Coinbase 如何在千人工程团队中规模化 AI

Lenny's Newsletter2026年3月2日

介绍 Coinbase 在千人以上工程师组织中推进 AI 采用的方法，包括提升 PR 流程效率、将反馈转化为功能的自动化，以及通过数据分析识别关键用户。

Chintan Turakhia is Senior Director of Engineering at Coinbase, where he’s led the transformation of a 1,000-plus-engineer organization to embrace AI tools at scale. When tasked with rewriting Coinbase’s self-custody wallet into a consumer social app in just six to nine months, Chintan turned to AI as a force multiplier. His team has achieved remarkable efficiency gains, including reducing PR review times from 150 hours to just 15 hours, and dramatically compressing the cycle from user feedback to shipped features.

How to drive AI adoption in large, established engineering organizations
The “speed run” technique that got 100 engineers to push 70 PRs in 15 minutes
How to identify and replicate the behaviors of AI power users
Why engineering leaders must get hands-on with AI tools to drive adoption
How to build custom AI agents that integrate with your existing workflows
The metrics that actually matter when measuring AI’s impact on engineering velocity
How to compress the cycle from user feedback to shipped features

WorkOS—Make your app enterprise-ready today

Rovo—AI that knows your business

(00:00) Introduction to Chintan

(02:38) How Coinbase approached rewriting their app with AI assistance

(08:00) The importance of leadership conviction and hands-on demonstration

(10:30) The “PR speed run” technique that transformed team adoption

(17:57) Measuring success

(19:20) Demo: Real-time feedback-to-feature implementation

(23:14) Using Cursor to analyze AI adoption patterns

(33:15) Quick recap and appreciation

(36:00) Demo: Building a live feedback capture system using AI transcription

(40:50) Using custom Slack bots to automate engineering workflows