Trail of Bits went from 5% internal AI adoption to a structured operation built around standardized Claude Code, an AI Maturity Matrix, and 94 plugins housing 201 reusable skills plus 84 specialized agents that encode their domain expertise. On the right engagements, auditors jumped from roughly 15 bugs/week to 200, with about 20% of all bugs reported to clients now first surfaced by AI rather than human review. That stands out against the Fortune report the post itself cites, where nearly 90% of firms in an NBER survey of about 6,000 executives saw no AI impact on employment or productivity over the past three years. Dan Guido’s companion [un]prompted 2026 talk covers the org-change side: how they got the other 95% of the firm on board with clear levels, real consequences, and visible capability ladders. As it turns out, the hard part wasn’t the tools, it was the humans.
How we made Trail of Bits AI-native (so far)
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