The Pragmatic Engineer

How AI is changing software engineering at Shopify with Farhan Thawar

02 Jul 2025

Audio

Description

Supported by Our Partners•⁠ WorkOS — The modern identity platform for B2B SaaS.•⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.• Sonar — Code quality and code security for ALL code. —What happens when a company goes all in on AI?At Shopify, engineers are expected to utilize AI tools, and they’ve been doing so for longer than most. Thanks to early access to models from GitHub Copilot, OpenAI, and Anthropic, the company has had a head start in figuring out what works.In this live episode from LDX3 in London, I spoke with Farhan Thawar, VP of Engineering, about how Shopify is building with AI across the entire stack. We cover the company’s internal LLM proxy, its policy of unlimited token usage, and how interns help push the boundaries of what’s possible.In this episode, we cover:• How Shopify works closely with AI labs• The story behind Shopify’s recent Code Red• How non-engineering teams are using Cursor for vibecoding• Tobi Lütke’s viral memo and Shopify’s expectations around AI• A look inside Shopify’s LLM proxy—used for privacy, token tracking, and more• Why Shopify places no limit on AI token spending • Why AI-first isn’t about reducing headcount—and why Shopify is hiring 1,000 interns• How Shopify’s engineering department operates and what’s changed since adopting AI tooling• Farhan’s advice for integrating AI into your workflow• And much more!—Timestamps(00:00) Intro(02:07) Shopify’s philosophy: “hire smart people and pair with them on problems”(06:22) How Shopify works with top AI labs (08:50) The recent Code Red at Shopify(10:47) How Shopify became early users of GitHub Copilot and their pivot to trying multiple tools(12:49) The surprising ways non-engineering teams at Shopify are using Cursor(14:53) Why you have to understand code to submit a PR at Shopify(16:42) AI tools' impact on SaaS (19:50) Tobi Lütke’s AI memo(21:46) Shopify’s LLM proxy and how they protect their privacy(23:00) How Shopify utilizes MCPs(26:59) Why AI tools aren’t the place to pinch pennies(30:02) Farhan’s projects and favorite AI tools(32:50) Why AI-first isn’t about freezing headcount and the value of hiring interns(36:20) How Shopify’s engineering department operates, including internal tools(40:31) Why Shopify added coding interviews for director-level and above hires(43:40) What has changed since Spotify added AI tooling (44:40) Farhan’s advice for implementing AI tools—The Pragmatic Engineer deepdives relevant for this episode:• How Shopify built its Live Globe for Black Friday• Inside Shopify's leveling split• Real-world engineering challenges: building Cursor• How Anthropic built Artifacts—See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

Transcription

This episode hasn't been transcribed yet

Help us prioritize this episode for transcription by upvoting it.

0 upvotes

🗳️ Sign in to Upvote

Popular episodes get transcribed faster

Other episodes from The Pragmatic Engineer

Transcribed and ready to explore now

Why Rust is different, with Alice Ryhl

20 May 2026

The Pragmatic Engineer

TypeScript, C# and Turbo Pascal with Anders Hejlsberg

13 May 2026

The Pragmatic Engineer

Designing Data-intensive Applications with Martin Kleppmann

22 Apr 2026

The Pragmatic Engineer

View all episodes from The Pragmatic Engineer

Comments

There are no comments yet.

Please log in to write the first comment.

Report any issue

The Pragmatic Engineer

How AI is changing software engineering at Shopify with Farhan Thawar

This episode hasn't been transcribed yet

Other episodes from The Pragmatic Engineer

Why Rust is different, with Alice Ryhl

TypeScript, C# and Turbo Pascal with Anders Hejlsberg

Designing Data-intensive Applications with Martin Kleppmann

Sign in to Audioscrape

Share this moment