Skill 12 - Post-Meeting Follow-Up Drafter

13. Skill 13 - Term Sheet Translator

14. Skill 14 - Cap Table Impact Modeler

15. Skill 15 - Negotiation Prep Brief

What a Skill Actually Is

A Skill is a markdown file that teaches Claude a process once, your numbers, your voice, your definitions, your standards, and then applies it automatically every time a matching task comes up. You’re not writing a better prompt. You’re writing the instructions down permanently, so Claude never needs the context re-explained.

The difference in practice: a prompt disappears the moment the chat ends. A Skill activates on its own, the next time and every time after, whether it’s you typing or a co-founder covering outreach while you’re in back-to-back partner meetings.

How to build any Skill below:

1. Open a new Claude chat

2. Paste the prompt under the Skill you want

3. Claude generates the SKILL.md file

4. Save it via Settings → Capabilities → Skills

Do this once for each Skill you actually need. Fifteen minutes of setup against eight weeks of raise.

One thing to build before any of these: a short reference file with your real numbers - ARR, burn, runway, round size, valuation expectation, the three objections you hear most. Every Skill below performs better when it can read that file first. Without it, you get competent generic output. With it, you get output that sounds like you already thought this through.

If you’re raising right now, you’ll need to read these:

• The Number That Kills More Fundraises Than Any Bad Idea: one slide, one metric, quietly killing raises before founders even notice.

• The Quiet Filter That Decides Your Entire Fundraise: every investor runs this before you open your mouth.

• The Way VCs Actually Calculate Your Valuation: they have a number in their head before you walk in.

• How Investors Decide If You’re Ready to Raise: it’s not timing, it’s not luck, it’s a checklist.

Category 1: Targeting and outreach

Skill 1 — Investor Fit Decoder

Takes a fund or partner’s public thesis, recent portfolio additions, and check size, and tells you honestly whether they’re a fit, a stretch, or a waste of both your time — before you write a single word of outreach.

Why founders use it: Ten minutes deciding whether to email beats three weeks waiting on a reply that was never coming. The founders who get responses aren’t emailing more investors - they’re emailing the right five.

Help me create a Skill called "Investor Fit Decoder" that
evaluates whether a specific investor is a genuine fit before
I send outreach.

When invoked, ask me for:
1. Investor or fund name, and what I know about their thesis
2. Their stated stage, check size, and sector focus
3. My one-line company description and current stage
4. Any known portfolio companies I could reference

Output:
- Verdict: Strong fit, Worth a shot, or Skip
- The specific reason for the verdict, not a generic one
- If a fit: the strongest comparable portfolio company to
  reference in outreach, and why
- If not a fit: what would need to change for this to work later

Be honest even when the honest answer is "skip this one."
Save as a permanent Skill.

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Skill 2 — Cold Outreach Email Builder

Writes a first-touch investor email anchored to their actual thesis, not a generic “we’re raising a seed round” template. Pulls in your traction, your ask, and a specific reason this partner, right now.

Why founders use it: A partner can tell within one sentence whether an email was written for them or copy-pasted to forty other inboxes. This Skill removes the copy-paste tell every time.

Help me create a Skill called "Cold Outreach Email Builder" that
writes investor-specific first-touch emails.

When invoked, ask me for:
1. Investor name, fund, and their known thesis or focus area
2. My company one-liner, traction highlight, and round details
3. The specific reason I'm reaching out to this person
4. Any warm signal (mutual connection, content they've published)

Output:
- Subject line, under 8 words, specific not clever
- 3-paragraph body: the specific hook for this investor,
  the traction proof point, the clear ask
- One sentence they could forward to an associate without editing

Under 150 words total. No adjectives doing the work numbers
should do. Save as a permanent Skill.

🔒 You’ve found the two Skills that get you into a room. Here’s what turns those meetings into a closed round.

Everything above already puts you ahead of most founders walking into their next raise. Here’s exactly what’s waiting below the paywall:

✅ Skill 3 - Warm Intro Request Drafter. The forwardable note that gets a mutual connection to say yes without doing your selling for you.

✅ Skill 4 - Pitch Narrative Architect. Rebuilds your story in the order it needs to land for an investor, not the order it happened to you.

✅ Skill 5 - Adversarial Pitch Stress-Test. Claude plays the skeptical partner looking for the reason to pass, before a real one gets the chance.

✅ Skill 6 - One-Pager Generator. The single-page summary that actually gets forwarded to other partners.

✅ Skill 7 - Metrics Definition Auditor. Locks your numbers so nothing you say in week eight contradicts what you said in week one.

✅ Skill 8 - Data Room Q&A Responder. Diligence answers checked against your own locked definitions before they go out.

✅ Skill 9 - Reference Call Prep Brief. Gets your references ready for the questions before the investor asks them.

✅ Skill 10 - Investor Update Writer. The exact format that gets forwarded to other partners without editing.

✅ Skill 11 - Board Deck Summarizer. Turns a forty-slide deck into the two-minute pre-read your board actually opens.

✅ Skill 12 - Post-Meeting Follow-Up Drafter. The specific, fast follow-up that beats the generic “great meeting today” every time.

✅ Skill 13 - Term Sheet Translator. Every clause in plain English, with the ones that actually matter flagged.

✅ Skill 14 - Cap Table Impact Modeler. What a term sheet does to your real ownership, modeled against your actual numbers before you sign.

✅ Skill 15 - Negotiation Prep Brief. What to push back on, what to accept, and the language to use for each.

✅ The full fifteen-Skill system, copy-paste ready, built to adapt to your own round. Swap in your numbers, your voice, and your investors, and run it for the rest of your raise.

Paid subscribers also get:

✅ 60+ additional tools covering every other stage of fundraising and running a company: pitch deck screening, investor research, meeting prep, term sheet analysis, and data room management. The same system this Skill library came from.

Start your 7-day free trial → Cancel anytime.

Skill 3 — Warm Intro Request Drafter

Writes the short note you send a mutual connection asking for an introduction - the version that’s easy to forward, not the version that makes the connector do your selling for you.

Read more

No fund. No LPs. No committee.

Just his own money and his own judgment.

By the time TechCrunch profiled him in 2021, that habit had produced 33 documented investments. One of them was an early check into what would become Paystack. Stripe later acquired it for a reported $200M.

Nobody at Sequoia approved that decision. Nobody at a16z was in the room.

One person decided. The money moved.

That’s the entire category this issue is about.

Founders spend enormous energy mapping the venture capital landscape. Who’s raised what fund. Who’s on partner track. Who’s “still deploying” this quarter.

Almost none of that energy goes toward an older, much less visible source of capital: individuals who write checks with their own money, on their own timeline, answering to no one.

We spent the last several weeks building a working directory of 184 of them. Across the US, UK, Europe, India, Southeast Asia, Australia, Japan, China, Israel, Africa, and Latin America.

Not firms. Not funds. People.

Here’s a sense of what’s in it, why this category behaves so differently from the institutional world, and what’s waiting in the full directory for Premium subscribers.

The four kinds of angel, and why the difference matters

Not all individual checks come from the same kind of person. The distinction changes how you should approach each one.

The self-publishing angel. These are the easiest to research, and often the easiest to reach, because they’ve already told you exactly what they want. Fabrice Grinda has written on his own blog about a personal portfolio that press has pegged in the hundreds of companies. Charlie O’Donnell has run the same personal blog documenting his NYC pre-seed thesis for over a decade. Elizabeth Yin built a public following around her own investing philosophy before she and her co-founder ever raised outside capital for Hustle Fund. If someone in this category has published their thesis, your job is to prove you read it. Not to pitch them the generic version of your deck.

The operator-angel. Someone who built or sold something, and now recycles capital and pattern recognition back into people doing what they used to do. Auren Hoffman built SafeGraph and LiveRamp before becoming known in press for well over 200 personal angel checks. Immad Akhund runs Mercury and is publicly known for the personal angel investing he discusses on his own X account. These people are pattern-matching against their own operating experience. The strongest pitch to them sounds like a peer conversation, not a fundraising ask.

The solo GP. Technically a fund, but functionally a single decision-maker who moved fast enough that “angel speed” became their whole brand. Charles Hudson at Precursor. Semil Shah at Haystack. Turner Novak at Banana Capital. The check comes from a vehicle, but the yes or no is one person’s call, usually within days, not months.

The syndicate lead. Someone who has built enough personal credibility that other people’s money follows their judgment. Joakim Achrén runs a 220-member gaming syndicate out of Helsinki most founders outside gaming have never heard of. Jennifer Kan runs a named climate syndicate. Getting time with the lead is often more valuable than the check itself. Their yes brings other checks with it.

Knowing which of the four you’re emailing changes the entire message.

What the regional pattern actually tells you

The directory isn’t evenly spread. The unevenness is informative.

The densest cluster of self-published, easily researchable individual angels sits in the US. Unsurprising, but worth noting why. American operator culture treats a public angel portfolio as a personal brand asset. So the research trail (blogs, newsletters, podcast appearances) is unusually rich.

Africa tells a different, and frankly more interesting, story. The individual angels we found there are concentrated heavily around Lagos, and they are almost entirely founders reinvesting their own exits directly back into the next generation of companies. Shola Akinlade (Paystack) and Olugbenga Agboola (Flutterwave) aren’t professional investors moonlighting as angels. They’re operators for whom angel investing is a direct, personal extension of having just built the thing themselves. If you’re building in African fintech, these are conversations with people who solved your exact problem in the last five years. Not investors who read a memo about it.

Israel’s angel scene skews toward longevity rather than volume. Zohar Gilon has been at this for roughly two decades. Globes describes him as sitting “at the apex” of Israeli angels, with something in the neighborhood of 160 companies backed. That’s not a person chasing a hot sector. That’s a person whose judgment has been tested across multiple downturns, which is exactly the kind of angel worth having in a hard round.

And the climate-tech and gaming clusters barely overlap with the “famous angel” list at all. They run almost entirely on syndicates (Climate Avengers, Climate Insiders, EGD Angel Syndicate) most generalist founders have simply never encountered, because they don’t show up in general startup press. If you’re in either category and you’re only pitching generalist angels, you’re skipping the people most likely to actually understand what you’re building.

Why this category is underpriced by most founders

VCs operate on a clock. A fund has a deployment period, a reporting cycle to LPs, and eventually a fundraise of its own that depends on showing enough deployed capital and enough markups. That structural pressure is why the same 40 to 50 firms get pitched relentlessly. They have to say yes to someone, on a schedule, whether or not this is the best possible month for it.

Individuals answering only to themselves don’t have that pressure. That cuts both ways.

The upside: no committee, no partner-track politics, no “let me run this by the team.” If the person you’re talking to is convinced, the money can move in days.

The downside: no obligation to reply at all. A cold, generic pitch to someone with zero deployment pressure is trivially easy to ignore, because ignoring it costs them nothing.

That second point is the real reason most founders underuse this category. Not because the people are hard to find, but because the approach that works on a VC associate (persistence, volume, a clean deck) actively backfires here. The angels who publish their own thesis are telling you, in their own words, exactly what would make them say yes. Almost nobody reads it before pitching them anyway.

What’s actually inside the full directory

The version unlocked for Premium subscribers is the complete working file. Not a summary.

• 184 individually verified people, organized by region and by type (self-publishing angel, operator-angel, solo GP, syndicate lead)

• Current role, affiliation, and sector focus for every entry

• Publicly documented notable investments, cross-checked across multiple sources, with inflated or unverifiable portfolio counts deliberately excluded rather than repeated uncritically

• A note on exactly how each person is publicly known as an angel, so you know precisely where to go and read their own words before you reach out

• A firm/affiliation index and a region-by-region breakdown for fast filtering

A preview of what’s locked inside

We’re not spoiling all 184. Here’s a taste of who’s waiting behind the paywall.

🔒 A Brooklyn solo GP who has published the same personal investing blog for over a decade, and still writes checks up to $250K directly from it

🔒 A Kenyan accelerator CEO whose portfolio companies have created 200+ jobs, quietly one of East Africa’s most active individual backers

🔒 A Finnish gaming syndicate lead running 220 members and 30+ investments most Western generalist founders have never heard of

🔒 A Thiel Fellow turned longevity-biotech solo GP whose second fund closed at $22M, and who still personally reviews every deal

Every one of those is a real, sourced entry in the sheet. Name, affiliation, and exactly how to start researching them properly before you reach out.

Why we built this as a Premium asset

We don’t gate news recaps you could read anywhere. We gate the research that changes what you do this week. The kind of proprietary list that would otherwise cost real money through an institutional data provider, or real hours doing it yourself one profile at a time.

Premium subscribers get:

• The full 184-entry Individual Angel Directory, this issue

• Every past and future proprietary database and framework we publish

• Early access to new research before the free list sees it

• No filler, no ads. Just the operator-grade material

If you’ve been on the fence about upgrading, make it this issue. One real conversation with the right individual, someone who can just decide and just wire it, can move faster than three institutional intros combined.

Paid subscribers also get:

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Let’s get into it.

First, something free 👇

The founders winning in 2026 are everywhere: LinkedIn, newsletters, podcasts, investor DMs. They run on a system that publishes for them, rather than carving out time they rarely have.

We built that system into a free AI Creator Kit: one Notion workspace with AI agents, templates, a creator CRM, and partner credits worth thousands.

Grab it here, no paywall:

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In-Depth Insights 🔍

• The Fundraising Agent That Runs Your Raise 💰
  Persistent fundraising systems outperform isolated prompts by maintaining context, follow ups, and consistent execution over time. Personalized outreach and disciplined investor tracking improve response rates in an increasingly competitive funding market. []

• The State of Intelligent Finance: AI, Agents, Trust 📊
  Consumers are becoming more comfortable using AI for financial decisions, but confidence depends on clear accountability. Human oversight, transparency, and reimbursement policies remain central to building trust in autonomous financial tools. [PLAID]

  

• The $10K Etsy Niche Built With Claude 🛍️
  A niche business becomes more durable when products, storefronts, and content feed the same audience instead of operating separately. The long term advantage comes from building an owned email list that compounds beyond marketplace sales alone.

  

• How to Eliminate Churn Before It Eats Your Growth 📉
  Retention starts with the right customers and fast activation rather than relying on cancellation flows to reduce losses. Payment recovery, annual plans, and expansion revenue strengthen growth, but solving early user friction matters most.

  

• Claude Cowork Runs a $10K SEO Agency 🤖🔍
  AI search is reducing organic traffic, making technical optimization and search intent analysis more valuable than rankings alone. Structured workflows help automate audits, research, and competitive analysis that previously required dedicated agency support.

  

• Run McKinsey Grade Diligence on Yourself 📁
  Founders who audit their own business before fundraising uncover weaknesses investors are likely to identify first. Organized documentation, structured reviews, and early fixes improve readiness before entering investor conversations.

  

• The Only Moat That Survives AI 🏰
  As models improve, execution shifts from generating answers to verifying whether outputs meet real world standards. Systems that continuously collect verification feedback build stronger data advantages with every completed transaction. [Kim “Chubby” Isenberg]

  

• Forward Deployed Executives: The Next Billion Dollar Unblock 🔓
  Many enterprise AI projects stall because organizations struggle with adoption rather than technical capability. Leaders who combine technical expertise with operational execution help companies turn pilots into measurable business results. []
  

Social Media Gems 💎

• 10 Financial Models Every Founder Should Build 📊
  The collection covers runway, SaaS metrics, valuation, FP&A, cohorts, M&A, exit planning, and fundraising scenarios. Strong financial models help founders answer investor questions with clear assumptions instead of rough estimates.

• 10 Claude Playbooks for Daily Work 📚
  The library covers coding, GTM execution, research, SEO, spreadsheets, presentations, and knowledge management workflows. The playbooks focus on practical operating systems that reduce repetitive work across business functions.

• Your Work Laptop Predicts Your Career 😂
  A Dell signals repeated warnings, a MacBook suggests runway protection, and a ThinkPad points to long weeks ahead. The joke reflects how startup culture stereotypes hardware as a proxy for company stage and job security.

  

• China Eliminates EV Charging Delays ⚡
  BYD introduced charging speeds close to refueling a gasoline vehicle, reducing one of the biggest barriers to EV adoption. China’s strategy continues to move from competing on cost to leading on performance across key technologies.

• Financial Models That Stand Up to Diligence 💰
  The templates include SaaS planning, revenue forecasting, runway analysis, valuation, cohorts, M&A, and exit modeling. Founders who prepare detailed models are better equipped for investor diligence beyond the initial pitch.

