Can AI agents do more than write code?

David Cortés Fulla, Staff Engineer at Shopify, shows how pi-autoresearch lets agents run autonomous engineering experiments against any measurable metric.

The talk follows a real developer pain: slow CI and long feedback loops. Instead of manually trying one-off fixes, autoresearch gives an AI agent a metric — like build time, installspeed, test performance, bundle size, prompts, or skills — and lets it iterate: propose changes, run checks, keep improvements, reject failures, and repeat.

David explains how this approach helped Shopify speed up backend CI, generate multiple performance improvements, and automate the kind ofvaluable but boring optimization work thatengineers rarely prioritize over feature development.

Agents used to code like us, but faster. Autoresearch lets them run the experiments we never had time for.

👉 Subscribe to Itnig for more conversations about real business, startups and brands.

🎙️ Want to join the Itnig podcast or sponsor one of our episodes?

Appear on the podcast: https://tally.so/r/wo1Poe

Sponsor the podcast: https://tally.so/r/3EERLN

ABOUT ITNIG: 🐦 X - ⁠https://x.com/itnig

💡 LinkedIn -⁠ https://linkedin.com/company/itnig

📸 Instagram - ⁠https://instagram.com/itnig

💌 Newsletter - ⁠https://itnig.net/newsletter/⁠

🌐 Web -⁠ https://itnig.net/

LISTEN TO OUR PODCAST ON:

🔊 Spotify: ⁠http://bit.ly/itnigspotify⁠

🎙️ Apple Podcast: ⁠http://bit.ly/itnigapple

⁠00:00:00 Intro & welcome

00:00:05 David introduces himself & his work at Shopify

00:01:16 The problem: slow feedback loops in development

00:04:27 First experiment with pi — tackling build times

00:08:00 First results — 50% faster builds with parallel workers

00:09:24 Live demo: real project walkthrough

00:13:00 How pi researches, iterates and self-improves

00:16:04 Storing ideas for future iterations across model versions

00:18:30 The results go viral: trending on X, 1,000+ stars, 160+ forks

00:20:15 50+ successful internal experiments at Shopify

00:21:11 Beyond speed: running autonomous feature experiments in parallel

00:22:32 Q&A