Before you run these exercises
Chapter 2 starts with a number you've probably heard — and shows why it's off by nearly 10x once you understand what's actually being measured. That's not a footnote. It's a framework for reading every stat you'll ever hear about who gets funded, including the ones investors will cite at you across the table.
The chapter also has an unflattering portrait of the people you're actually pitching — not the version from their firm websites. Reading it before you go into meetings will change how you prepare. The exercises below are built around what the chapter reveals; they'll work better once you have the full context.
The book does something most people never bother to do with a widely-cited funding statistic — it actually reads the footnotes. What it finds changes the whole picture. Run this exercise after you've read the chapter's analysis of what the number actually measures.
One of the sharpest observations in the chapter is about tacit knowledge — the things venture-backed founders learn by osmosis from their well-connected friends that nobody writes down anywhere. How a fundraising process actually runs. What specific clauses in a term sheet mean. What level a CEO actually has to perform at. What a winning pitch sounds like from the inside.
This is the gap AI can most directly close. Claude has no information gatekeeping incentive, no social judgment about your questions, and no reason to make you feel like you should already know this.
Here's a practical proxy for whether you know your space well enough to raise: could you organize a conference in it?
Not throw one — plan one. Who would speak? What would the panels be about? Which investors would sponsor it? Which founders who just raised would you put on stage? If you can populate that agenda with real names and real topics, you know your ecosystem. If you're staring at blank slots, that gap is going to show up in your pitch too — because investors will ask you about competitors, about market dynamics, about who else is working on this, and they'll feel it if you don't know.
This isn't just about impressing investors. Founders who know their ecosystem at this level make better product decisions, find better early customers, and build better networks. The conference is the test. Passing it makes you a better founder, not just a better fundraiser.
Claude can search the web in real time — just ask it to research your space directly.
Chapter 2 ends with something most founder books skip: an honest account of who you're actually pitching. Junior associates who can't say yes. Emerging managers who might not have the capital yet. Partners at dysfunctional firms where your champion might disappear next quarter.
Founders do almost no due diligence on investors before pitching them. That's backwards. Use Perplexity for this — you need cited, verifiable information, not synthesis. You want to know what's actually on the record.
The chapter makes a point that gets buried under the bias discussion: some of the most compelling credibility signals in a pitch come directly from a founder's specific vantage point on the problem. Not their demographic — their proximity to the problem, their domain knowledge, their lived experience of what's broken and why.
These signals work on every investor, not a subset. The founder who spent eight years in hospital administration pitching a healthcare workflow tool. The founder who ran a restaurant group for a decade pitching supply chain software. The founder who was the customer before they were the builder. That kind of credibility isn't demographic — it's earned, and it should be front and center with everyone you pitch.
Most founders undersell this. Use Claude to find it and sharpen it.
Chapter 2 maps out distinct investor types — each with fundamentally different objectives when they sit across from you. A pitch that works on one will fall flat with another. Read the chapter for the full taxonomy, then use this simulation to practice against each type.
The most useful preparation is to practice against the version of each type who is least naturally inclined to say yes to you. Use Claude to simulate that.
Most founders track their investor pipeline in a CRM or a spreadsheet — but they track the wrong things. They track "met with," "followed up," "waiting." What they should also track is what they know about the investor: their deal authority, what they've said publicly about the space, and which archetype they are.
Add a second tab to your landscape tracker (from Chapter 1) — or create a new sheet — for investor diligence. Claude can populate your initial research.
If you have Claude's Google Sheets integration connected (via MCP in Claude's settings), Claude can write this directly to a sheet for you. Just tell Claude the name of the sheet you want it to create or update. If you don't have it connected, ask Claude to format the output as a table you can paste in manually.
- Create a Google Sheet with columns: Investor Name, Firm, Role/Title, Deal Authority (GP/Partner/Principal/Associate), Space Thesis (what they've said publicly about your category), Archetype (based on Ch 2 taxonomy), Recent Deals, Red Flags, Warm Intro Path, Notes.
- For each investor on your list, run the Perplexity prompt from Exercise 04 above.
- Then ask Claude to format your research into a row you can paste directly (or write it to your sheet via MCP):
- Do this for every investor on your list before you start pitching. The act of filling it in will surface gaps in your research and force you to confront which investors you know almost nothing about — which is usually most of them.
The honest takeaway from Chapter 2 isn't discouraging — it's clarifying. The system has structural inequalities, bias is real, and the knowledge network advantage is significant. But almost none of that is fixed and permanent. The knowledge gap, in particular, is more closeable than it has ever been.
Before you move on, you should have three things: a clear-eyed view of what the funding data actually says about someone in your position (not the headline stat), an honest assessment of where your insider knowledge gaps are, and a research file on at least five investors you're planning to approach — with enough in it that you could describe their actual thesis and decision-making authority, not just their firm name.
And if you're still putting VCs on a pedestal: stop. They need a great deal as much as you need a check. The asymmetry is mostly in your head.