• The 8% Driving Economic Growth 📊
  Most sectors have expanded slowly while computer equipment, software, and R&D continue to account for outsized growth. The data highlights how technology spending remains concentrated even as broader economic activity stays subdued. [Eric Basmajian]

  

Trending News ⚡

• Hugging Face Pushes AI Breach Disclosure 🔓
  Hugging Face CEO Clem Delangue said AI companies should disclose cyberattacks instead of restricting model releases. He argued wider model access strengthens defenses, pointing to open source tools used after the OpenAI breach. [Business Insider]

• DeepSeek V4 Flash Sets New Cost Benchmark 💰
  DeepSeek’s V4 Flash costs roughly three cents per test run, making it the lowest cost model measured by Artificial Analysis. Its performance matched Google’s Gemini 3.6 Flash while remaining behind OpenAI and Anthropic’s strongest models. [Reuters]

• Big Tech Rebuilds The AI Super App 📱
  Google, OpenAI, Anthropic, and Microsoft are consolidating AI products into broader assistant platforms. The strategy mirrors WeChat by combining workflows into a single interface instead of separate applications. [BusinessInsider]

  

  
  

• Nvidia Backed AI Alliance Ships SAFE Framework 🖥️
  The Open Secure AI Alliance released its first SAFE proposals for reporting AI cybersecurity incidents just one week after launching. More than 120 companies joined the effort, while Anthropic, OpenAI, and Google remain outside the alliance. [TechCrunch]

  

  
  

• Meta Confirms Muse Spark Security Incident ⚠️🔓
  Meta said its Muse Spark model exploited a third party security vulnerability during testing after a misconfigured evaluation environment. The disclosure adds Meta to a growing list of AI labs reporting agent security incidents alongside OpenAI, Anthropic, and Hugging Face. [Business Insider]

  

• Meta Unveils Muse Code Coding Agent 💻
  Meta introduced Muse Code with usage based pricing that undercuts subscription focused coding assistants. A discounted contributor tier lowers costs while allowing user activity to improve Meta’s models. [Business Insider]

• Google Reshapes AI Leadership Team 🔄
  Demis Hassabis will become Alphabet’s chief scientist while Koray Kavukcuoglu assumes leadership of DeepMind. Jeff Dean is leaving Google to launch Discovery Loop with Sanjay Ghemawat after decades at the company. [Business Insider]

  

  
  

• OpenAI Expands ChatGPT Advertising Markets 📢
  ChatGPT ads are rolling out to Brazil and Mexico alongside new carousel formats for Free and Go users. OpenAI also introduced stronger campaign tools and signaled future testing of sponsored AI agents. [Business Insider]

  

New Funds 💰

• Index Ventures announced $2B in new venture capital funds to invest in startups from seed through growth stages across Europe, the U.S., and Israel.

• Continuim Equity Partners closed its oversubscribed Fund III at $548M, surpassing its target to invest in lower middle-market industrial, manufacturing, distribution, and business services companies across North America.

• U.S. Venture Partners (USVP) is raising up to $400M for its 14th flagship venture capital fund to back early-stage startups across enterprise, healthcare, and frontier technologies.

• Robinhood Ventures launched Fund II to continue investing in early-stage startups across fintech, AI, infrastructure, and consumer technology.

That’s a wrap for this week.

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See you next time 🚀

This series is a preview of a new book I’ve written with my partners Richard Blundell and Paul Watson — The Selling Software Algorithm: The Go-to-Market Navigation System for B2B Software Leaders.

It isn’t a strategy deck dressed up as a book. Between the three of us we’ve spent close to seven decades inside B2B software as founders, operators, investors and coaches — building companies, exiting some, and quietly breaking a few along the way, which is where most of the real learning lives. Through our work at Vencha we’ve now supported hundreds of founders trying to do the single hardest thing in software: turn a clever product into predictable commercial traction in a market that’s noisy, cautious, and more crowded than it has ever been.

One pattern shows up again and again. Companies rarely struggle because the product is bad. They struggle because they have no navigation system for going to market. This book is that system.

Get My Copy

We’ve spent two articles getting precise about who you’re selling to.

The Economic Buyer, understood as a human being with ambition, pressure and personal risk, not a job title. The Perfect Customer Profile, the exact kind of company where your value is inevitable rather than merely possible. That’s real work, and if you’ve done it, you’re already ahead of most of the market.

But precision about who doesn’t close anything on its own.

Because software isn’t bought on logic. It’s bought when business pain becomes impossible to ignore. You can have the right buyer, in the right company, and still lose the deal, because nothing you’ve said has made staying the same feel more dangerous than changing. That’s the job of this chapter: finding the one or two pains so sharp your buyer feels compelled to act now, and willing to fight for you when procurement slows things down and the organisation’s inertia pushes back.

Table of Contents

1. Most Founders Get Pain Backwards

2. Borrow the Oldest Trick in Advertising

3. Build the Pain Slide, Not the Pitch Deck

4. The First Rule of Testing: Don’t Sell Anything

5. The Pain Wheel: From Ten Down to Three

6. The Solution Slide Is the Mirror Image of the Pain

7. Weaponise the Three Pains, Respectfully

   ---

1. Most Founders Get Pain Backwards

Ask most founders what pain their software solves and you’ll get a list. Sometimes a long one. Efficiency gained, time saved, cost reduced, risk mitigated, workflows streamlined — all true, and all, on their own, useless. Breadth doesn’t create conviction. Ten irritations laid side by side just look like a features page with better adjectives.

What actually moves a deal isn’t ten reasons to change. It’s one or two pains so sharp the Economic Buyer can’t rationalise doing nothing for another quarter, backed by a second and third pain that reinforce the case when someone in procurement asks why this can’t wait.

That’s a different kind of work than most go-to-market teams do. It’s not cataloguing everything that’s broken inside your customer’s business. It’s uncovering the hierarchy of pain — the one thing that makes delay feel dangerous, and the two things that back it up when internal resistance appears, as it always does.

And here’s the part that trips people up: pain doesn’t live in strategy documents. It lives in the quiet apology a manager makes when targets slip. In the tension between two departments who’ve stopped trusting each other’s numbers. In the dread that creeps in before a Monday morning stand-up. Until you can name that, precisely, no amount of ROI modelling will move the needle.

2. Borrow the Oldest Trick in Advertising

Before we get into how you find those pains, it’s worth understanding why naming them works at all.

Think about how transformation gets sold in fitness, health or cosmetics. The before-and-after photo. The classic image of a smile before and after orthodontic work. No explanation is required — the brain registers instantly what’s wrong, what’s possible, and what staying the same costs.

B2B software runs on the identical psychological mechanism, even though nobody’s showing anyone their teeth. The transformation here is professional rather than physical: chaos to control, friction to flow, apology to confidence. The “before” isn’t a face, it’s a process — a workflow, a handover, a spreadsheet that shouldn’t still exist. But the effect is the same. When you show a buyer their own broken process laid bare, and then show them what life looks like without it, you force them to confront the cost of inaction in a way that a features list, however well argued, never will.

That’s the entire logic behind what we call a Pain Slide and a Solution Slide. The before, and the after.

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3. Build the Pain Slide, Not the Pitch Deck

A Pain Slide is the B2B equivalent of the “before” photo. Its job is to lay bare the messy, fragmented, exhausting reality your Perfect Customer is currently living inside — and it should be uncomfortable to look at, because the world it’s describing is uncomfortable to work in.

You build it by gathering your team, again, and asking everyone in customer success, product, sales and support to write down every pain they’ve observed or heard, not just the functional frustration but the emotional one — the moment of embarrassment, the stress, the confusion. Spread it across a wall. Cluster it. Patterns will emerge fast; certain frustrations will show up so often their significance becomes impossible to miss.

Then shape those clusters into a story. Follow one user through a working day, or one workflow from start to finish, and reveal the friction one layer at a time — a progressive reveal in a tool like PowerPoint or Miro, not a static wall of chaos. The first click shows a single task beginning. The next reveals a missing piece of information. The next, the first duplication of effort. Gradually the slide gets heavier, noisier, more familiar — spreadsheets stacking up, “sorry for the delay” email threads, handwritten workarounds. That’s deliberate. The slide should feel exhausting because the process it depicts is exhausting.

Done well, a Pain Slide is a mirror. The buyer doesn’t just see inefficiency. They see the reputational risk and political cost their team has been quietly absorbing for years. And once they see it, they can’t unsee it.

4. The First Rule of Testing: Don’t Sell Anything

Here’s where most founders sabotage their own good work. They build a strong Pain Slide, fall in love with it, and skip straight to using it as a pitch.

Don’t. Test it first, with real Economic Buyers who sit inside your Perfect Customer Profile — people who actually live the pain you think you’re solving. Aim for around ten conversations. Frame them honestly, as structured research rather than a sales call: there’s nothing to buy and nothing to decide, you just want to check whether what you’ve mapped reflects their world.

That framing matters more than it sounds like it should. It disarms the buyer and shifts them out of “being sold to” and into “helping you get it right” — which means they’ll tell you the truth. Walk them through the Pain Slide slowly, one reveal at a time, and watch as much as you listen. The lean forward, the raised eyebrow, the rueful laugh — these tell you more than their most polished sentence will.

Real validation is unmistakable. Buyers get specific. They name colleagues. They relive a meeting that went badly. Polite agreement — “yeah, that looks about right” with no detail behind it — is a warning sign, not a win. Politeness kills truth, and truth is what you’re there to collect.

One discipline above all others: resist the urge to pitch. When a buyer describes a pain you recognise, every instinct says “we can fix that.” The moment you say it, you’ve stopped being a researcher and started being a salesperson, and their guard goes back up. Sit with the discomfort. If the pain is real, they’ll ask for the solution in their own time.

5. The Pain Wheel: From Ten Down to Three

By the end of a handful of these conversations, you’ll usually be looking at more pain than you started with, not less. Organisations accumulate pain the way stones accumulate in a riverbed — some merely inconvenient, others corrosive. To make sense of it, we use something we call the Pain Wheel: the ten most significant pains surfaced across your team’s whiteboarding and your early testing, laid out as a hypothesis for the buyer to react to.

Presented this way, ranking becomes instinctive in a way it never is in the abstract. Ask which pains they see every day, which ones derail projects, which ones cause friction across their teams, which ones expose them personally. Their reasoning tells you whether a pain is functional (it slows work down), emotional (it drains morale or credibility) or strategic (it exposes the business to real threat) — and some sit far closer to the buyer’s heart than others.

Walk through the top pain, then the second, then the third, asking each time what it costs and what it disrupts. Don’t rush this part. You’re not extracting data, you’re uncovering meaning, and by the end you’ll almost always see three pains rise clearly above the rest — the ones with stories attached, with stakes attached, with consequences attached. The remaining seven stay part of the narrative, but they’re convincers now, not protagonists.

This is the moment the whole chapter is built around. It’s the clarity no amount of desk research could ever hand you, and it’s what lets everything downstream — your messaging, your demo, your outreach — be grounded in evidence instead of hope.

6. The Solution Slide Is the Mirror Image of the Pain

Once the Pain Slide is tested and refined, build its opposite: the Solution Slide. If the Pain Slide is the storm, this is the calm that follows — the ordered, confident picture of what life looks like once the pain is gone. Not a prettier product overview, and not a features list wearing a nicer font. It has to be built around the specific top three pains your testing surfaced, not your own view of what matters, or it won’t land with anything like the same force.

Bring it into a second testing call, but don’t open with it. Start by playing back what you heard the first time, and ask what’s lingered in the buyer’s mind since. That reawakens the pain before you offer the relief. Then walk through the Solution Slide calmly, inviting the buyer to critique it — what would be politically hard internally, what might block adoption, who holds the veto. Those objections aren’t setbacks. They’re the headwinds you’ll actually face in a real sale, handed to you for free.

It’s also where you find the buyer’s personal win. Ask what would be different for them — less stress, a target finally hit, a Board update they no longer dread. When someone tells you that, you’ve found the emotional anchor that carries a deal through everything that tries to stall it later.

And if the second call ends badly — “this really isn’t for us” — that’s not a failure either. It’s a far cheaper lesson than discovering the same thing twelve months and a lot of wasted marketing spend from now.

7. Weaponise the Three Pains, Respectfully

Once you’ve earned your three visceral pains, the job is to embed them everywhere, deliberately, so the business can’t drift back into generic language.

Your website should stop sounding like every other software company and start sounding like your Economic Buyer’s internal monologue — because in a world of infinite noise, the only messages that cut through are the ones that feel painfully specific. Your outbound should stop asking for time and start describing their reality back to them, calmly, so the right person recognises themselves in a sentence. Your demo should stop explaining what your product does and start relieving the pain you already know, in detail, is keeping them up.

Here’s what that looks like written down, using the same formula from articles one through three:

Our software is perfect for the COO or Head of Operations in UK-based logistics and field service businesses with 250 to 2,000 employees, turning over £25m–£300m, who run multi-site operations on spreadsheets and email. They’re struggling with three visceral pains: operational visibility that collapses under pressure, repeated service failures caused by manual handovers and stale data, and constant internal firefighting that’s burning out their teams and putting their own credibility at risk.

Notice what that does. It names the buyer. It draws hard boundaries around the company. It names how they’re currently coping. And it describes pain with emotional weight attached, not just process inefficiency. You feel the world it’s describing. That’s what you’re aiming for — not ten “nice to fix” irritations, but three “cannot continue like this” truths that justify budget, survive scrutiny, and get defended internally when the organisation’s inertia inevitably pushes back.

Get that right, and pricing gets easier too, because you’re no longer negotiating software. You’re helping someone justify removing a pressure that’s already been costing them reputation, energy and control.

—Chris Tottman

Most founders lose their raise before they ever send the first email.

The ones who close have something the rest don’t: they know exactly how investors read a pitch deck before you’re even in the room, which AI prompts are quietly transforming how founders prepare, how to turn a cold outreach into a warm conversation, what a two-minute briefing can do that a ten-slide deck can’t, how to stress-test your pitch before an investor ever sees it, and how to build a fundraising narrative that actually sticks.

That edge isn’t luck. It’s 30 years sitting across the table from founders, 500+ investments, and the patterns that quietly decide who gets funded and who gets ghosted — now distilled into a system you can use today.

We’ve packaged all of it into 60+ premium tools. One subscription.

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Start with these six. They’ve already changed the outcome for thousands of founders before you — here’s what happens when it’s your turn:

Your Pitch Deck’s First Reader Isn’t Who You Think — Before any human sees it, something else decides its fate. Know what it is before you hit send.

The 6 Claude Prompts That Change How You Raise — Most founders use AI to write emails. The ones closing rounds use it like this instead.

The Claude Prompt That Turns a Cold Outreach Warm — One prompt. The difference between ignored and in the room.

The Two-Minute Investor Briefing — Investors don’t have time. This format respects that — and gets the meeting anyway.

I Asked Claude to Reject My Pitch — Here’s What It Found — The holes investors find but never tell you about. Find them first.

How to Build Your Fundraising Narrative — Not your deck. Not your numbers. The story that makes both of them land.

Every raise has two sides: the founders who get the meeting, and the ones who wonder why they didn’t. Upgrade now — and make sure you’re on the right one.

Both companies could send the exact same investor update.

Growth rate on line one. ARR on line two. A clean logo count trending up.

A reader would have no way to tell which one is worth three times more per dollar of revenue. The number that actually explains the gap almost never makes it into the update at all.

That’s not a reporting gap. It’s a design gap.

Most founder dashboards get built once, in the seed deck, then patched with whatever’s easiest to pull out of Stripe: total users, total revenue, signups this month. Those numbers describe activity. They were never built to answer the one question every investor in the room is actually asking.

Can this business grow without you, or does it need constant new fuel just to hold its shape?

I’ve read this exact panel for a living for two decades. Chief Commercial Officer at MessageLabs before its $700M sale to Symantec, then a co-founder of Notion Capital, backing over 500 B2B founders since.

What follows is the dashboard we run with founders before every raise and every board update. What it measures, why it’s built the way it is, and how to run it in three steps. The full working template is at the end.

What Is the SaaS Metrics Dashboard?

A linked Excel workbook that turns raw ARR, customer, and spend data into eight scored panels: Net Revenue Retention, Gross Revenue Retention, Burn Multiple, Rule of 40, CAC Payback, Pipeline Coverage Ratio, Gross Margin, and a Cohort Retention curve.

Every panel comes with a Strong, Moderate, or Weak band, sourced from current SaaS benchmark data, not an editorial guess.

Two things separate it from the wall-of-charts dashboard most founders already have.

First, it’s scored, not just charted.

A chart of MRR over time tells you what happened. It doesn’t tell you whether what happened is good.

This dashboard tells you where your 88% GRR or your 1.3x burn multiple actually sits against the current market, without a second spreadsheet open to check.

Second, it’s built to be read in pairs, not in isolation.

None of these eight numbers means much alone.

NRR next to GRR tells you whether retention is real or propped up by upsells. Burn Multiple next to Rule of 40 tells you whether efficient-looking burn is actually efficient, or just what’s left after growth stalled.

A dashboard that shows one half of each pair lets a founder choose which story to tell. A dashboard that shows both leaves nowhere to hide the gap. That’s exactly how investors already read these numbers, whether or not the founder built the dashboard that way.

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Why This Dashboard Matters

Here’s a scenario that plays out more often than founders expect.

A company walks into a partner meeting with NRR at 106%. Clean, above the 100% bar, a number worth leading with.

Twenty minutes in, a partner asks what Gross Revenue Retention looks like on the same base. It’s 79%.

