Descriptions:
In this episode of How I AI, host Claire Vo interviews Chintan Turakhia, Senior Director of Engineering at Coinbase, about how the company successfully rolled out AI coding tools — primarily Cursor — across more than 1,000 engineers, achieving genuine adoption rather than the checkbox-and-abandon pattern common at large organizations.
Turakhia describes the conditions that made the initiative work: a leadership mandate combined with hands-on technical credibility (engineers need to see leaders actually use the tools, not just decree their use), a concrete product forcing function (a full rewrite of a self-custody wallet into a consumer social app in 6–9 months with a small team competing against multi-thousand-person incumbents), and obsessive focus on making adoption stick rather than tracking surface-level metrics.
The interview includes a live Cursor demo where Turakhia runs a cohort analysis on engineering team usage data, segmenting users into agent-heavy, tab-heavy, and balanced profiles — and using a multi-agent pipeline (one agent to enrich a CSV, a second to generate an HTML dashboard from the output) to do the analysis itself. He also discusses how MCP integrations are turning Cursor into a general-purpose work operating system beyond coding. For engineering leaders evaluating AI tooling at scale, this conversation offers one of the most grounded and specific case studies available, anchored in a real product deadline with measurable outcomes.
📺 Source: How I AI · Published March 02, 2026
🏷️ Format: Interview
