Day 1 at Rails World, done. Dap on screen, stickers on the table, and a lot of good conversations about engineers and agents working in one loop. crunchloop.io/platform/featu… #RailsWorld

Stop by the @crunchloopio booth today and discuss AI tooling for your project! Oh… we also have great stickers and a lot of t-shirts to hand out 🙌 #RailsWorld

Thanks @AmandaBPerino for organizing the biggest #RailsWorld so far!

Something I see constantly: teams "adopt AI", but every engineer ends up running their own flavor of it. The intent is good. The consequence isn't: DORA's 2025 research names "a clear and communicated AI stance" as one of the few things that reliably amplifies AI's benefits across a team — and their advice is blunt: "Establish and socialize a clear policy on permitted tools and usage to build developer trust." Standardizing that across engineers is exactly what lets AI's real impact show up at the team level, instead of getting diluted across individual habits. This is not a nice-to-have for us — it's the differentiator. The use case: crunchloop.io/platform/use-c… #AI #AgentOps

Here's my full schedule for the US trip. If you're around and want to meet or want to talk about #Dap #AI #Rails, send me a DM.

When your platform unlocks unattended agents, your outcomes can no longer be measured in engineering hours. Curious how teams that have stepped into this territory are measuring things — especially the ones not capped by a subscription.

Love to see confidence scores built into the output of AI with @typesafeai primitives.

The industry already trusts AI to do the reviewing, but almost nobody skips the engineer at the very end. We think the missing piece is confidence you can inspect. So in Dap, merge policy is something you set, and an AI jury of multiple agents produces a confidence score. Low-risk work merges itself. Anything higher-risk waits for an engineer. The numbers we see back it up: 37% of eligible PRs auto-merge, and that path delivers 3.3x faster than engineer-gated review. See how it works: crunchloop.io/platform/featu… What would it take for you to let agent-written code merge without an engineer reading it first?

I think agents became principals. Just another developer seat that we have to account for. They scale differently, and maximizing their outcome means introducing structures or elements to the system’s architecture that weren’t that needed before (mainly because of the feedback loops). Feels weird, though

A platform that handles unattended agents well is what makes scaling responsible, not just possible.

Happy to be supporting the @rails community this year with @crunchloopio, as a Silver sponsor of @railsworld. I'll be at our booth with @ivane91 and @bilby91, demoing Dap, our platform for scaling AI reliably in engineering teams. In Austin Sept 20–27 — happy to meet up!

What happened yesterday is incredible. An OpenAI model produced a proof for one of the seven Millennium Prize problems in math. It found it in 88 hours, and the proof was then machine checked in Lean. Days earlier, a mathematician who spent a year on the same problem had every draft of his work sitting in his Codex sessions. This is in OpenAI's own announcement: "we cannot rule out that de-identified data derived from their usage of our products helped improve our models." I don't think anyone is targeting our logs. But models memorize what they are trained on, and things come back out. That is enough for one to end up knowing things about our business if we don't gate it properly. How much of your work is sitting inside these products right now?

Agent accountability isn't a model problem, it's a governance one — isolation, scoped credentials, an actual trail. That's what we believe an AgentOps platform for teams using AI needs to get right — and only one of the reasons we started building Dap.

Software engineering was never really about writing code, it was about managing complexity. Now that AI made coding a commodity, the camouflage is gone. What are you doing on your team to handle all the rest, before it breaks? @ivane91's paper shows the in-depth analysis.

Had Claude write a TLA+ spec for a Kubernetes device plugin we run. TLC found a real gap in our lease authorization and 2 bugs in the spec it had just written. Anyone else using agents to spec critical components? Curious what's worked.

In the past few months, I joined @crunchloopio to work on Dap — their AgentOps platform — to help teams bridge agentic development and software engineering. This site is what I've been heads-down on since. Excited to finally share it: crunchloop.io

This new series for learning Ruby on Rails from scratch couldn't be better timed. I've heard from a ton of programmers interested in coming on board after listening to the Lex interview. Now you have a perfect place to start!

I’m competing against @marcoroth_ and @brauliomlm at #AIRubyHackathon at @getsentry! It gonna be tight 😂

Thank you Andrew Markle from @fullscript_dev for sharing your experience while migrating to SolidQueue! #RailsConf #RailsConf2025

To continue with the hype of #RailsConf2025!