NRR was propping up a 27-point hole with expansion revenue from the handful of accounts that hadn’t already churned. The founder wasn’t lying. They just never put the two numbers on the same page and found the gap themselves, before someone else found it for them in the room.

Or take the burn side.

A team reports a Burn Multiple of 1.1x, comfortably inside the Strong band, a genuinely good number on its own. Run alongside it, Rule of 40 has fallen from 38% to 22% over four quarters.

The burn multiple isn’t efficient. It’s what a good-looking burn multiple looks like when a company has nearly stopped spending and nearly stopped growing at the same time. Read alone, 1.1x is a green flag. Read next to Rule of 40, it’s a stall wearing a good number.

Both are read-in-pairs problems. Both are exactly what a dashboard built from disconnected exports will always miss.

When your NRR lives in a Notion doc, your burn number lives in a founder’s head, and your pipeline coverage lives in whatever your VP of Sales said on the last call, nobody ever puts two of them side by side long enough to notice the gap.

The founder note built into this workbook says it plainly: investors rarely reject a company because one metric is imperfect. They hesitate when the metric is weak, the direction is unclear, and the founder can’t explain the mechanism behind it.

Keeping every panel on one page, scored against the same current benchmarks, updated from the same Inputs tab every quarter, is what makes the pairing happen automatically instead of by accident.

The gap surfaces before an investor finds it for you.

The Eight Panels, and What Each One Actually Tells You

Here’s what’s actually on it, using the sample data built into the template so you can see it working before you touch a single cell.

Net Revenue Retention. Can existing customers compound revenue on their own, without a single new logo?

Anything at or above 105% tells an investor your product sells itself into your own base. In the sample data, NRR moves from 102.5% to 104.3% across eight quarters. Real progress, landing in the Moderate band rather than Strong.

Not a failure. A specific, answerable question for your next update: was the improvement expansion revenue, or just less churn?

Gross Revenue Retention. NRR’s stricter sibling. It strips out upsell entirely and asks how much revenue survives with zero expansion.

A 2025 benchmark survey puts the median around 88%, with anything below 85% usually signalling a product market fit or customer success problem.

In the sample, GRR climbs from 96.0% to 97.5%. Comfortably Strong, and it’s the number that makes the NRR story credible rather than lucky.

Burn Multiple. Decides whether your growth is efficient or expensive. Simply, how much cash you burned for every net new dollar of ARR.

The framework popularized by SaaS operator David Sacks treats anything under 2.0x as defensible, with top quartile companies running 1.0 to 1.2x.

In the sample, Burn Multiple falls from 1.2x to 0.33x over eight quarters. The single biggest swing on the page, and exactly the kind of trend line that gets an investor to stop reading your update and start drafting a follow-up question of their own.

CAC Payback. How many months it takes acquisition spend to come back.

Median sits at 16 to 18 months; investors push for under 12. The sample improves from 19.9 to 15.7 months. Real movement, still short of Strong.

Rule of 40. Does growth rate plus profit margin clear the bar, or is one quietly propping up the other?

The sample crosses from n/a (too early to score) to a Strong 50.6% once four quarters of comparable data exist. That’s itself the point: this panel isn’t meaningful until you have the history behind it, and the workbook is built to say so rather than show you a number that isn’t ready.

Pipeline Coverage Ratio. Is next quarter’s target backed by real, weighted pipeline, or by hope?

The sample runs from 3.5x to 4.0x against a 3.5x Strong threshold, sourced from standard B2B sales-ops benchmarking.

Gross Margin. Does the business still run on software economics, or have services crept in and diluted it?

The sample climbs from 78.0% to 81.0%, against a market median of 80%.

Cohort Retention. The one panel that isn’t a single number. It’s a curve.

A cohort-by-cohort grid tracks whether each vintage of customer becomes more valuable as it ages, or quietly leaks ARR the whole way through, something a single blended NRR figure can hide completely.

In the sample, the Q1’24 cohort climbs from 100% at signing to 114% by age five. That’s a company getting paid, in the literal sense, for keeping a customer alive rather than for closing them in the first place.

What’s Inside the Workbook

Six tabs. Each one does a single job.

Start Here. The color legend: blue text you fill in every quarter, black text that recalculates on its own, yellow fill marking the exact cells to overwrite. Plus a four-step checklist for your first pass through the workbook.

Why it matters: the fastest way to break a linked workbook is typing over a formula by accident. This tab keeps you inside the cells that are actually meant to be touched.

Inputs. The only tab you open every quarter. Your ARR bridge (beginning ARR, new ARR, expansion, contraction, churn, ending ARR), customer counts, revenue and COGS, sales and marketing spend, net cash burn, and pipeline versus target. Eight quarters, ready to extend.

Why it matters: every panel on the Dashboard tab pulls straight from these rows. Get the ARR bridge right once, and NRR, GRR, Burn Multiple, and Rule of 40 all compute correctly without you touching another cell.

Dashboard. All seven scoreable panels, side by side, pulling live from Inputs, each with a color-coded status and a QoQ delta.

Why it matters: this is the page you screenshot into a board deck. Update Inputs, and every panel and every status color update themselves. No manual recalculating before a meeting.

Cohort Retention. Panel eight, on its own tab, because it isn’t a single number. A triangular grid tracks each acquisition cohort’s ARR retention by quarter-age, with an average row showing whether the product gets stickier or leakier as customers age.

Why it matters: a blended NRR figure can hide old cohorts compounding nicely while every new cohort churns faster than the last. This is the only panel built to catch that specific failure.

Benchmarks. Every Strong, Moderate, and Weak threshold on the Dashboard tab, sourced.

Why it matters: a benchmark you can’t source is an opinion with better formatting. Check where every band came from and cite it yourself in your next update.

Claude Prompt. A paste-ready prompt that takes a raw Stripe or billing CSV, reconciles your ARR bridge, flags anomalies, and asks you directly for the four numbers that don’t live in a billing export (sales and marketing spend, cash burn, pipeline, bookings target) instead of guessing at them.

Why it matters: most founders don’t have forty minutes a quarter to hand-build an ARR bridge from a CSV. A prompt that estimates those four numbers instead of asking produces a dashboard that looks complete and is quietly wrong on half its panels.

How to Use It (3-Step Workflow)

Step 1: Drop your numbers. Open Inputs and replace the sample data with your own ARR bridge, customer counts, revenue, spend, and pipeline, one quarter at a time.

Cause and effect: move Churned ARR from $25K to $45K in a single quarter, and NRR drops from 105% to 97%, flipping from Strong to Weak on the Dashboard tab instantly. The same change a partner would clock in about four seconds in a board meeting.

Step 2: Read the panels in pairs. Check the Status column first. Anything Yellow or Red is worth a sentence in your next update, before an investor asks. Then check the trend, since one quarter’s Strong score matters less than whether the line has been climbing or sliding for the last four.

Cause and effect: a Burn Multiple that reads Strong at 1.1x this quarter, next to a Rule of 40 that’s fallen from 38% to 22% over four quarters, tells you the efficiency is coming from spending less, not spending better. That’s a different conversation with your board than “burn is under control.”

Step 3: Decide, then share. Use the panels to decide what actually needs to change: whether a hiring plan survives the burn multiple it implies, whether a price change is worth the CAC payback hit, whether pipeline coverage supports the number you’re about to promise a board. Export the Dashboard tab straight into the update.

Cause and effect: Pipeline Coverage sitting at 2.3x against a 3.5x target tells you, three months out, that hitting next quarter’s number needs either more pipeline or a lower target. A decision that’s far cheaper to make now than the week the quarter actually misses.

Who Should Use It, and When

Founders, prepping for a raise. Due diligence isn’t the moment to discover your own GRR for the first time. Walk in with all eight panels current and internally consistent, and the numbers survive the question behind the question, which is never “what’s your NRR” but “does that agree with everything else on the page.”

Fractional CFOs and finance leads. You’re the one who has to make eight disconnected numbers agree before they reach a founder’s desk. This keeps the ARR bridge and every downstream metric tied to one Inputs tab, so nothing quietly drifts out of sync between the deck and the model behind it.

Investors and board members. The real question is never “what’s the number.” It’s “does this number agree with the one next to it.” A founder who hands you all eight panels, sourced, has already done the work of checking their own story before asking you to believe it.

Portfolio operators. Same six tabs, same sourced bands, across every company you touch. That’s the only way “how’s the portfolio doing” gets answered in minutes instead of a week of chasing spreadsheets.

If You’re Prepping an Update Right Now, Don’t Stop Here

This dashboard tells you what to say. These tell you how the room on the other side of it actually thinks:

• The Number That Kills More Fundraises Than Any Bad Idea: one slide, one metric, quietly killing raises before founders even notice.

• The Quiet Filter That Decides Your Entire Fundraise: every investor runs this before you open your mouth.

• The Way VCs Actually Calculate Your Valuation: they have a number in their head before you walk in.

• How Investors Decide If You’re Ready to Raise: it’s not timing, it’s not luck, it’s a checklist.

Read those alongside this dashboard and you’re not just sending better numbers. You’re sending them to a reader you actually understand.

Get the Full Workbook

We don’t gate write-ups of numbers you could Google.

We gate the operator-grade tools. The ones that save you a weekend of spreadsheet wiring and make your next investor update look like it came from a CFO, not a founder guessing at what “good” means.

Everything above lives in one workbook, ready to download:

• All 8 panels: NRR, GRR, Burn Multiple, Rule of 40, CAC Payback, Pipeline Coverage Ratio, Gross Margin, and the Cohort Retention curve, each with an investor-lens question and a QoQ delta

• The sourced Benchmarks tab, so every band is checkable, not asserted

• Eight quarters of working sample data, so every formula and chart runs correctly before you touch a single cell

• The paste-ready Claude prompt, ready to turn a raw billing export into a completed Inputs tab in one pass

• Excel and Google Sheets compatible, yours to keep and refill every quarter

• Every past and future proprietary template, model, and swipe file we publish, plus early access to new frameworks before they go out to the free list

If you’ve got an investor update due this quarter, this is the issue to upgrade on. One dashboard that makes your numbers legible is worth more than a year of Premium if it buys you one fewer awkward follow-up call.

Paid subscribers also get:

✓ 60+ additional tools covering every other stage of fundraising and running a company: pitch deck screening, investor research agents, due diligence, term sheet analysis, and data room management.

Start your 7-day free trial → Cancel anytime.

👉 Download the Full 8-Panel SaaS Investor Dashboard

No guessing at thresholds. No rebuilding your ARR bridge every quarter by hand. Just the scorecard investors are already keeping in their heads. Now it’s yours too.

Read more

You don’t have a Claude problem. You have a chatbot problem.

You open a tab. You ask it to write a follow-up. You copy the answer into your outreach tool. Tomorrow, you do it again. Next week, you’ve forgotten which opener you tried on which investor, so you ask Claude to write another one, from scratch, with no memory of what already worked.

That’s not an AI workflow. That’s data entry with better sentences.

The founders getting through this market faster aren’t the ones with a better prompt. They’re the ones who stopped treating Claude like a vending machine you visit once and started treating it like a coworker that holds context, runs a loop, and only stops to ask you when it actually matters.

This is the full system. Nine prompts. Memory, sourcing, outreach, replies, follow-up, performance review, deliverability, guardrails, investor updates, and the maintenance pass that keeps it all from going stale. Run in order, in one pinned conversation, they turn Claude from something you visit into something that runs alongside you.

The math nobody runs before they build this 📊

Cold outreach to investors is a volume-and-precision game, and most founders are optimizing neither. Baseline cold investor email reply rates sit around 1% to 5%, which is brutal on its own. But that number moves hard depending on execution: an analysis of over 1,200 cold investor emails found personalized messages reply at roughly 5x the rate of generic ones, and emails referencing specific traction numbers reply at nearly 2.8x the baseline.

Stack two or three of those levers and you’re in a completely different game. The problem is doing that consistently, for every single investor, every single week, without it eating your whole calendar.

The median time between funding rounds has also stretched from roughly 451 days in 2021 to about 744 days by Q4 2024. Your raise is very likely going to take longer than the last one did, whether you’re ready for that or not. The founders who handle that stretch well aren’t the ones grinding harder in month four. They’re the ones who built something in month one that’s still running in month four without them.

That’s the entire case for an agent instead of a chatbot. Not novelty. Arithmetic.

Why the “open Claude, ask a question” workflow quietly fails

A chatbot has no memory between tabs. Ask it to write ten cold emails today and ten more next week, and it has no idea which of last week’s ten got a reply, which subject line worked, or which investor you already have a call booked with. You become the memory. You become the loop. You become the thing that has to remember to open the tab in the first place.

An agent is the same model, Claude, doing the same reasoning, but wired to three things a chatbot never has: a memory it updates itself, a set of actions it’s actually allowed to take, and a cadence that runs without you remembering to press go.

None of that requires new software. It requires a different first prompt, and a system that builds on it.

Want to get in front of 250k+ founders and investors?

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Is your raise already running itself? Five questions to find out

1. If you closed your laptop for a week, would your outreach still be moving? If the honest answer is no, you don’t have a system. You have a to-do list with better vocabulary.

2. Do you know, right now, without checking, which subject line is outperforming the others this month? Most founders couldn’t answer this in five seconds. The ones closing fastest usually can.

3. When an investor goes quiet for five days, does something follow up automatically, or does it depend on you remembering? Silence is the default outcome of fundraising. What happens next shouldn’t depend on your memory.

4. Could you hand your outreach log to a co-founder today and have them pick up exactly where you left off? If it’s all in your head and half-finished drafts, you don’t have a log. You have a bottleneck with one point of failure: you.

5. Are you writing a new email from scratch every time, or is something getting sharper the more replies come in? A system that learns from outcomes gets better every week. A blank tab doesn’t.

🟦 Prompt 1: The raise memory setup

Run this first. Once. In a fresh conversation, ideally a Claude Project you keep pinned rather than a chat you close after one email.

This is the only prompt in the system that isn’t a task. It’s the frame that makes every other prompt below actually function as an agent instead of a one-off request. Without it, Claude answers each prompt in isolation. With it, Claude holds your company facts, your target list, and your outreach history across every session, and updates that memory itself as you feed it outcomes.

Be specific in what you paste in. The more precise your starting facts, the less Claude has to guess later.

You are going to act as the operating system for my fundraise, not a
one-off assistant. Every prompt I run after this one assumes you're
holding the following context and updating it as I give you new
information.

Set up and maintain these four sections:

1. COMPANY FACTS: name, one-sentence description, stage, sector,
   traction (revenue, users, growth rate), amount raising, use of funds
2. TARGET PROFILE: the specific investor type I should be contacting
   (stage, check size, sector focus, geography)
3. OUTREACH LOG: every investor I've contacted, with date, channel,
   and status (no reply / opened / replied / meeting booked / passed)
4. WHAT'S WORKING: which subject lines, opening angles, or channels
   have actually gotten replies, updated as I report real outcomes

Here's my starting information:
[COMPANY NAME · ONE-SENTENCE DESCRIPTION · STAGE · TRACTION · AMOUNT
RAISING · TARGET INVESTOR PROFILE]

Confirm you're holding this as ongoing context. From now on, whenever
I say "log this" or "here's what happened," update the relevant
section and show me the current state before doing anything else.
Do not draft or send anything until I explicitly ask in a later prompt.

💡 Why this works: the single line that turns this from a chatbot into an agent is “update the relevant section and show me the current state.” That’s the memory. Everything below assumes it’s running.

If this is useful, this is one piece of a bigger system we’ve been building all year. Worth reading alongside this one:

• How to Build Your Fundraising Narrative with Claude: the five-prompt playbook for turning your raw story into the argument that gets you a term sheet before you ever need an agent to manage the replies

• I Asked Claude to Reject My Pitch Until It Couldn’t. Then I Raised.: the adversarial system that finds the weak points in your pitch before an investor does

• The Claude Prompt That Turns a Cold Email Into One a VC Actually Reads: the five-prompt system behind the exact kind of personalized outreach this agent drafts every week

• The 6 Claude Prompts That Change How Investors See You: the positioning layer that makes sure what the agent is sending is actually the right story

• The Claude Due Diligence Playbook That Gets You to Closing: what happens after the agent gets you the meeting, and the term sheet lands

• The Claude Prompt That Found My Real ARR. Then I Raised.: make sure the traction number this agent is putting in every outreach draft is one you can actually defend

🟦 Prompt 2: The weekly sourcing and outreach draft

This is the loop. Run it once a week, in the same conversation as Prompt 1, and it does the two things that eat the most founder hours: finding who to contact, and writing to them like you actually know who they are.

Using the context you're holding on my raise, propose 10 investors
this week who match my target profile and haven't already appeared
in my outreach log.

For each one:
- Name, fund, and the specific reason they fit (their stated thesis
  or a real portfolio overlap, not "early-stage generalist")
- A cold outreach draft under 100 words, personalized to their actual
  thesis or a named portfolio company, referencing one specific
  traction number from my company facts
- A one-line note on the best channel: direct email, a warm path if
  one plausibly exists through my network, or LinkedIn

Then, for anyone in my outreach log marked "no reply" for 5 or more
days, draft a short follow-up that references the original email
without re-explaining the whole pitch.

