StaffEng

Jonathan joins Alex and David to talk about what actually changes when agents get good enough to do the work. He walks through the 60-service monorepo migration that convinced him the ceiling had moved, why "raising ambition" is now a real coaching conversation with his team, and how Block is using linters and LLM-as-judge to keep GraphQL API design honest.

The conversation goes past the usual velocity story into the harder question: engineering is multiplayer, and most AI tooling is still single-player. Jonathan makes the case that the human touch points — design reviews, pairing, cross-functional feedback — are the part you have to deliberately protect, not the part you optimize away. Plus: adversarial code review with mixed models, why he'll let an agent write his code but not his voice, and the trap of low-hanging fruit that doesn't compound.

https://x.com/JWondrusch
https://x.com/davidnoelromas
https://x.com/voidfiles

Karla joins Alex and David from Sydney, where she's been building security-conscious AI workflows at Lorikeet--a customer service automation company where writing code by hand has officially become "artisanal."

https://www.lorikeetcx.ai/

https://x.com/tetrakazi

Dylan Vassallo is an engineering manager at OpenAI leading the People Innovation Labs team — an eng, product, and design team embedded within the People org, building AI-powered tools for recruiting, HR, internal comms, and the employee experience.

In this episode, Dylan talks about what it actually looks like to be an engineering team inside a frontier AI company, how non-engineers are becoming builders, and what the "graduation" process looks like when a prototype needs to become a production system.

Links & References

https://x.com/dylanvee
OpenAI Codex - https://openai.com/codex
Lattice - https://lattice.com — performance management platform mentioned
Linear - https://linear.app — used for team project tracking
Workday - https://workday.com — referenced as system of record

Hosts: Alex Kessinger & David Noël-Ramos 
Guest: Karynn Ikeda — Former Engineering Manager → AI Enablement Program Manager at Babylist @ktikeda
Karynn Ikeda shares the full arc of how Babylist adopted AI across its engineering organization — from a six-week Windsurf pilot on a single team, to company-wide Claude Code adoption and a bold initiative to onboard product managers and designers into the codebase. She discusses leadership buy-in, measuring developer sentiment over raw velocity metrics, the shift toward agent orchestration, and why the return of joy and creative empowerment may be the most important signal of all.
Links & References
Karynn Ikeda (@ktikeda)
Babylist  babylist.com
Shopify CEO Tobi Lütke's AI Memo (April 2025)  Original post on X
Anthropic Code Review for Claude Code  claude.com/blog/code-review
Claude Code  code.claude.com
Devin (AI coding agent by Cognition)  devin.ai
Cursor  cursor.com
Windsurf windsurf.com
Lovable (vibe coding tool)  lovable.dev
V0 (by Vercel)  v0.dev

Will Maier leads growth engineering at Stripe, where he's spent the last five years working across nearly every surface of the product. His background isn't CS — it's the history of science — and he's been through enough industry shifts (racking servers, the cloud transition, DevOps) to know when something really big is happening.
Find us now also on YouTube: @StaffEngPodcoast
In this season premiere of StaffEng, Will joins Alex and David to talk about what changed for him after November 2025, why he spent the holidays building a Lua distribution from his phone while doing laundry, and how he thinks about the organizational dynamics of AI adoption inside a large engineering org.
Topics covered:
Why Will hasn't opened an IDE since November — and what replaced it
The psychology of AI adoption: shame, hallucinated PRs, and "AI vegans"
Skills as the new packages: how improvised markdown files are changing how teams share leverage
Why measuring token usage (the wrong metric) surfaced the right insights
The case for making the incident report critic, not the incident report writer
What the cloud and DevOps transitions teach us about where AI is headed