Nov 23, 2025Pitching AI growth with confidence but no overreach is hard. By the end of this lesson, you’ll write investor‑grade, risk‑adjusted forecasts that use probabilities, cohorts, and sensitivities to defend valuation without promising outcomes. You’ll get a clear framework, sharp real‑world examples, and concise practice exercises—including multiple choice, fill‑in‑the‑blank, and error correction—to pressure‑test your language. The tone is surgical and compliant: auditable assumptions, scenario bands, and the exact phrasing investors expect.

Nov 23, 2025Tired of hand‑waving claims about “better AI” that don’t stand up in diligence? This lesson equips you to defend an AI moat with bounded, testable language—tying specific advantages to unit economics, competitive and regulatory context, and risk‑adjusted forecasts. You’ll find clear, step‑by‑step guidance, investor‑grade phrasing, sharp real‑world examples, and targeted exercises to pressure‑test your messaging. Finish with precise statements you can put in board decks and investor calls without overclaiming.

Nov 23, 2025Investors probing your TAM, SAM, and SOM will punish vague claims—so let’s make your wording audit‑proof. By the end, you’ll define tightly scoped markets for AI products, tie them to units and margins, and produce a bottom‑up, probability‑weighted SOM that defends valuation under diligence. Expect concise explanations, investor‑grade examples, and targeted exercises (MCQ, fill‑in, and error‑correction) to pressure‑test your language. Precision in; credibility out.