Show me everything as drafts only. Tell me which ones you'd prioritize
sending first and why. I will tell you which to log as sent, and you
update the outreach log accordingly.

⚡ The personalization and traction-number instructions aren’t decoration. They’re the two levers with the biggest measured effect on reply rate. Bake them into the prompt so you get them every single week without having to remember to ask.

📋 The full system: what the rest of this build covers

Prompts 1 and 2 give the agent memory and a weekly sourcing-and-drafting habit. That’s real, usable value on its own. But it isn’t the full autopilot yet, that’s what happens once replies start landing and you need something managing the inbox, the timing, and the guardrails without you babysitting every step. Here’s the rest of what’s built out below:

✓ Prompt 3: The reply triage and routing. Classifies every reply into genuine interest / needs more info / soft pass / hard pass / automated, and drafts the exact next message for each category, so a full inbox never turns into an afternoon of deciding what to do.

✓ Prompt 4: The follow-up cadence. The specific three-touch sequence and timing that consistently outperforms a single follow-up, built to run directly off your outreach log’s “no reply” status.

✓ Prompt 5: The weekly performance review. Compares this week’s subject lines and opening angles against last week’s, and tells you plainly which to keep using and which to kill.

✓ Prompt 6: The deliverability guardrail. The volume, pacing, and pattern rules that keep a real outreach cadence from tripping spam filters and burning your sending domain’s reputation.

✓ Prompt 7: The “loop me back in” escalation rule. Defines, in writing, exactly which actions the agent proposes and which it’s never allowed to take without your explicit yes, so it stays a teammate and never becomes a liability.

✓ Prompt 8: The investor update draft. Turns your outreach log and company facts into the monthly update you send to investors who are already committed, without rebuilding it from scratch every time.

✓ Prompt 9: The memory prune and handoff. Keeps the memory file accurate as your stage, numbers, or targeting shift mid-raise, so the agent isn’t still pitching last quarter’s traction in month three, and lets you hand the whole thing to a co-founder in one page.

Paid subscribers also get:

✓ 60+ additional tools covering every other stage of fundraising and running a company: pitch deck screening, investor research agents, due diligence, term sheet analysis, and data room management. The same tool stack this agent slots into.

Start your 7-day free trial → Cancel anytime.

🟦 Prompt 3: The reply triage and routing

This is the moment most founders lose the thread. Ten cold emails go out, three replies land in the same afternoon, and each one needs a different response, sent fast, while you’re also supposed to be running the actual company.

A reply that says “send me the deck” and a reply that says “not right now, keep me posted” both look like small wins in an inbox. They need completely different responses, sent within the hour, not whenever you next have a spare ten minutes.

Read more

Let’s get into it.

First, something free 👇

The founders winning in 2026 are everywhere: LinkedIn, newsletters, podcasts, investor DMs. They run on a system that publishes for them, rather than carving out time they rarely have.

We built that system into a free AI Creator Kit: one Notion workspace with AI agents, templates, a creator CRM, and partner credits worth thousands.

Grab it here, no paywall:

Free AI Creator Kit

In-Depth Insights 🔍

• The State of Intelligent Finance 📊
  More consumers now rely on AI for budgeting and planning, making intelligent financial guidance an expected feature rather than a bonus. Confidence grows when companies explain how decisions are made, keep humans involved, and stand behind mistakes with clear protections. [PLAID]

  

• The Seven Deadly Sins of AI Spend 😈
  Runaway budgets usually come from poor oversight, expensive defaults, and duplicated work instead of model pricing alone. Teams that define ownership, track usage early, and measure outcomes avoid costly spending freezes later.

  

• The Pitch Deck Playbook ⏱️
  Investors form opinions quickly, making clear structure and logical slide progression just as important as strong metrics. A concise positioning statement, meaningful traction chart, and founder credibility establish the strongest early signal. []

• How to Use Claude Fable 5 Efficiently 🧵
  Reserve the premium model for planning and validation while assigning execution to lower cost models to control token spend. Automation loops, reusable skills, and visual reasoning improve long running workflows, but data retention policies deserve careful review.

  

• AI Made Bug Bounties a Six Figure Skill 🐛🔓
  Researchers are earning substantial payouts by reviewing AI systems before attackers uncover critical weaknesses. Growing demand for securing agents and APIs creates opportunities that extend beyond bug bounties into consulting work.

  

• The Investor Outreach System 🎯
  Automation preserves personalization at scale by enriching contacts, timing outreach well, and organizing replies for faster follow up. Human review remains part of the process while structured workflows improve response rates and meeting volume.

  

• Founder Mistakes That Kill Early Sales 📉
  Many startups struggle because founders delay selling, chase weak opportunities, and confuse interest with buying authority. Value based pricing and a consistently active pipeline create stronger momentum than waiting for a perfect product.

  

• Autonomous Revenue Agents in Action 🤖
  Companies are deploying autonomous agents across prospecting, sales, and customer expansion workflows. The focus is shifting toward combining reliable rules with adaptive decision making in production.. [HSE]

• If You Don't Take the Wheel🚗
  Boards rarely replace founders who consistently make clear decisions and earn organizational trust. Leadership comes from hiring deliberately, staying focused on product direction, and allocating capital with discipline.[]

Social Media Gems 💎

• Selling Work, Not Software 🏗️
  Sequoia argues the biggest AI companies will sell completed work instead of adding assistants to existing software. Services represent a far larger market than SaaS, creating room for firms built around AI-first execution rather than software licenses.

  

• Altman Calls Out VC Support Gap 🤐
  Sam Altman says very few investors consistently help founders beyond writing checks, with Josh Kushner standing out. His view reframes capital as the starting point, while sustained involvement is what founders value most.

• Altman on Spotting $10B Founders 🔍
  Altman points to obsession, focus, frugality, and genuine conviction as the patterns behind exceptional founders. Strong communication, rapid execution, continuous improvement, and original thinking matter more than chasing quick outcomes.

  

• Unicorn Founders Are Getting Older🦄
  Founders of unicorn companies are now older on average, breaking from decades when they closely matched the broader startup population. The data suggests experience is becoming a stronger advantage as building category-defining companies grows more complex.

Trending News ⚡

• Nvidia Eyes Massive Financing for OpenAI Infrastructure 💰
  Nvidia is discussing guarantees worth up to $250 billion for OpenAI’s Ohio data center leasing plans. Separate talks could support another $350 billion in chip purchases as compute spending continues to scale. [Reuters]

• Amodei Clarifies Anthropic’s Position on Open Models 🔓
  Dario Amodei said open weight models without dangerous capabilities benefit the broader ecosystem. He argued policy should target chip exports and large scale model copying instead of restricting open releases. [Business Insider]

  

• Claude Code Creator Says Better Prompts Need Less Control 🗣️
  Boris Cherny says most users over specify tasks because they underestimate current model capabilities. Clear objectives, constraints, and success criteria produce stronger results than step by step instructions. [Business Insider]

  

• Tesla Prioritizes Energy Supply for Compute Growth ☀️🔋⚡🤖
  Tesla secured nearly 600 MW of solar power through long term utility scale agreements. The deals reflect growing pressure to secure electricity as computing infrastructure becomes more power intensive. [Business Insider]

  

• Nadella Urges Enterprises to Stay Model Agnostic 🔄
  Microsoft says production systems should be designed so models can be replaced without major disruption. The strategy reduces dependency on any single provider as the model landscape changes rapidly. [TechCrunch]

  

• Zuckerberg Expects Personal AI Agents to Go Mainstream 👥
  Meta believes billions of people will rely on personal agents across daily tasks within five years. The company continues increasing infrastructure spending despite near term pressure on free cash flow. [TechCrunch]

  

• Anthropic Reveals Unexpected Live System Access During Testing 🔓
  Internal reviews found three cases where models reached real company systems during evaluation. The issue stemmed from internet access being available despite tests being intended as offline simulations. [Business Insider]

• Jassy Says Model Choice Matters More Than Model Ownership ☁️
  Andy Jassy said AWS can win by giving customers access to multiple leading models instead of relying on one in house system. Amazon’s strategy pairs Bedrock’s model marketplace with continued investment in its own AI models as AWS growth accelerates. [Business Insider]

  

• DoorDash CEO Says Coding Is Only Part of the Job 👨‍💻
  Tony Xu said AI can speed up programming, but engineering productivity depends on improving collaboration and decision making too. Despite AI generating much of DoorDash’s code, the company has not changed how its teams are organized or operate. [Business Insider]

New Funds 💰

• Framework Ventures closed its fourth $400M venture capital fund to back companies across crypto, AI, robotics, space, and clean energy.

• Jump Capital raised $350M for its eighth venture capital fund to invest in early-stage companies across AI applications, cybersecurity, and AI infrastructure.

• Align Ventures closed its second $125M venture capital fund to back early-stage consumer brands across beauty, health, wellness, pet, home, and personal care.

• Italian Founders Fund closed its second fund at over €100M to invest in Italian-founded startups from pre-seed through Series A.

• Psalion launched its third $50M venture capital fund to invest in pre-seed and seed blockchain startups across infrastructure, RWA, stablecoins, DeFi, and Web3.

That’s a wrap for this week.

If you want to stay ahead of the curve, make sure you're subscribed. No fluff, just real startup insights delivered straight to your inbox.

See you next time 🚀

This series is a preview of a new book I’ve written with my partners Richard Blundell and Paul Watson — The Selling Software Algorithm: The Go-to-Market Navigation System for B2B Software Leaders.

It isn’t a strategy deck dressed up as a book. Between the three of us we’ve spent close to seven decades inside B2B software as founders, operators, investors and coaches — building companies, exiting some, and quietly breaking a few along the way, which is where most of the real learning lives. Through our work at Vencha we’ve now supported hundreds of founders trying to do the single hardest thing in software: turn a clever product into predictable commercial traction in a market that’s noisy, cautious, and more crowded than it has ever been.

One pattern shows up again and again. Companies rarely struggle because the product is bad. They struggle because they have no navigation system for going to market. This book is that system.

Get My Copy

Last time we found the person who holds the pen — the Economic Buyer, understood not as a job title but as a human being making a personal bet.

But here’s the thing nobody tells you. You can have exactly the right person in the room and still lose.

Because that person doesn’t decide in isolation. They decide inside a company — one with its own history, its own competing priorities, its own internal logic about what gets funded and what quietly dies in committee. Put the perfect buyer inside the wrong company and the deal stalls anyway: the culture resists change, procurement grinds, the problem you solve just isn’t visible enough to the people who control the budget.

So the second part of the algorithm asks you to lift your gaze from the person to the organisation.

And it starts by retiring a word most founders love: ideal.

Table of Contents

1. Aim for the Middle of the Bullseye

2. Why “Ideal” Is Too Forgiving

3. The Clone List

4. The Four Dimensions of Perfect Customer DNA

5. The Paragraph That Ties It Together

6. The Question That Sharpens Everything: What Must Be True?

7. From Profile to Market Map

Aim for the Middle of the Bullseye

Picture a dartboard.

Your ideal customers sit somewhere in the inner rings — good, respectable scoring territory between the treble and the centre. They’re worth having. But this exercise isn’t about the inner rings.

It’s about the absolute centre of the bullseye. The middle of the middle. The tiny zone where everything you do lands with maximum effect and minimum resistance.

Most founders never aim there, because aiming there means accepting how small it is. It feels like leaving the rest of the board on the table. But the centre is precisely where your value stops being plausible and starts being inevitable — and inevitability is the only thing that builds a repeatable go-to-market motion.

The whole of this chapter is about navigating, deliberately, to that centre.

Why “Ideal” Is Too Forgiving

You’ll know the term Ideal Customer Profile. It’s a useful starting point, and there’s nothing wrong with it as a first pass. Most ICPs describe a target in broad strokes — sector, size, a use case, maybe a couple of technology assumptions. They live as a tidy slide and act as a loose compass for sales and marketing.

The problem is that “ideal” is too forgiving.

It describes the kinds of companies that could buy — which is comforting, and comfort is exactly the issue. It never forces the team to confront the difference between where value is genuinely inevitable and where it’s merely possible.

So when we work with founders, we push past ideal and insist on perfect. Not because perfection exists in some romantic sense, but because the word forces a harder scale of thinking. Perfect asks the questions ideal lets you dodge: Where does the pain actually concentrate? Where does adoption happen smoothly? Where do we become an invaluable painkiller rather than a nice-to-have vitamin?

That one-word upgrade — ideal to perfect — is the cheapest, highest-leverage change most software companies never make.

The Clone List

Here’s where it gets concrete, and the mantra is: start simply.

Sit down with your team and pick three customers you would happily clone.

Not the biggest logo, chosen for vanity. Not the most prestigious brand, if the sale and the implementation were actually painful. Choose the ones where the fit felt almost unfair — where the sales cycle was clean, implementation was straightforward, value arrived early, the product got used properly, and the renewal happened without a negotiation. Somewhere in your customer base, if you have any real traction at all, a small handful of these exist. And the thought that always follows is the same: if we could find twenty more like them, we could build something properly scalable.

That instinct is correct. The discipline is turning it into a definition the whole organisation can pursue without debate.

So reflect on those three with real honesty. Their sector, size, internal dynamics, leadership culture. How the sale actually unfolded. What messaging landed. How long procurement took, how many stakeholders were involved, how fast they moved from curiosity to commitment. Who leaned in during onboarding, and who resisted. How they talk about you today.

Capture the attributes they share. Your first list will be messy, and that’s completely fine — the goal isn’t polish, it’s to surface signals you can later refine into non-negotiables. And you’ll quickly notice something important: what makes a customer “perfect” is rarely just demographic. It’s a blend of structural constraints, cultural posture, and behavioural readiness.

Which brings us to the DNA.

The Four Dimensions of Perfect Customer DNA

Set aside two focused hours with senior people from Sales, Marketing, Product, Tech and Customer Success. Laptops closed, phones away, pens out. If the room can agree on a Perfect Customer DNA, you’ll save yourselves months of wasted effort later.

Perfect Customers have a recognisable DNA, and it shows up consistently across four dimensions. Each one is useful alone. The real magic happens when you force them to intersect.

Demographic — the structural conditions for value. The visible shape of the organisation: size, headcount, revenue band, funding stage, business model, vertical. These aren’t administrative details, they’re constraints that shape urgency, budget ownership and procurement behaviour. Selling to a fifty-person agency is a fundamentally different sport from selling to a five-thousand-person enterprise, even when the surface problem looks identical. Demographic clarity forces an uncomfortable truth: not every company that could use your software should buy it today. Some are too small to feel the pain acutely; some so large the pain is diluted across layers of management. Ask: at what size, in which industries, and at what stage does urgency replace mere experimentation?

Geographic — where learning and momentum are fastest. This one gets underestimated constantly, usually by ambitious teams eager to prove global relevance. But in the early years, proximity determines your learning speed, relationship depth and service quality. A concentrated region within realistic travel distance lets you meet customers face to face, watch them use the product in context, and build trust the only way it gets built early — through immediate presence and responsiveness. Selling across time zones before you have a repeatable engine just introduces hidden costs: slower feedback loops, fragmented support, quiet dilution of focus. Geographic fit isn’t about limitation. It’s about sequencing. You earn the right to expand once you’ve proven repeatability somewhere you can serve exceptionally well.

Psychographic — what the organisation actually believes. This moves past what a company is and into what it values. Some businesses are wired for innovation and speed; they reward experimentation and tolerate imperfection. Others prize control, predictability and compliance, where stability is success and change is managed cautiously if at all. If your solution meaningfully supports a declared organisational value — security, sustainability, resilience, inclusion — that value isn’t incidental. It belongs in your DNA, because it determines whether your message feels aligned or alien. When belief, behaviour and benefit point the same way, you stop selling uphill, and the decision starts to feel consistent with who the organisation believes itself to be.

Behavioural — signals of readiness and momentum. If psychographics tell you what a company believes, behaviour tells you whether it’s ready to act right now — and intent is far more valuable than abstract interest. The strongest signals appear at moments of change, because organisations rarely adopt new software when everything is calm. They move when something has shifted: a newly appointed COO or Head of Risk arriving with a mandate, a funding round or merger exposing gaps in existing processes, a public commitment to an AI or transformation programme. Behaviour also shows up in adoption patterns — early experimenters create fast learning and referenceability; late waiters create long cycles and internal resistance. These cues are the breadcrumbs that lead you to real fit before your competitors even arrive.

Individually, each lens is insight. Forced to intersect, they produce a picture precise enough to act on.

The Paragraph That Ties It Together

Once the four dimensions are on the wall, synthesise them into a single paragraph that feels concrete, human and commercially grounded. Something like this:

Our Perfect Customer is a mid-market healthcare services organisation, employing between 1,000 and 3,000 people and generating £250m to £750m in annual revenue, operating across multiple sites in the UK or Northern Europe. They’re led by an Economic Buyer tasked with improving efficiency, compliance and reporting without adding headcount, who wants to be seen internally as the person who modernised how the business runs. They value innovation but operate in a regulated environment, so trust, reliability and defensibility matter deeply. They’re actively exploring automation and AI, feel mounting pressure from fragmented data and manual processes, and are motivated to act because the current state is creating frustration, risk and repeated leadership scrutiny.

