4 posts
Traditional technical due diligence misses the AI-specific risks. Here's the checklist I developed for evaluating AI features in startup acquisitions and funding rounds — model provenance, data rights, eval evidence, and vendor lock-in.
Read →Investors are about to look under the hood. Here's the founder prep guide I wish every startup had before the DD call — what to fix, what to document, and what to stop worrying about.
Read →The specific patterns I see again and again when I open a seed-stage codebase for the first time — what they mean, why they happen, and how to fix them before they cost you a fundraise.
Read →What a real technical due diligence looks like from the inside — the eight categories I evaluate, the specific questions I ask, and the red flags that kill deals.
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