I'm thrilled by the positive feedback on my efforts to enhance our hiring process. Today, I finally wrote an article about it. What are your thoughts? Any areas you think I should delve into more deeply?

lesscodeworks.com/how-we-redefin…

@avithaldas0m+/year improving Todoist with some of the world's most skilled people. And we are probably much more proficient with AI than most vibe coders.

People greatly underestimate how hard it is to create truly great products. It's like food: many people can cook, but not at a Michelin level.

Zed meetup in Amsterdam is just around the corner on October 27! 👻 🎃 We're teaming up with @AITinkerers and @jetbrains for a night of tech talks and networking (with food and drinks of course). Plus Zed dev Gaauwe Rombouts will share how and why we built Zed's newest product, Delta.

Link to RSVP in thread.

I didn’t know miniatures can be so satisfying 😅

A pretty big change is that Pi now has MCP at the core. How is this even possible? What made us change our way? earendil.com/posts/you-said…

Preinstalled Omarchy machines are now for sale from The Linux Laptop 🤘 thelinuxlaptop.com/marketing-and-…

I love pi and after I saw @lucasmeijer love letter to pi I switched to html as output whenever I needed it.

Day 2 at @AIEMiami left me with one big takeaway: AI coding is no longer just about model quality. We’re moving from “LLMs that help write code” to “agent-driven software systems”.

Our products now need to work for agents too.

That means:
- APIs
- auth
- docs
- CLIs
- interfaces

All need to become more agent-friendly.

In many cases, your next user may not be a person clicking a dashboard.

Success with AI will not come from simply picking the best model. It will come from building the best workflow around the model.

Day 2 had a lot of great talks, but the common thread was clear: AI coding is becoming a systems problem, not just a model problem.

@aiDotEngineer Miami Day 1 had one clear message: The future of agents is boundaries, not authority.

Best ideas I heard:
- code > tool calls
- pipelines > mega-prompts
- skills/markdown > bloated abstractions
- agents should author artifacts, not touch prod
- secrets should never reach the model

Agents scale execution. They do not scale judgment. That’s now our job.

The product lesson was maybe the most important:
AI removed the engineering friction that used to kill bad ideas early. Teams can ship bad ideas much faster.

Execution scaled. Judgment didn’t.

Summary of Day 1:
Agents scale execution. They do not scale judgment. Which means the winning teams will be the ones that rebuild structure on purpose: pipelines, guardrails, review, persistence, and restraint.