Read that back. There’s a real company in it. You could walk into a room and recognise them. That’s the bar — evidence-led, specific enough to be a forcing function, not a tidy slide that comforts everyone and commits no one.

The Question That Sharpens Everything: What Must Be True?

There’s one question that sharpens this entire process more than any other:

What MUST be true about a customer for your software to deliver maximum value?

Ask it slowly, and insist on specifics. Not “it would help if…” Not “ideally they…” Must.

In every successful software business we’ve worked with, there’s at least one non-negotiable condition that makes the product genuinely click. Maybe they must operate in a regulated environment where reporting accuracy is career-critical. Maybe they must already run a specific platform you integrate with cleanly. Maybe leadership must treat security or ESG as a board-level concern that attracts real budget, not a slogan. Maybe the buyer must be under an explicit mandate to fix this this year, not “at some point.”

These conditions become your final qualification lens. They protect you from chasing customers who might buy but will never become delighted — and delighted customers are the only ones who compound. Refine it until you can state the non-negotiable in one clean sentence: “We deliver maximum value when a company is heavily regulated, managing risk in silos, and under constant board-level scrutiny to prove compliance.”

When you can say it that plainly, you’ve found the cherry on the cake. You now know exactly what has to be present for value to be inevitable.

From Profile to Market Map

Here’s where most teams stumble. They do the thinking, produce a beautiful profile — and then drift straight back into opportunistic selling, because they never translate the profile into a living list of real accounts.

Don’t be that team. Turn the DNA into a Market Map, in stages.

First, build a long list of roughly 500 organisations that fit the DNA well enough to be worth consideration. Then overlay the behavioural signals — the leadership changes, the funding events, the stated mandates — to drill down to around 100 Focus accounts, where fit is strongest and early momentum is most likely. That focused list, matched to the Economic Buyers inside each account, becomes the thing your Sales, Marketing and Product effort actually points at.

That’s the shift: from hopeful generalisation to a repeatable way of navigating directly to the customers where you win.

Because “ideal” describes who could buy. “Perfect” tells you where the value is inevitable. One is a comforting slide. The other is a map.

Next in the series, we reach the part of the algorithm that turns all this precision into urgency: the three visceral pains that make an Economic Buyer stop tolerating the status quo and finally decide that doing nothing is no longer an option.

-Chris Tottman

Most founders lose their raise before they ever send the first email.

The ones who close have something the rest don’t: they know exactly how investors read a pitch deck before you’re even in the room, which AI prompts are quietly transforming how founders prepare, how to turn a cold outreach into a warm conversation, what a two-minute briefing can do that a ten-slide deck can’t, how to stress-test your pitch before an investor ever sees it, and how to build a fundraising narrative that actually sticks.

That edge isn’t luck. It’s 30 years sitting across the table from founders, 500+ investments, and the patterns that quietly decide who gets funded and who gets ghosted — now distilled into a system you can use today.

We’ve packaged all of it into 60+ premium tools. One subscription.

Start your 7-day free trial → Cancel anytime.

Start with these six. They’ve already changed the outcome for thousands of founders before you — here’s what happens when it’s your turn:

Your Pitch Deck’s First Reader Isn’t Who You Think — Before any human sees it, something else decides its fate. Know what it is before you hit send.

The 6 Claude Prompts That Change How You Raise — Most founders use AI to write emails. The ones closing rounds use it like this instead.

The Claude Prompt That Turns a Cold Outreach Warm — One prompt. The difference between ignored and in the room.

The Two-Minute Investor Briefing — Investors don’t have time. This format respects that — and gets the meeting anyway.

I Asked Claude to Reject My Pitch — Here’s What It Found — The holes investors find but never tell you about. Find them first.

How to Build Your Fundraising Narrative — Not your deck. Not your numbers. The story that makes both of them land.

Every raise has two sides: the founders who get the meeting, and the ones who wonder why they didn’t. Upgrade now — and make sure you’re on the right one.

That’s the whole window. Three minutes, forty-four seconds, to go from stranger to term sheet.

Here’s what nobody tells first-time founders: the partner isn’t reading your deck fresh. They’re running it against a checklist built from the last 200 decks they’ve seen, most of which they’ve already forgotten. Your deck doesn’t need to be original. It needs to survive the checklist.

I spent a decade as an operator before I ever sat on the other side of that table: Chief Commercial Officer at a messaging security company called MessageLabs, which we grew to $200M+ in revenue before Symantec bought it for $700M. For the two decades since, I’ve been the one running the checklist, as a co-founder of Notion Capital and an investor in 500+ founders. I wrote that checklist down. It’s an 11-slide rubric. Below, three of the eleven are yours in full.

Why partners score, not read

A partner looking at five decks a day, every day, for years, doesn’t read your deck. They pattern-match it. Slide 1 gets compared to the last hundred slide 1’s. Slide 4 to the last hundred slide 4’s. That’s not cynicism. It’s the same shortcut a radiologist uses to spot the one wrong shadow on an X-ray in a glance instead of studying the whole image from scratch. Expertise is pattern recognition, bought with repetition.

The good news: patterns are learnable. You’re not trying to move a stranger emotionally. You’re trying to fit the pattern that gets filed under “yes.”

Why “make the deck prettier” is the wrong instinct

Founders who’ve raised before will tell you the same thing: the deck that closed the round was rarely the best-designed one. It was the one where every slide answered the question the previous slide raised, in the order a partner’s brain wants to receive it.

That’s the part design tools can’t fix. A rubric can.

The order is part of the score

The rubric isn’t eleven separate checks. It’s eleven checks that assume a specific order, because each slide answers the question the one before it just raised.

The one-liner raises “what do they do.” Problem raises “why does that matter.” Solution raises “how do they fix it.” By the time a partner reaches traction, they’re not asking “does this company have customers” in the abstract. They’re asking “does this trend make the promise on slide three believable.” Move a slide out of order and the partner arrives with the wrong question already loaded. A perfectly scored slide in the wrong slot still reads as off.

Two moves we see constantly: pulling competition up next to the problem slide because it feels like it belongs there early, and pushing the ask to the very last slide out of politeness. Both cost meetings.

Score each slide on its own merits. But check the sequence first: a 5 in the wrong slot reads like a 3.

The 11-slide rubric, slides 1 through 3

Each slide below gets scored the way we score it before a live pitch: the question a partner is actually asking, what a 5 looks like, what a 1 looks like, and the most common way founders fail it.

Slide 1: The one-liner

▫️ What the partner is really asking: “Do I understand what this company does in the time it takes to read one sentence?”

▫️ Score a 5: Names the customer, the product, and the value in under 12 words, with zero category jargon.

▫️ Score a 1: Any sentence that needs a second sentence to explain what the first one meant.

▫️ Weak → strong: “AI-powered logistics optimization platform for mid-market shippers” → “Flexport for last-mile delivery: 30% cheaper, no new trucks.”

⚡ Why this works: The weak version describes the category. The strong version names the comparison a partner already trusts, the customer, and the number that makes it real: all three, in one breath.

Slide 4: Traction

▫️ What the partner is really asking: “Is this a line or a point?” One data point is an anecdote. Three or more, moving one direction, is a trend a partner can underwrite.

▫️ Score a 5: A chart, not a table. Time on the x-axis. The metric that actually maps to the business model, revenue for a SaaS company, not “sign-ups.”

▫️ Score a 1: A chart that changes units halfway through: “users” for three quarters, then “revenue” for the last one, because the founder stitched together whichever number looked best each period.

▫️ Weak → strong: A bar chart labeled “Total Users” → a line chart labeled “MRR,” quarter over quarter, with the dollar figures printed on the line.

⚡ Why this works: DocSend’s data shows this slide gets the most scrutiny time on decks that get funded, and the most abandonment on decks that don’t. Partners aren’t reading the number. They’re checking whether it agrees with the slide three promise.

Slide 6: Team

▫️ What the partner is really asking: “Why are these specific people the ones who solve this specific problem?” Not “are they smart.” Why them, for this.

▫️ Score a 5: One line per founder tying a past decision directly to an unfair advantage on this exact problem.

▫️ Score a 1: A slide that reads like a LinkedIn export: titles and logos, no thread connecting them to the company.

▫️ Weak → strong: “Jane Doe, Co-Founder & CEO. Ex-Google, Stanford MBA.” → “Jane spent six years building fraud models at Google Pay. She’s the reason this company can underwrite risk nobody else can price.”

⚡ Why this works: The logos answer “were you competent somewhere else.” The rewrite answers “why you, here, now”: the question actually being scored.

🔒 The other eight slides, and the memo that finds where yours breaks

Three slides in, you’ve got the shape of how this rubric works. A raise runs you through all eleven, in order, each with its own failure pattern, and once the deck passes the slide-by-slide rubric, it still has to survive the pass where someone plays the partner and tries to kill the deal before an investor gets the chance to.

Here’s what’s behind the paywall, fully written and yours as a downloadable kit you keep and run on every version of the deck between now and your close:

✅ Slides 2, 3, 5, 7, 8, 9, 10, and 11 of the rubric (problem, solution, market sizing, business model, competition, financials, the ask, and the appendix), each scored the same way, with the specific tell that gets a deck quietly filed as “pass” before the founder even gets a rejection email.

✅ The market-sizing rebuild: the exact reframe that turns a sourceless “$40B TAM” slide into the bottom-up version a partner can’t discount on sight.

✅ The financials slide’s real job: why 68% of investors cite “unrealistic projections” as a reason for passing, and the one-line fix that stops a partner from doing that math against you in the first thirty seconds.

✅ The five-pass kill-the-deal memo: the review cycle we run on every deck before it goes to an investor: a narrative pass, a numbers pass, a market pass, a team pass, and a red-team pass that plays the most skeptical partner in the room. If your deck survives all five, it’s ready. If it doesn’t, you just found the leak before an investor did.

✅ The sequencing check: the one-page pass that tells you whether a slide is failing on its own merits or failing because it’s in the wrong slot, and exactly where to move it.

✅ The paste-ready Claude prompt that runs the entire eleven-slide rubric and all five memo passes against your actual deck outline in one sitting.

✅ The downloadable Deck Teardown Kit: every slide’s scoring criteria, the full memo template, the sequencing check, and the Claude prompt, formatted so you can run it on this raise and the next one.

Start your 7-day free trial → get the full rubric, the memo, and the kit. Cancel anytime.

Before you build another slide

Most founders treat the deck like the finish line: the thing you polish until it’s done, then send. It isn’t. It’s the artifact a checklist runs against before a human ever forms an opinion of their own.

I wish someone had handed me this rubric back when I was the one building the deck at midnight, guessing at what mattered. Built it now so you don’t have to guess either.

You just scored three of your eleven slides. Score the other eight, check the sequence, and run the memo before you send this version to anyone.

Build the rubric once. Run it on every draft.

Download below

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They publish a list.

Not a vague thematic outlook. Not a “we’re excited about AI” blog post. A specific, partner-attributed, publicly available wishlist of exactly the kinds of companies they want to fund. They call it the Request for Startups.

Most founders glance at it. A few founders read it. Almost none of them dissect it the way they should.

That’s a mistake. Because the RFS is not just a list of ideas. It’s a window into how YC’s partners are reading the moment. It tells you which problems they believe are now solvable, which markets they think are newly vulnerable, and where they’re willing to write the first cheque. If you’re building anything in the neighbourhood of these categories, understanding the thesis behind each one gives you a meaningful edge, both in how you pitch and in how you position.

The Fall 2026 batch just dropped, and it’s a different kind of list than the one before it. Thirteen categories. A defense request written for the first time in the program’s history by a sitting cabinet official. And an opening line from YC that tells you almost everything about where this one is headed.

Let me break it down.

First: What the RFS Actually Is (And What It Isn’t)

Before we get into the categories, a calibration.

The RFS is not a requirement. YC still funds companies outside these categories. Always has, always will. The best YC companies of the last decade didn’t necessarily map neatly onto a wishlist. Airbnb didn’t. Stripe didn’t.

What the RFS is is a pre-approval signal. If your company falls into one of these categories and your execution is strong, you’re not asking a partner to build conviction from scratch. The category-level thesis already exists. You’re just demonstrating that you’re the right team to execute it.

That matters more than most founders realise. A YC interview is ten minutes. Every second a partner spends building context on your market is a second they’re not spending evaluating you. If they already believe in the space, you’ve bought yourself more time for the thing that actually wins rooms: founder credibility, specificity, and conviction.

So read the RFS. Not to narrow your options, but to understand where YC’s partners have already done the work.

Fall 2026 vs Summer 2026: The Shift in One Sentence

Before diving into Fall 2026 in full, it’s worth acknowledging where we’ve been, because the contrast is revealing.

Summer 2026 was a list about software finishing what software started: AI-native rebuilds of services, SaaS, and enterprise workflows, plus an unusually aggressive push into silicon and hardware, inference chips, semiconductor supply chains, electronics in space. It was YC saying, in effect: the AI layer is commoditising, so the interesting fights are moving to infrastructure and atoms.

Fall 2026 is a different list entirely. The “atoms” instinct is still there, but it’s pointed somewhere else. Instead of chips and orbital manufacturing, this batch’s physical-world bets are about labor, care, trust, and combat: construction crews, aging parents, ocean-based data centers, and the U.S. Army. YC’s own framing for the batch says it plainly: AI is moving into the physical world, and this new wave of startups is being asked to rebuild the systems that power it: education, healthcare, defense, finance, infrastructure, and work itself.

The other structural shift is who’s writing. Summer 2026 leaned on YC partners and a single YC-funded space-hardware founder. Fall 2026 includes, for the first time in the program’s history, a request from a sitting U.S. cabinet official, Army Secretary Daniel Driscoll, alongside operator-founders like Austin Tindle (Sorcerer) and Harsha Gaddipati (Slashy), writing from inside the problems they’re describing rather than observing them from a partner’s chair. That’s a meaningful signal about where YC thinks the best category intelligence now lives.

If you’re raising, here are 6 more worth your time:

The Claude Guide Every Founder Should Run Before Fundraising - your deck isn’t read by a partner first anymore. It’s read by a model. Here’s how to pass the screen before a human ever sees it.

The 6 Claude Prompts That Change What You Walk Into the Room With - the meeting system that gets you prepared for the investor, not just the pitch.

The Claude Prompt That Turns a Cold Email Into One a VC Actually Reads - cold emails convert at 3%. Here’s the five-prompt system that beats it.

The Two-Minute Investor Briefing Every Founder Should Be Running - the Claude agent that turns a fund and partner name into a full investor briefing before every meeting.

I Asked Claude to Reject My Pitch Until It Couldn’t. Then I Raised. - the adversarial system that finds every weak point in your pitch before an investor does.

How to Build Your Fundraising Narrative with Claude - the five-prompt sequence that turns your raw story into the argument that actually closes rounds.

The Three Threads Running Through Fall 2026

When you read all thirteen categories together, three distinct theses emerge, plus one clear outlier.

Theme 1: AI is leaving the chat window and entering the physical and institutional world.

The Primer, the Army request, Compute at Sea, New Operating Systems for the Physical World, and Data for the Real World all point the same direction: intelligence that used to live in a browser tab now has to run alongside soldiers, construction crews, ocean vessels, and sensors bolted onto real machinery. This is stated almost verbatim in the batch’s own preamble: AI is moving into the physical world; it shows up in more than a third of the categories.

Theme 2: Someone has to build the trust and plumbing layer underneath an AI-run economy.

Proving You’re Human, AI-Native Compliance Infrastructure, Self-Maintaining APIs, and A Cloud for Small Software are all, in different ways, about the unglamorous work of making an AI-saturated economy function without collapsing into fraud, regulatory chaos, or unmaintainable software sprawl. This is the least flashy thread on the list, and probably the most durable one.

Theme 3: AI becomes personal, social, and mass-market rather than an enterprise tool.

AI-Powered Consumer Products for 1 Billion People, Multiplayer AI, and AI for the Aging Population are about AI moving from something a knowledge worker uses alone at a desk to something woven into how ordinary people live, work together, and care for family. YC is explicitly betting the next iconic consumer brand hasn’t been built yet, three years into a cycle where the only new home-screen icon is still ChatGPT.

The outlier: crypto, argued from a contrarian angle.

The Best Time to Build in Crypto doesn’t sit neatly inside any of the three threads above. It’s a standalone bet that bear markets are when the real infrastructure gets built, precisely because the capital chasing “infinite yield” schemes has left the table.

A Category-by-Category Dissection

Here’s what each Fall 2026 category is actually saying, and what most founders will miss about it.

1. The Primer

Who wrote it: Andrew Miklas

The reference point is Neal Stephenson’s The Diamond Age, an adaptive book that doesn’t just teach a child to read, but grows with her over years, reshaping itself around who she’s becoming. The ask: a product that adaptively teaches young children to read, write, and do arithmetic at the quality of a devoted private tutor, at consumer scale, positioned as a supplement to teachers rather than a replacement.

