How Coinbase Scaled AI to 1,000+ Engineers | Chintan Turakhia

Why It Matters

Large, established engineering organizations can materially accelerate product development by embedding AI into core workflows—making adoption a competitive necessity rather than optional experimentation. Demonstrable, leadership-led usage is crucial to overcome skepticism and realize productivity gains at enterprise scale.

Summary

Coinbase engineering leader Chintan Turakhia says the company has successfully scaled AI across a 1,000+ engineer organization to boost velocity and rebuild a major consumer-facing app under an aggressive six- to nine-month timeline. Adoption succeeded after leadership became hands-on with tools, demonstrated practical use cases, and drove daily experimentation rather than mandate-only rollouts. Early tooling flopped for some engineers, so the team focused on making AI “stick” by integrating it into everyday coding, debugging, and operational workflows. The shift also changes leadership expectations toward fewer meetings and more coding and tool-driven mentoring.

Original Description

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.

What you’ll learn:

1. How to drive AI adoption in large, established engineering organizations

2. The “speed run” technique that got 100 engineers to push 70 PRs in 15 minutes

3. How to identify and replicate the behaviors of AI power users

4. Why engineering leaders must get hands-on with AI tools to drive adoption

5. How to build custom AI agents that integrate with your existing workflows

6. The metrics that actually matter when measuring AI’s impact on engineering velocity

7. How to compress the cycle from user feedback to shipped features

Brought to you by:

WorkOS—Make your app enterprise-ready today: https://workos.com?utm_source=lennys_howiai&utm_medium=podcast&utm_campaign=q22025

Rovo—AI that knows your business: https://rovo.com/

In this episode, we cover:

(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

(47:10) Advice for driving AI adoption within your organization

(50:00) Personal use case: AI for wine selection based on taste preferences

(55:23) Lightning round and final thoughts

Detailed workflow walkthroughs from this episode:

• How I AI: Chintan Turakhia’s Playbook for AI Adoption at Coinbase: https://www.chatprd.ai/how-i-ai/playbook-for-ai-engineering-adoption-at-coinbase

• Use ChatGPT to Become Your Own Personal Wine Sommelier: https://www.chatprd.ai/how-i-ai/workflows/use-chatgpt-to-become-your-own-personal-wine-sommelier

• Build an Automated User Feedback to Pull Request Pipeline: https://www.chatprd.ai/how-i-ai/workflows/build-an-automated-user-feedback-to-pull-request-pipeline

• Create a Data-Driven AI Adoption Playbook Using Cursor: https://www.chatprd.ai/how-i-ai/workflows/create-a-data-driven-ai-adoption-playbook-using-cursor

Tools referenced:

• Cursor: https://cursor.sh/

• Linear: https://linear.app/

• Slack: https://slack.com/

• ChatGPT: https://chat.openai.com/

• Claude: https://claude.ai/

• GitHub Copilot: https://github.com/features/copilot

Other references:

• Coinbase: https://www.coinbase.com/

• React Native: https://reactnative.dev/

• How custom GPTs can make you a better manager | Hilary Gridley (Head of Core Product at Whoop): https://www.lennysnewsletter.com/p/how-custom-gpts-can-make-you-a-better-manager

Where to find Chintan Turakhia:

LinkedIn: https://www.linkedin.com/in/chintanturakhia/

X: https://x.com/chintanturakhia

Base App (formerly Coinbase Wallet): https://base.app/

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

_Production and marketing by https://penname.co/._

_For inquiries about sponsoring the podcast, email [e-mail]._