A friend pinged me at midnight asking whether we should build a bot to follow Serenity, the supply-chain researcher who blew up on X, in and out of his trades. My first reaction was that it was pointless: a strategy that actually compounds gets quietly levered up, not broadcast. But by the end of the night I'd changed my mind. There is something worth distilling here — it just isn't in his holdings, it's in the order he asks his questions. So we turned that process into an open-source skill.

Memory is the most cyclical business in tech — 40 years of up-10x, down-90%. This run has three genuinely structural differences. But 'this time is different' is the most expensive sentence in finance, so the bear case gets equal weight.

Your edge is your questions. What compounds over twenty-five years is not information — it is the capacity to ask better questions. The final workshop is the only one you do without an agent.

Most people use their AI agent in one mode. Investment agents play four distinct roles — analyst, red team, tutor, executor — and the way you frame your request determines which role you get.

A stock is a claim on future cash flows — not a ticker, not a chart. Three sources of return, five types of edge, and the vocabulary you need before you can judge an agent's output.

You do not need to read every line of a 10-K. You need to recognize patterns. Three financial statements as three lenses — business structure, fragility, and truth.

Every number in a DCF is a story choice. Agents compute flawlessly and default to consensus. Your job is the narrative — and knowing which assumption your valuation secretly depends on.

Risk is the probability of a loss you cannot afford — not standard deviation. LTCM optimized for volatility and was killed by correlation breakdown. Four real risks, and why only you can decide what you can afford to lose.

Most investors have beliefs, not theses. A written thesis with kill criteria is accountability against your own memory — because memory is self-serving, and beliefs mutate silently.

A single agent is a tool. A fleet with defined roles, cross-verification, and explicit handoffs is transformative. Five patterns cover 90% of investment workflows — but over-engineering the fleet is itself a form of procrastination.

Everything from chapters 1 through 8 collapses into one end-to-end workflow. Three companies, one decision. This chapter IS the workshop — expected time: 4 to 8 hours across multiple sittings.

Investment analysis used to require either a Bloomberg terminal or the ability to write code. AI agents removed both prerequisites. The barrier is now judgment — and that changes what an investing curriculum should teach.