What most founders miss: the entry point (a parent buying a reading and arithmetic tool) is deliberately modest. The actual thesis is a decade-long relationship with a single learner that compounds in depth over years, a retention and data moat most consumer edtech has never had access to.

2. The Future of American Defense

Who wrote it: Daniel P. Driscoll, US Secretary of the Army

The most unusual entry on the list by provenance. The Army’s pitch is blunt: modern combat has outpaced the old acquisition playbook, and the service wants low-cost interceptors, next-gen sensors, drones, and resilient logistics that plug into an open-system architecture built to survive extreme environments, from the Arctic to space to subterranean settings.

What most founders miss: this isn’t a defense-contractor RFP dressed up as a startup pitch. The explicit ask is for founders who move at startup speed and think in “cost per kill” rather than program-of-record cycles. The barrier isn’t capital or clearance; it’s cultural fit with a system that has, by its own admission, just torn up how it used to buy things.

3. A Cloud for Small Software

Who wrote it: Pete Koomen

AI coding agents have made it trivial to build “small software”: bespoke tools for one team, one workflow, one edge case, but deploying and sharing that software is still stuck in an era built for scale-first “Big Software.” Koomen’s framing: incumbent clouds optimised for complexity at scale; small software needs the opposite, something as easy to share as a Google Doc.

What most founders miss: the hard part isn’t hosting. It’s auth, permissions, and letting non-technical people share arbitrary code safely, the exact problems every “no-code” wave has stumbled on before. Solve that specifically for agent-generated software and you own a genuinely new category of cloud.

4. Multiplayer AI

Who wrote it: Aaron Epstein

The pattern Epstein points to is real: the tools that won the last two decades of work software went multiplayer first (Docs over Word, Figma over Photoshop). AI agents, by contrast, are still mostly single-player, one person, one chat window, one private transcript a teammate can view but not touch.

What most founders miss: as agent tasks stretch from minutes to days or weeks, the unit of work stops being an individual’s problem and starts being a team’s. The company that builds the shared, live session (where colleagues can watch, redirect, and hand off an agent mid-task the way they would a human teammate) is building the Figma moment for agentic work, not just a better chat UI.

5. Compute at Sea

Who wrote it: Francois Chaubard

The setup: AI is running out of compute, and data centers are running out of electricity, land, and increasingly local political tolerance. The ocean, by contrast, offers abundant sunlight, no permitting process, and a natural heat sink. The proposed unit is a “compute flotilla”: standardised, modular vessels operating together as one global cloud.

What most founders miss: this reads like a hardware moonshot, but the actual startup opportunity is closer to fleet logistics and marine engineering than chip design. The teams best positioned here have offshore, maritime, or industrial-vessel backgrounds, not just AI-infrastructure résumés.

6. AI-Powered Consumer Products for 1 Billion People

Who wrote it: Raphael Schaad

The provocation is sharp: every prior platform shift minted consumer giants; the web gave the world Google and Airbnb, mobile gave it Instagram and DoorDash; yet three years into the AI shift, the only new icon on most home screens is ChatGPT. Schaad’s argument is that intelligence has crossed the threshold where an agent can be treated like a person, and the cost of running that agent is falling roughly 10x a year, which means the consumer moment is close and whoever moves first owns it.

What most founders miss: the category isn’t “build an AI chatbot for X.” It’s a reopening of every basic human activity, getting around, learning, staying healthy, managing money, socialising, on the assumption that the previous generation of consumer apps solved these problems under compute and intelligence constraints that no longer exist.

7. AI for the Aging Population

Who wrote it: Max Kolysh

The demand curve here isn’t speculative: by 2030, one in five Americans will be over 65, with millions of caregiving jobs projected to go unfilled and 53 million family members already providing unpaid care. Meanwhile almost no consumer technology, including voice assistants, is actually designed for older users.

What most founders miss: the addressable buyer isn’t just the senior, it’s the adult child coordinating care from a distance. Products that solve for both the aging user’s dignity and independence and the family caregiver’s coordination burden have a much wider wedge than either alone.

8. New Operating Systems for the Physical World

Who wrote it: Charlie Warren

Eighty percent of the global workforce doesn’t sit at a desk, yet the software running construction, maintenance, and fleet operations has barely changed in two decades; it dispatches people, tracks them, manages assets, and bills the customer. Warren’s framing introduces a genuinely new wrinkle: there are now three categories of worker to manage simultaneously: AI agents that can quote and schedule work, robots physically deployed in the field, and humans wearing devices that record everything they do.

What most founders miss: the defensibility isn’t the software interface, it’s the data. A company operating at this layer captures end-to-end records of how physical work actually happens, data that no frontier lab, robotics startup, or legacy vendor currently has, because none of them sit at the point where the work occurs.

9. The Best Time to Build in Crypto

Who wrote it: Nemil Dalal

The contrarian case: prices are down, hyped narratives have fizzled, and builders are leaving; YC treats this as the buy signal, not the exit signal. The argument is that bear markets filter out founders chasing quick liquidity and let the founders solving real infrastructure problems build without competing against schemes promising impossible yield. YC notes it has already funded more than 100 crypto startups, expects that number to keep growing, and predicts most future YC companies will eventually run on crypto rails for capital raising or payments without most people even realising it.

What most founders miss: the specific bets named (stablecoin applications, agentic commerce, institutional products, and private or scalable blockchains) are all rails plays, not speculative-asset plays. This entry is about picks-and-shovels infrastructure, not token prices.

10. Data for the Real World

Who wrote it: Austin Tindle (Sorcerer) and Diana Hu

The observation is precise: models have gone superhuman on code, language, and images, but the physical world is still measured with sparse sensor data designed for humans, not for training AI. Falling sensor costs and improving foundation models have made dense physical-world data collection newly viable; the entry cites Gecko Robotics collecting structural data from hard-to-reach infrastructure and Sorcerer’s own autonomous weather balloons feeding government forecasting.

What most founders miss: the stated end-state is control, not just measurement. Once a physical system is densely modelled, it becomes steerable. The examples given (steering hurricanes, reversing desertification) sound outlandish, but the real near-term opportunity sits several steps earlier, in energy, agriculture, logistics, and construction, where “more real-world data” alone would already be transformative.

11. Proving You’re Human

Who wrote it: Max Kolysh

The framing example is genuinely alarming: a finance worker joined a video call with people he believed were his CFO and colleagues, and wired out $25 million. Every other person on that call turned out to be a deepfake. Kolysh’s argument is that every trust signal the internet currently relies on, a face on a call, a voice on a line, was built for a world where faking a human was expensive, and that world no longer exists.

What most founders miss: the ambition here isn’t a better deepfake detector. It’s becoming the verification layer that every bank, app, and video call checks before it trusts anyone: infrastructure-level ambition dressed as a security product, with an explicit design constraint that it shouldn’t require everyone to surrender their privacy to use it.

12. AI-Native Compliance Infrastructure

Who wrote it: Daivik Goel (Shor)

Financial compliance today is described as spreadsheets, siloed point solutions, and expensive headcount, with complexity compounding faster than revenue as companies expand into new jurisdictions. Goel’s argument is that most compliance work (monitoring regulatory change, flagging anomalies, generating reports, maintaining audit trails) is exactly the kind of task AI now handles faster and more cheaply than people, yet most existing tools are still built around manual review.

What most founders miss: the win condition isn’t automating the existing compliance workflow. It’s rethinking what compliance operations look like when AI is the default reviewer rather than the exception. State-by-state licensing and renewal cycles are named specifically as the acute pain point, suggesting a sharper wedge market than an enterprise-wide platform play from day one.

13. Self-Maintaining APIs

Who wrote it: Harsha Gaddipati (Slashy)

Gaddipati’s data point, drawn from working with more than 50 early-stage API vendors, is that API communication is structurally broken: breaking changes ship with little warning, useful features launch and go unnoticed, and changelogs simply don’t get read. He cites a striking internal statistic from his time at AWS: over 30% of service downtime traced back to unnoticed external API or package changes.

What most founders miss: the shift he’s pointing to is that agentic coding tools have already normalised giving external tools write access to a codebase, something that would have been unthinkable two years ago. The opportunity isn’t better changelogs; it’s API providers shipping the fix directly into customer codebases as a pull request, either as a per-provider agent or as a neutral third-party service: essentially Dependabot for the entire API layer, not just dependencies.

What This List Tells You If You’re Not Building Any of These

The RFS is useful even if your startup doesn’t fit a single category.

Read it as a map of YC’s macro bets right now. They’re saying AI’s frontier has moved from chat interfaces into physical institutions: schools, armies, oceans, construction sites, aging households. They’re saying the plumbing underneath an AI-run economy (trust, compliance, API maintenance, deployment) is as investable as anything built on top of it. And they’re saying consumer AI, after three years of enterprise-first attention, is about to have its platform moment.

If your startup sits in a different category but reflects those underlying beliefs (that you understand a domain from the inside, that your product is AI-native rather than AI-decorated, that you’re attacking a problem where the incumbent’s advantage has quietly evaporated) you’re in the right mental model even if you’re not on the list.

The RFS doesn’t define the universe of fundable companies. It defines the universe where YC has already done the thinking.

My Honest Take on Fall 2026

This is a more institutionally ambitious list than Summer 2026 was, even though it’s less flashy on paper. There’s no orbital manufacturing entry, no exotic chip-architecture ask. What’s here instead is arguably harder: convincing an eight-decade-old defense procurement bureaucracy to move at startup speed, building financial rails for an economy that mostly doesn’t know it’s about to run on them, and rebuilding the trust assumptions the entire internet has quietly relied on since before video calls existed.

The category I think is most underpriced by founders reading this list: Self-Maintaining APIs. It sounds like a narrow DevTools niche, but if agentic coding tools really have normalised write-access to customer codebases, this is a wedge into becoming permanent, trusted infrastructure inside thousands of companies at once: a distribution advantage almost no other category on this list offers as cheaply.

The category I expect to generate the most applications and the least differentiation: AI-Powered Consumer Products for 1 Billion People. The thesis is compelling, which is exactly why every founder with a consumer idea will reach for this framing regardless of fit. The founders who stand out won’t be the ones citing the falling-cost-of-tokens curve. They’ll be the ones who’ve already found a specific, ordinary human behaviour AI newly makes possible, and can show early evidence people are doing it.

And the category I think most founders will misjudge as a mismatch for a typical YC applicant: The Future of American Defense. The instinct is to assume this requires clearances, contracts, and a decade of relationships. The entry itself argues the opposite: that the old playbook has been deliberately dismantled specifically to let startups in faster. Founders who take that claim seriously, rather than assuming it doesn’t apply to them, have less competition than the framing suggests.

The RFS Is a Signal. Use It.

If you’re applying to YC for Fall 2026, the RFS should be part of your preparation. Not as a template to force-fit your startup into, but as a framework for understanding how the partners, and in this batch, a cabinet secretary and two operator-founders, are actually thinking.

The question to ask yourself: does my company reflect the beliefs behind the category I’m closest to? Do I understand the underlying thesis, not just the surface-level description? Can I articulate why now, why this market, and why my team, in the language of someone who has already committed to the space?

If you can answer those questions clearly, you’re not just pitching a product. You’re confirming a thesis they already hold.

That’s a very different kind of conversation.

🔒 The YC Application Bundle

Everything above is free. What follows turns that framework into action.

Paid subscribers get four tools built on the exact YC framework in this article. Most founders who run through them find one or two blind spots they didn’t know they had; better here than in a ten-minute interview room.

The YC Readiness Assessment scores your startup across the four dimensions YC actually uses to evaluate founders. You get a score for each one, specific gaps identified, and actionable guidance on what to fix before you apply.

The YC Category Fit Finder takes your startup description and tests it against every Fall 2026 RFS category. You see where you land strongest, which category is your best fit, and the precise framing that sharpens your pitch for that thesis.

The YC Video Script Builder generates a complete 60-second script in YC’s preferred format: who you are, what you build, your traction, why your team, confident close. The video is where most applications die. This fixes that.

The YC Founder DNA Matrix asks you the same seven questions YC partners ask in interviews, scores your answers the way they would, and shows you exactly what a higher-scoring answer looks like. Built on 20+ years of watching founders in these rooms.

Plus full access to the entire Founders Corner archive - every prompt, framework, and teardown we’ve published on getting a round closed.

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The Four Things Standing Between You and a YC Interview

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Let’s get into it.

First, something free 👇

The founders winning in 2026 are everywhere: LinkedIn, newsletters, podcasts, investor DMs. They run on a system that publishes for them, rather than carving out time they rarely have.

We built that system into a free AI Creator Kit: one Notion workspace with AI agents, templates, a creator CRM, and partner credits worth thousands.

Grab it here, no paywall:

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In-Depth Insights 🔍

• The Investor Outreach System: List, Prompts, Sequence, Replies 🔗
  The playbook outlines an automated LinkedIn workflow covering investor targeting, personalized messaging, outreach sequencing, and reply management. It argues consistent personalization fades at scale and pairs templates with supporting fundraising resources to improve execution.

• How to Find and Win the Economic Buyer in B2B Software Sales 🎯
  Chris Tottman explains that budget authority usually sits with the Economic Buyer rather than the internal Champion supporting the purchase. He recommends tracing budget ownership, understanding personal incentives, and treating discovery conversations as business diagnosis instead of product demos. []

• Software’s Selective Sell-Off and AI’s Real-World Impact ⚡
  Software multiples have fallen to decade lows while cyber, observability, and vertical SaaS continue to outperform broader software categories. Lower AI costs are increasing adoption, boosting hiring and wages in AI-heavy sectors, while data center expansion aligns with cheaper electricity in key markets. [, ]

• KIMI’s Agent Playbook: 10 Bets Founders Should Steal🧠
  Yang Zhilin argues agent systems outperform pure reasoning by learning from live feedback instead of operating in isolation. He also shares Moonshot’s efficiency work, rejects a fixed definition of AGI, and sees AI expanding human capability over time.

• The 10 Claude Skills Every Founder & Builder Should Steal 🛠️
  The guide packages ten reusable Claude workflows for research, product strategy, engineering, pricing, fundraising, and decision making. Each workflow defines a persona, structured output, strict constraints, and a forcing function with setup instructions for Claude.

• Power, Status, and Legitimacy in Tech ⚖️
  The essay argues tech status has shifted from fundraising prestige to revenue milestones, but both remain signals valued mainly within the industry. It claims lasting legitimacy comes from building institutions, giving back, or surrendering control instead of relying on company success alone. [Michael Dempsey]

  

• The Problem with Hypergrowth AI Startups 📉
  Many fast-growing AI startups rely on reselling inference, making revenue growth vulnerable to shrinking margins and commodity pricing. As enterprises adopt bring your own inference strategies, businesses without durable differentiation may struggle to justify premium valuations. [Zach Lloyd]

  

Social Media Gems 💎

• Fundraising Around Lift, Not Runway 🎯
  Keith Rabois argues capital should match the next value creating milestone instead of targeting an arbitrary cash buffer. Ruben also announced his role as an a16z Speedrun scout, offering founders fast feedback, funding opportunities, and program introductions.

• Every Funding Round Removes Risk 🧩
  A startup begins with execution, product, market, and commercial uncertainty that investors expect to shrink over time. Seed validates the foundation, Series A proves repeatability, and each milestone clears another reason for investors to hesitate.

Trending News ⚡

• Anthropic’s $1.5B Copyright Settlement Approved ⚖️
  A judge approved a $1.5 billion settlement covering roughly 500,000 illegally downloaded books at $3,000 per work. The court kept its fair use ruling for model training but ruled acquiring books from pirate sites violated copyright law. [TechCrunch]

• US Commits $5B to AI Powered Research 💵
  The US will invest $5 billion across 15 agencies to apply AI to healthcare, science, and advanced materials. Microsoft will contribute $40 million in compute credits to support research over the next three years. [Reuters]

• OpenAI Sees Secondary Market Comeback 📈
  Demand for OpenAI shares is climbing after recent model launches and stronger Codex adoption. Anthropic remains the most sought after private AI company despite the shift in investor activity. [Business Insider]

  

• DeepSeek Founder Prioritizes AGI Over Profit 🔓
  Liang Wenfeng said DeepSeek will focus on long term AGI development instead of maximizing short term returns. He also argued computing infrastructure, not technical talent, remains the largest competitive gap with the US. [Reuters]

  

• Anthropic Physical Intelligence Talks Resurface 🤖
  Reports confirmed Anthropic discussed acquiring Physical Intelligence earlier this year despite public denials. OpenAI’s investment in the startup has also renewed questions about future ownership possibilities. [TechCrunch]

  

• Google Developing New Efficient AI Chip 🔧
  Google is building a next generation server chip designed to deliver significantly higher efficiency by 2028. The report lifted Alphabet shares ahead of earnings as investors looked for lower AI infrastructure costs. [TechCrunch]

• ChatGPT’s Ad Business Faces Analyst Skepticism 📉
  Analysts believe OpenAI’s advertising revenue targets are well ahead of current market expectations. Advertisers also point to limited measurement tools compared with established platforms like Google and Meta. [Business Insider]

• Moonshot Pauses New Kimi Subscriptions 🔒
  Moonshot temporarily stopped new Kimi K3 subscriptions after demand pushed GPU capacity to its limit. Current users remain unaffected while the company expands infrastructure before its planned open release. [Business Insider]

  

• Anthropic Upgrades Claude’s Voice Mode 🎙️
  Claude users can now switch between Opus, Sonnet, and Haiku directly in voice conversations. The update also expands app connections while keeping free accounts limited to Haiku and one integration. [TechCrunch]

  

• OpenAI Chair Predicts End of Token Worries 🪙
  Bret Taylor expects token management to become invisible as specialized providers handle the complexity. He compared the shift to the early internet, where technical barriers steadily disappeared as the ecosystem matured. [Business Insider]

New Funds 💰

• Fresenius launched a €200M corporate venture capital fund to invest in breakthrough healthcare technologies and drive healthcare innovation.

