10,000 Hours with AI: How We Made Our Team AI Native
summary
Remote-first analytics company of ~80 people across 30+ countries bets on tokenized assets and doubles down on AI by measuring usage: a Q1 target of 5,000 hours (≈4 hours/week) is hit and Q2 raises to 6,000 hours with averages climbing toward 10 hours. Tracking uses a one-minute weekly Slack form and a dashboard, reveals top tools (ChatGPT, Fireflies, GitHub Copilot, Cursor), shows 50–60% daily Copilot adoption among engineers, and credits workshops for lifting go‑to‑market uptake.
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chapters (8)
- 0:00Company context and vision
- 2:21Leveraging AI in product
- 5:01Organizational productivity
- 5:56Measuring AI adoption
- 7:44Tracking methods and data
- 9:15Essential AI toolset
- 10:07Engineering tool preferences
- 10:34Principles for AI culture
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