Greg Herlein

I’ve been teasing this for a while. Time to stop teasing. Meet Gorai — a modern, open-source robotics framework written in Go.

Most people think of a BrightSign player as the little box behind a screen that loops a video. That’s true right up until you realize the thing is a full ARM64 Linux computer with an NPU sitting idle most of the day. And you can run your own code on it. Natively. That’s what an extension is, and once you grok it, a whole world opens up.

Python won because it was easy. That was the whole trick. And now, in the age of agentic coding, that trick has stopped being an advantage — and quietly became a liability.

Last post I showed off the chainsaw I built myself — my build-autonomous loop, the padded room, the whole rig — and cut down a little tree with it: a Go CLI to boss around a smart plug. It was well worth building! I also think you should probably stop building your own. Yes, including me. Especially me.

People keep asking me how I actually work with Claude Code now. Not the “does AI coding work” question — I’ve beaten that horse into glue on this blog already — but the boring, practical, how-does-my-loop-actually-work question. So here it is. The whole rig. And fair warning: what I’m about to describe is a chainsaw, and most of the industry is still lined up at the axe-chopping contest.

I just spent a few days at a retreat on the future of software development. Small rooms. Unconference format. Some of the sharpest people in our industry - the kind of names that show up on the spines of the books on your shelf. I’m not going to tell you who was there or who said what. We ran the whole thing under Chatham House Rule: use what you learn, attribute none of it. This is my initial take-away.

Here’s a question I can’t stop chewing on: why is some software so damn good, and most of it so… not? Not buggy. Not slow. Just bad. Bad in a way you feel in your gut the moment you touch it. The answer isn’t tooling, or budget, or headcount. It’s taste. And I’m starting to think taste is the whole ballgame in the age of AI.

A couple weeks ago I wrote that your organization has to learn as fast as your best AI adopter. Externalize, combine, socialize, internalize. Run Nonaka’s spiral or get left behind. A bunch of you wrote back with the same question: okay, but where does the knowledge actually go?

Everyone is asking the wrong question. “How do we adopt AI agents?” “Which tool?” “What’s the right policy?” Wrong questions. The right question is: how does your team turn what one person learned on Tuesday into something everybody on the team uses by Friday?

Next week I get to watch one of my favorite things: see a room full of smart people handed a hard problem and watch them figure it out in real time. I’m headed to InfoComm to mentor, judge, and sit on a panel for an idea sprint about AI at the edge. And I could not be more excited.