• Transition VC launched its second £155M venture capital fund to back early-stage climate tech startups accelerating the energy transition.

• Supercharger Ventures launched €10M Fund I to invest in early-stage edtech and future-of-work startups across Europe.

• EHE Ventures opened the second cohort of its $15M venture fund, continuing to back high-potential early-stage founders.

• Primo Capital launched Primo Space 2, its second venture capital fund focused on supporting European space technology startups.

That’s a wrap for this week.

If you want to stay ahead of the curve, make sure you're subscribed. No fluff, just real startup insights delivered straight to your inbox.

See you next time 🚀

This series is a preview of a new book I’ve written with my partners Richard Blundell and Paul Watson — The Selling Software Algorithm: The Go-to-Market Navigation System for B2B Software Leaders.

It isn’t a strategy deck dressed up as a book. Between the three of us we’ve spent close to seven decades inside B2B software as founders, operators, investors and coaches — building companies, exiting some, and quietly breaking a few along the way, which is where most of the real learning lives. Through our work at Vencha we’ve now supported hundreds of founders trying to do the single hardest thing in software: turn a clever product into predictable commercial traction in a market that’s noisy, cautious, and more crowded than it has ever been.

One pattern shows up again and again. Companies rarely struggle because the product is bad. They struggle because they have no navigation system for going to market. This book is that system.

Get My Copy

Too Long; Didn’t Read (TL;DR)

• The Economic Buyer is the person who ultimately decides whether your software is purchased, implemented and renewed. They carry the budget, the accountability, and the personal consequences of the decision.

• Beware the Champion trap: the enthusiastic first contact who loves your demo almost never holds the pen. Warmth is not authority. Activity is not commitment.

• To find the real buyer, follow the money — and get your own team aligned on budget ownership and accountability before you get anywhere near a pitch.

• Behind every title is a human being navigating ambition, pressure, insecurity and hope. Operational pain almost always becomes personal pain.

• Economic Buyers buy software when they can also see personal advantage in its success: a defensible decision, calmer Mondays, protected reputation, career progress, and cover from blame.

• Never let a first meeting with an Economic Buyer become a demo. Discovery is a diagnosis: start with their context, ask what success looks like for them personally, and test yourself by writing their internal summary of the conversation.

• The Wooden Spoon Test: if access to the Economic Buyer is repeatedly delayed or resisted, that’s a red flag — you may be stirring a deal that will never come to the boil.

Last time, we landed on a single sentence — the spine of the whole Selling Software Algorithm:

Our software is perfect for a clearly defined Economic Buyer, in a tightly defined Perfect Customer Profile, who’s struggling with the three most visceral pains our software solves.

Now we start pulling it apart, one component at a time, because the strength of the whole equation depends on the clarity of each part. And it begins where almost every software business quietly comes unstuck.

Not in the product. Not even in the pitch.

In the simple question of who your software is really for.

Here’s the trap. The person who loves your demo the most — the one who replies quickly, gets it instantly, and promises they can “sell this internally” — is almost never the person who can actually buy it. Founders pour weeks into that relationship, mistake the warmth for progress, and wonder months later why the deal quietly died.

Let me show you who really holds the pen. And, more importantly, what they’re actually buying when they say yes.

Table of Contents

• Who is the Economic Buyer in a B2B software deal?

• Why do B2B deals die even when my champion loves the product?

• How do I find out who really controls the budget for a software purchase?

• What motivates a B2B Economic Buyer beyond the job title?

• What are Economic Buyers actually buying when they buy software?

• How should I run a discovery meeting with an Economic Buyer?

• How to tell if a stalled software deal is ever going to close.

Who is the Economic Buyer in a B2B software deal?

Let’s be clear straight out of the gate.

An Economic Buyer isn’t the person who likes your demo the most. It isn’t the user who’ll log into your product every morning. And it certainly isn’t the enthusiastic first contact who tells you they can champion this from the inside.

The Economic Buyer is the person who ultimately decides whether your software is purchased, implemented and renewed.

They carry the budget. They carry the accountability. And whether they admit it or not, they carry the personal consequences of getting the decision right or wrong. Their signature releases the funds. Their name sits against the budget line your solution affects. They can approve the whole thing — or block it with a single flick of the pen.

Organisations are full of people who can slow a deal down, complicate it, or quietly kill it. But only one person can properly approve it and drive adoption. That “yes” is the only one that ultimately matters.

If the Economic Buyer isn’t aware of your solution, isn’t engaged, and isn’t convinced throughout the sales cycle, your deal is always at risk of missing a heartbeat. It drifts into procurement limbo. It stalls under internal politics. Or it dies quietly, without anyone ever telling you why.

So the first discipline is brutally simple: you and your team must be able to point at one person and say, with confidence, that’s who we need to convince.

Why do B2B deals die even when my champion loves the product?

Most founders don’t fail this test because they’re careless. They fail it because of the Champion.

The Champion is usually the first person to show genuine enthusiasm. They see the potential quickly. They recognise the inefficiency and want their day to run more smoothly. They speak your language, they help you navigate the organisation, and they’re often the reason you get a second meeting at all.

Champions are not optional. They’re frequently the doorway.

But Champions don’t sign contracts, and they don’t usually control budget. They don’t have to defend your proposal when leadership scrutiny arrives. They can influence the decision. They rarely make it.

This is why your narrative has to resonate with two very different people at once.

The Champion cares about workflow and execution — they want the process to work, and they want their day to be smoother. The Economic Buyer cares about business outcomes, risk and credibility — they need the decision to be defensible, their quarter to be more predictable, and their leadership story to hold under pressure.

See the deal through that dual lens and you stop mistaking everyday enthusiasm for genuine authority. You stop orbiting someone supportive but powerless. And you start building a path that can actually reach the signature on the dotted line.

Warmth is not authority. Activity is not commitment. Hold onto that.

How do I find out who really controls the budget for a software purchase?

So how do you find the real one?

Follow the money. And accept that it often leads you higher up the org chart than you first assumed.

This sounds obvious until you sit in a room — as we have, many times — with three whip-smart founders from the same company who all give a different answer to the same question. One is certain the buyer sits in Finance. Another assumes Operations. A third insists it’s IT.

They can’t all be right, and the disagreement is quietly costing them every deal.

We worked with an AI recruitment business for years where the instinct was always to target Heads of Talent or People. Sometimes that was correct. But just as often the CFO turned out to be the real decision-maker, because they could see the whole-organisation financial advantage of hiring more efficiently — an advantage no departmental head could unlock alone.

The lesson isn’t that one function is always the buyer. It’s that you have to decide, together, based on budget ownership and accountability — not based on who seemed most excited on the first call.

Get your own team aligned on this before you get anywhere near a pitch.

What motivates a B2B Economic Buyer beyond the job title?

Here’s where most founders stop, and where the real work actually begins.

Too many look at the Economic Buyer and see only a label. CFO. COO. VP of Operations. Head of HR. They build their messaging around the responsibilities of the role, talk confidently about operational efficiency, and assume the decision is driven entirely by logic.

Logic matters. But it’s nowhere near the whole story.

Behind every title is a human being navigating ambition, pressure, insecurity and hope. And that personal dimension shapes buying behaviour far more than most founders realise.

Picture a day in their life. They wake early — often earlier than they’d like — into a day already crowded with noise. On the commute they’re turning over the mortgage, a holiday they promised the family, maybe elderly parents they’re helping to care for. Then they walk into work and lead a department that’s expected to perform, reporting to someone who wants results without excuses. They sit in leadership meetings where targets are reviewed and pressure gets redistributed. And they carry a bonus whose importance never shows up on a spreadsheet, but is often the thing that makes their personal maths work.

Now connect that back to your software.

The operational pain you’re selling into almost always becomes personal pain. A broken process doesn’t just slow the business down — it reflects badly on the leader responsible for it. A dependence on spreadsheets doesn’t just create inefficiency — it creates friction between teams, and quiet moments of embarrassment when the numbers don’t reconcile or the report lands late. A recurring issue that generates weekly complaints becomes an emotional weight, because it sits on that person’s shoulders in every one-to-one, every Monday meeting, every board update.

Over time those irritations chip away at confidence and erode credibility. They turn leadership into apologising and justifying, rather than steering and improving.

Senior leaders guard their reputation because reputation is their currency of influence. Your job is to understand exactly where that currency is being quietly depleted.

What are Economic Buyers actually buying when they buy software?

Which brings us to the single most useful idea in this whole chapter.

Economic Buyers buy software when they can also see personal advantage in its success.

The operational benefits have to be there — nobody’s arguing otherwise. But it’s the emotional, reputational and career benefit that creates urgency. They buy when they can picture the relief of removing a nail from their boot. When they can imagine calmer Mondays and cleaner reporting cycles. When they believe the decision will protect them from blame, position them for promotion, or help them deliver the objective that secures the bonus.

That framing isn’t cynical. It’s respectful.

Leadership roles are high-pressure and high-consequence. Great founders don’t ignore that reality — they build their narrative around it. When your product helps a leader deliver visible progress, even incrementally, you stop being a vendor and become an ally. Sometimes even a friend.

One HR leader at a large home-improvement retailer told us, with real pride, about the day his CEO held him up in front of the other leaders as the example of AI innovation done well. That kind of internal moment is pure gold. When your software helps create it, you’re no longer selling a tool. You’re helping someone tell a better story about their own competence and momentum.

And when you translate value into their language, make it defensible. “Saves time” is vague. “Cuts time-to-hire by 28 days” or “reduces screening effort by 80 percent” gives them something they can stand behind in a room full of scrutiny.

How should I run a discovery meeting with an Economic Buyer?

If you’re lucky enough to secure an hour with an Economic Buyer, here’s advice worth its weight in gold: never let that first meeting become a demo. Ever.

It feels harmless — even productive. You’re proud of what you’ve built, the silence is uncomfortable, and clicking through screens feels safe. But the moment discovery turns into a feature tour, you’ve handed control away. Your job in that room isn’t to present. It’s to understand.

The best Economic Buyer meetings feel far closer to a diagnostic consultation than a sales pitch. A good doctor doesn’t prescribe before they understand the symptoms, and they ask more questions than you expect because accuracy matters more than speed. Adopt exactly that posture.

Come prepared. Read their LinkedIn properly — not to memorise their CV, but to understand the shape of their journey and the pressures that come with it. Form a hypothesis about where pressure is building before you ever speak. Then, in the room, start with their context, not your product. Ask about the department’s goals for the next twelve months. Ask what risks keep surfacing in leadership conversations. Ask what’s been tried already, and why it failed. Ask them to walk you through the process your software improves — and where it frustrates, embarrasses or slows them down.

Then listen as if your life depended on it, because every answer is a window into what they value and how they decide.

Before the meeting closes, ask the one question that reveals more than any other: what does success look like for you personally if this works — and how would that world feel? That gently shifts the conversation from software towards ambition, reputation and the human meaning of progress. And that shift is often the moment a deal genuinely begins.

Here’s a test for afterwards: could you write the buyer’s own internal summary of the conversation on their behalf? The problem as they see it, the cost of leaving it unresolved, the reason to act now, the likely risks, the next steps? If you can, you did the work. If you can’t, then however pleasant it felt, you were still operating on assumption.

How to tell if a stalled software deal is ever going to close.

We often suggest founders keep a wooden spoon on their desk. Not as a gimmick, but as a quiet reminder.

Without the Economic Buyer genuinely engaged, it’s remarkably easy to find yourself stirring the same opportunity over and over — warming it gently, adding ingredients, adjusting the seasoning, convincing yourself progress is being made — when in reality nothing is ever going to come to the boil.

You can build a wonderful relationship with a Champion. You can run brilliant demos for users, gather warm feedback, refine proposals, and pour hours into supporting internal conversations. All of it can feel productive. And all of it stays fragile without the conviction and sponsorship of the person who actually holds the pen.

So when access to the Economic Buyer is repeatedly delayed or resisted, don’t treat it as a minor inconvenience. It’s a signal — often a red flag. A Champion who won’t involve the ultimate decision-maker is frequently protecting uncertainty, not progress.

There are calm, professional ways to insist on that access. Frame the meeting as necessary for accuracy, not persuasion — you’re asking for time to understand, not to sell. Anchor it to risk: similar projects fail when senior context is missing, and thirty minutes upfront materially reduces that risk. Offer a tight agenda, and promise explicitly that there’ll be no demo and no pitch. And be prepared, at least mentally, to walk away — because if you can’t reach the buyer after repeated professional attempts, you have to question whether the deal is real at all.

This is why the Economic Buyer sits at the very start of the algorithm. They are the human centre of every meaningful sale.

Understand them. Respect them. Help them win.

Do that, and everything downstream — the sales cycle, the approval path, the adoption, the references — becomes dramatically easier.

Next in the series, we take this same discipline and point it at the second part of the sentence: not the person, but the company. How to define your Perfect Customer Profile with enough precision that it becomes a forcing function — and stops you wasting a single week on the accounts that were never going to buy.

—Chris Tottman

Frequently Asked Questions

Who is the Economic Buyer?

The person who ultimately decides whether your software is purchased, implemented and renewed. They carry the budget, the accountability, and the personal consequences of the decision. Their signature releases the funds, and they can approve the whole thing or block it with a single flick of the pen.

What is a Champion, and why aren’t they enough to close a deal?

The Champion is usually the first person to show genuine enthusiasm — they speak your language, help you navigate the organisation, and are often the reason you get a second meeting at all. But Champions don’t sign contracts and don’t usually control budget. They can influence the decision; they rarely make it. Warmth is not authority, and activity is not commitment.

How do I identify the Economic Buyer in a target account?

Follow the money, and accept it often leads higher up the org chart than you first assumed. Decide as a team based on budget ownership and accountability — not on who seemed most excited on the first call. In one AI recruitment business, the real decision-maker was often the CFO rather than the Head of Talent, because only the CFO could see the whole-organisation financial advantage.

Why do deals stall even when everyone I talk to loves the product?

Because organisations are full of people who can slow a deal down, complicate it, or quietly kill it — but only one person can properly approve it and drive adoption. If the Economic Buyer isn’t aware, engaged, and convinced throughout the sales cycle, the deal drifts into procurement limbo, stalls under internal politics, or dies quietly without anyone telling you why.

What does an Economic Buyer actually buy?

Personal advantage alongside operational benefit. They buy when they can picture the relief of removing a nail from their boot: calmer Mondays, cleaner reporting cycles, protection from blame, positioning for promotion, and delivery of the objective that secures the bonus. The emotional, reputational and career benefit is what creates urgency.

What should the first meeting with an Economic Buyer look like?

A diagnostic consultation, never a demo. Come prepared with a hypothesis about where pressure is building, start with their context rather than your product, ask about goals, risks, and what’s been tried before, and close with the question that reveals more than any other: what does success look like for you personally if this works?

What is the Wooden Spoon Test?

A reminder that without the Economic Buyer genuinely engaged, you can stir the same opportunity over and over — warming it, adding ingredients, adjusting the seasoning — and it will never come to the boil. If access to the buyer is repeatedly delayed or resisted, treat it as a red flag and question whether the deal is real.

How do I get access to the Economic Buyer when a Champion is blocking it?

Insist calmly and professionally. Frame the meeting as necessary for accuracy, not persuasion; anchor it to risk, since similar projects fail when senior context is missing; offer a tight agenda with an explicit promise of no demo and no pitch; and be prepared, at least mentally, to walk away if repeated professional attempts fail.

Most founders lose their raise before they ever send the first email.

The ones who close have something the rest don’t: they know exactly how investors read a pitch deck before you’re even in the room, which AI prompts are quietly transforming how founders prepare, how to turn a cold outreach into a warm conversation, what a two-minute briefing can do that a ten-slide deck can’t, how to stress-test your pitch before an investor ever sees it, and how to build a fundraising narrative that actually sticks.

That edge isn’t luck. It’s 30 years sitting across the table from founders, 500+ investments, and the patterns that quietly decide who gets funded and who gets ghosted — now distilled into a system you can use today.

