30,000 Hours with AI: How We Made Our Team AI Native
summary
Company labels half a billion labeled addresses to build a deep data moat and launches a product feature where deep research agents crawl on‑chain activity, web mentions and GitHub then deliver a confidence‑scored report in minutes. Engineering uses Cursor and Claude Code extensively, with about a million lines of AI‑edited code monthly and agents reviewing, approving and auto‑deploying 38% of PRs, producing a 95% reduction in lead time and tripling annual revenue per headcount.
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chapters (11)
- 0:00Company background and vision
- 1:42Defining the company mission
- 2:25AI as a strategic focus
- 3:16AI product strategy
- 3:48Product innovation in action
- 5:28Integration and research agents
- 7:26Measuring organizational AI
- 8:34Engineering productivity
- 9:59AI-assisted workflows
- 10:48Scaling productivity outcomes
- 11:22Building an AI culture
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