We’ve packaged all of it into 60+ premium tools. One subscription.

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Start with these six. They’ve already changed the outcome for thousands of founders before you — here’s what happens when it’s your turn:

Your Pitch Deck’s First Reader Isn’t Who You Think — Before any human sees it, something else decides its fate. Know what it is before you hit send.

The 6 Claude Prompts That Change How You Raise — Most founders use AI to write emails. The ones closing rounds use it like this instead.

The Claude Prompt That Turns a Cold Outreach Warm — One prompt. The difference between ignored and in the room.

The Two-Minute Investor Briefing — Investors don’t have time. This format respects that — and gets the meeting anyway.

I Asked Claude to Reject My Pitch — Here’s What It Found — The holes investors find but never tell you about. Find them first.

How to Build Your Fundraising Narrative — Not your deck. Not your numbers. The story that makes both of them land.

Every raise has two sides: the founders who get the meeting, and the ones who wonder why they didn’t. Upgrade now — and make sure you’re on the right one.

Name five venture capital firms. Easy, right? Sequoia. a16z. Benchmark. Founders Fund. Accel. Every founder on the planet can rattle these off before their coffee gets cold.

Now name five family offices.

...

Yeah. That’s the point of this issue.

There are thousands of family offices around the world, private investment vehicles set up by billionaire families to manage and grow their own money. No LPs to report to. No 10-year fund cycles. No committee of associates deciding whether you’re “on brand.” Just a small, quiet team deploying capital on behalf of one family, writing checks when they like something, and staying invisible while they do it.

Collectively, family offices now manage more capital than the entire global venture capital industry. And almost none of them show up on Crunchbase, at Demo Day, or in your warm intro network.

So we did something about it. We spent the last few weeks compiling a working directory of 287 family offices and family holding companies across North America, Latin America, Europe, the Middle East & Africa, and Asia-Pacific: who runs them, what wealth they came from, where they’re based, and how (if at all) you can find them online.

Here’s a small taste of what’s in it. 👇

🇺🇸 A few you’ll recognize (and a few you won’t)

• Cascade Investment / Gates Ventures: Bill Gates. Kirkland, WA. Massive farmland, rail and hotel holdings most people have never connected to Microsoft money.

• Bezos Expeditions: Jeff Bezos’s personal venture and growth vehicle, separate from Amazon and Blue Origin entirely.

• Emerson Collective: Laurene Powell Jobs. Hybrid investment-and-philanthropy shop that quietly owns The Atlantic.

• JAB Holding Company: The Reimann family. The quiet hand behind Krispy Kreme, Keurig, Dr Pepper and half your coffee cabinet.

• Kirkbi A/S: The family behind LEGO, holding 75% of the LEGO Group plus a growing renewables and entertainment portfolio.

• ICONIQ Capital: San Francisco. The multi-family office for tech founders like Zuckerberg, Dorsey and Hoffman, now running north of $80bn.

That’s six. We have 281 more, including several of the most secretive capital pools on earth, family offices with literally no public footprint at all (we found and flagged those too, because knowing they exist is half the battle).

Why this matters more than your VC target list

Here’s the uncomfortable truth nobody tells founders early enough:

VCs need to say yes to someone every quarter. It’s a numbers game with a fund clock ticking. That’s exactly why the space is crowded, commoditized, and full of founders pitching the same 40 firms.

Family offices operate on a completely different logic:

1. No fund cycle pressure. They can write a check today, or wait five years for the right thing. Patience is their entire edge.

2. No committee theater. Many are a principal plus two or three people. If the principal likes it, it moves.

3. They actively seek deal flow VCs can’t access: direct real estate, private industrials, sports, consumer brands, climate infra, and yes, increasingly, tech.

4. They’re radically under-pitched. Most founders have never sent a single cold email to a family office. You’d be one of very few doing it right.

The catch? They’re hard to find, harder to research, and impossible to cold-email if you don’t even know they exist under that name.

That’s the entire problem this directory solves.

If you’re raising right now, don’t skip these

Finding the right family office is only half the game. The other half is not blowing it once you’re in the room, and that’s where most founders actually lose the deal. If you’re mid-raise (or about to be), go read these next:

• The Number That Kills More Fundraises Than Any Bad Idea: one slide, one metric, and it’s quietly killing raises without founders ever knowing it.

• The Quiet Filter That Decides Your Entire Fundraise: every investor runs this before you even open your mouth. Learn it now, not after the “no.”

• The Way VCs Actually Calculate Your Valuation: they already have a number in their head before you walk in. Here’s how to hit it.

• How Investors Decide If You’re Ready to Raise: it’s not timing, it’s not luck. These are the exact criteria they’re using on you right now.

• The Pitch Deck Test Investors Use: the same test gets applied to every deck that crosses their desk, including yours.

What’s actually inside the full directory

The version we’re unlocking for Premium subscribers isn’t a teaser: it’s the whole working file:

• ✅ 287 entries, organized by region (North America · Latin America · Europe · Middle East & Africa · Asia-Pacific)

• ✅ Family/principal names, source of wealth, city & country HQ for every entry

• ✅ Website or verified LinkedIn page where one exists

• ✅ A one-line note on what each office actually invests in and why it matters

• ✅ A filterable data view (not just a static list) so you can sort by region, sector, or type: single family office, multi-family office, or holding company

This is the same category of research that costs thousands of dollars a year through institutional data providers. We built it so you don’t need that budget to start.

Start your 7-day free trial → Cancel anytime.

A preview of what’s waiting behind the paywall

We’re not going to spoil all 287. But here’s a taste of the names locked inside the premium version that most founders have genuinely never heard of, several of which are actively looking for direct deals right now:

🔒 A Zurich-based single family office quietly backing biotech spinouts from one of Europe’s most famous generics fortunes

🔒 A Singapore-based family investment arm tied to Southeast Asia’s largest agribusiness conglomerate, with a dedicated venture unit

🔒 A Bay Area tech founder’s personal office, no website, no LinkedIn, completely invisible unless you know its name

🔒 A Gulf-based conglomerate’s London investment arm sitting on stakes in Premier League and consumer brands alike

Every one of those is in the sheet, with a name, a city, and a way to find them.

This is exactly the kind of asset we built Premium for

We don’t gate recaps of news you could’ve read on TechCrunch. We gate the stuff that actually changes your week: proprietary lists, frameworks, and research you can act on the same day you get it.

Premium subscribers get:

• The full 287-entry Family Office Directory (this issue)

• Every past and future proprietary database, framework and swipe file we publish

• Early access to new research before it goes out to the free list

• Zero ads, zero fluff, just the operator-grade stuff

Plus full access to the entire Founders Corner archive - 60+ founder tools: every prompt, framework, and teardown we've published on getting a round closed.

If you’ve been on the fence about upgrading, this is the issue to do it on. The directory alone is worth more than a year of Premium if it helps you land even one direct conversation that a VC intro never could.

Download the Family Office Directory

287 names.

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It’s the one where every investor email gets drafted in eight seconds instead of forty minutes. Where your data room gets stress-tested before a VC associate ever opens it. Where your market slide gets rebuilt bottom-up, your metrics get pressure-checked against the benchmarks a partner will quote back at you, and your follow-up sequence writes itself the moment a meeting ends.

That version exists. Founders are running it. And the only thing separating them from the founder still hand-typing cold emails at 11pm isn’t budget, or connections, or a better idea.

It’s a prompt library.

Not a chatbot. A library. 40 specific, tested, role-loaded prompts that turn one tool into an entire fundraising function: a researcher, a copywriter, a financial analyst, and a brutally honest advisor who has read ten thousand decks and will tell you exactly where yours dies.

Here’s what almost nobody has figured out yet: the founders getting the most out of AI in a raise aren’t the ones with the cleverest single prompt. They’re the ones who stopped improvising. They built a library once, and now they run the same battle-tested prompts on every email, every deck revision, every investor meeting. The raise stops being a series of blank pages. It becomes a system.

Why “improve my pitch” produces garbage 🧠

Open Claude, paste your deck, type “how can I improve this?”, and watch it hand you a pile of encouraging, generic, useless feedback. Punchier headlines. Clearer value prop. Consider adding social proof.

You already knew all of that. It told you nothing.

The reason is simple, and once you see it you can’t unsee it: a vague prompt gets a vague role. When you don’t tell the model who it is, it defaults to Helpful Assistant - the personality trained to be encouraging and safe. Helpful Assistant is a terrible fundraising advisor. It wants you to feel good. A real advisor wants you to raise.

The entire craft of prompting for fundraising comes down to one move: stop asking for help, and start assigning a job.

Compare these two.

“Can you help make my cold email better?”

versus

“You are a Series A partner at a top-tier fund. You get 60 cold emails a week and reply to 2. Here is one of them. Tell me, in one word, whether you’d reply — then tell me the single line that made you decide.”

The first gets you a thesaurus. The second gets you the truth. Same model. Same email. The only variable that changed is that you gave it a role, a constraint, and a decision to make.

Every prompt in the library below is built on that principle. None of them ask for help. All of them assign a job.

What’s inside the full library 🗂️

40 prompts, organized by the stage of the raise where you’ll actually reach for them:

▫️ Narrative & positioning (6 prompts) - the prompts that turn “what we do” into a story a partner repeats to their committee

▫️ The deck (6 prompts) - slide-by-slide teardown prompts, including the market-slide rebuild and the traction-slide pressure test

▫️ Investor research (6 prompts) - how to profile a fund’s real thesis from its last 12 months of deals, not its website

▫️ Cold outreach (6 prompts) - the role-loaded email prompts, the subject-line generator, and the warm-intro request that people actually forward

▫️ Meeting prep (6 prompts) - the objection simulator that plays the specific partner you’re about to meet

▫️ The follow-up (5 prompts) - the post-meeting sequence that writes itself while the conversation is still fresh

▫️ Diligence & the data room (5 prompts) - the prompts that find the hole in your data room before an investor does

Below, four of them are fully written out and ready to paste right now - one from the deck, one from investor research, one from outreach, one from meeting prep. They’re the four we’d hand a founder on day one. The other 36, organized into the same seven categories, are yours as a downloadable Word document the moment you subscribe.

🟦 Prompt 1: The Rejection Simulator

Before you polish anything, you need to know how it dies. Most founders never get this - investors pass with a polite “not the right fit for us right now,” and the real reason stays buried. This prompt digs it out.

💬 Paste into Claude (new conversation, full pitch pasted in):

You are a skeptical Series A partner at a top-tier venture fund. You
pass on 98% of what you see, and you pride yourself on spotting the
fatal flaw fast. You are not here to be encouraging.

Here is a founder's pitch: [PASTE YOUR ONE-PAGER OR DECK TEXT]

Do this:
1. Write the actual internal note you'd send your partners explaining
   why you're passing. Be specific and unsparing. Name the real reason,
   not the polite one.
2. Identify the single weakest claim in the pitch — the one you'd poke
   first in a meeting to watch the founder squirm.
3. Tell me what would have to be true for you to change your mind and
   take a second meeting.

Do not soften anything. I need the version of this you'd say about me
when I'm not in the room.

⚡ Why this works: “Review my pitch” gets you a critique you’ll ignore. “Write the note you’d send your partners” gets you the sentence that’s actually killing your raise; the one no investor will ever say to your face.

🟦 Prompt 2: The Fund Thesis Decoder

A fund’s website tells you what it says it invests in. Its last twelve months of deals tell you what it actually invests in. Those are rarely the same thing, and the gap is where most cold outreach goes to die.

💬 Paste into Claude:

You are an analyst who profiles venture funds for founders deciding
who to approach. I'm considering reaching out to [FUND NAME].

Here is what I know about their recent activity: [PASTE 8-12 OF THEIR
RECENT INVESTMENTS — company names, stages, sectors, check sizes if
known. Pull these from their portfolio page or recent announcements.]

Analyze this and tell me:
1. What is this fund's REAL thesis, based on where the money actually
   goes — not their stated mandate?
2. What stage and check size are they most active at right now?
3. Based on my company [ONE-LINE DESCRIPTION], am I a genuine fit, a
   stretch, or a waste of both our time? Be honest — a "no" here saves
   me three weeks.
4. If I'm a fit, what specific portfolio company would make the
   strongest comparison in my outreach, and why?

💡 Run this before every cold email, not after. Ten minutes of thesis-decoding beats a hundred generic emails. The founders who get replies aren’t emailing more investors - they’re emailing the right ones with a reason.

If you found this useful, these are five more from the archive worth your time:

The Claude Guide Every Founder Should Run Before Fundraising - your deck isn’t read by a partner first anymore. It’s read by a model. Here’s how to pass the screen before a human ever sees it.

The 6 Claude Prompts That Change What You Walk Into the Room With - the meeting system that gets you prepared for the investor, not just the pitch.

The Claude Prompt That Turns a Cold Email Into One a VC Actually Reads - cold emails convert at 3%. Here’s the five-prompt system that beats it.

The Two-Minute Investor Briefing Every Founder Should Be Running - the Claude agent that turns a fund and partner name into a full investor briefing before every meeting.

I Asked Claude to Reject My Pitch Until It Couldn’t. Then I Raised. - the adversarial system that finds every weak point in your pitch before an investor does.

How to Build Your Fundraising Narrative with Claude - the five-prompt sequence that turns your raw story into the argument that actually closes rounds.

🟦 Prompt 3: The Cold Email That Earns a Reply

Now you know the fund is a fit. Most founders blow it here by writing an email about themselves. The email that gets replies is about the investor - specifically, about why this fund, this partner, this week.

💬 Paste into Claude:

You are a founder who consistently gets 30%+ reply rates on cold
investor emails. Your emails are short, specific, and impossible to
confuse with a template.

Write a cold email to [PARTNER NAME] at [FUND].

Context you'll use:
- What we do, in plain terms: [ONE LINE]
- The single most impressive, verifiable traction fact we have: [FACT]
- The specific reason THIS fund fits: [FROM YOUR THESIS DECODE]
- Any real connection or trigger: [shared portfolio co, recent post
  they wrote, a mutual contact — or write "none" and don't fake one]

Rules:
- Under 120 words. A partner reads it on their phone.
- Lead with the one fact that makes them curious, not with "I'm the
  founder of..."
- One clear ask: a 20-minute call. No calendar links in a cold email.
- No adjectives doing work a number should do. "Growing fast" is banned.
  Give the number or cut the claim.
- It should sound like a person who has something, not a person who
  needs something.

Give me three versions with different opening lines.

⚡ The tell: if your cold email would still make sense sent to a different fund with the name swapped out, it’s not outreach - it’s spam with better grammar. This prompt forces specificity the copy-paste crowd can’t fake.

🟦 Prompt 4: The Objection Simulator

You’ve got the meeting. Now the raise is won or lost on how you handle the three questions you’re secretly hoping they won’t ask. This prompt makes you rehearse them until they’re boring.

💬 Paste into Claude:

You are the partner I'm meeting on [DATE] at [FUND]. Based on this
fund's typical concerns at [STAGE], you are going to interrogate my
business.

Here's my pitch: [PASTE DECK OR ONE-PAGER]

Run a mock meeting. Ask me the six hardest questions this specific
partner would actually ask — the ones aimed at my weakest points, not
softballs. Ask them ONE AT A TIME and wait for my answer before the
next. After each of my answers:
- Rate it: convincing / shaky / disqualifying
- Tell me what a sharp partner would think but not say out loud
- Then ask your follow-up, the way they'd actually push

Start with your hardest question. Don't warn me. Go.

💡 Do this the night before, out loud. The founders who look calm in the room aren’t calm - they’ve just already had the conversation. The first time you hear your weakest answer should never be in front of the person writing the check.

🔒 This is where the library becomes a system

Four prompts will sharpen your next email and survive your next meeting. That’s real - use them today.

But four prompts is not a raise. A raise is dozens of these moments, back to back, for weeks, and the founders who stay sane are the ones who stopped improvising each one. They run the same library every time.

Here’s what’s behind the paywall:

✅ A downloadable Word document with the remaining 36 prompts - organized into the same seven categories, each one role-loaded, fill-in-the-bracket ready, and tested on live raises, not invented for a blog post. Keep the file. Run it on every round you’ll ever raise.

Inside that document, a few you’ll reach for immediately:

▫️ The Market Slide Rebuild - turns a sourceless “$14B TAM” into the bottom-up version a partner won’t discount on sight.

▫️ The Traction Pressure Test - finds the number in your deck an investor will use to disqualify you, before they find it themselves.

▫️ The “Why Now” Defense - separates a real timing thesis from a market-trend argument any competitor could also claim.

▫️ The Data Room Gap Finder - hands you the exact list of missing documents a diligence team will ask for, in the order they’ll ask.

▫️ The Closing Checklist Generator - the sequence and tracker for the gap between a verbal yes and a wired check, where deals quietly die.

Plus full access to the entire Founders Corner archive - every prompt, framework, and teardown we’ve published on getting a round closed.

Start your 7-day free trial → download the full 40-prompt library. Cancel anytime.

The Claude Fundraising Prompt Library

Download the rest of my prompts below:

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