For the past few months I’ve been hacking on Jarvis in the evenings: a small Go agent that gives an LLM a handful of local tools (read files, run shell, spawn sub-agents, that kind of thing). I’m not trying to ship the next OpenClaw clone. I just wanted to see how the pieces fit together when you build them yourself.
Please Stop Force-Feeding AI FOMO to Others!
Not too long ago, I wrote a post about the AI Hype Burnout and how it was harmful to the whole industry.
I thought that was the end of it, but it seems like the FOMO is starting to kick in. Many people are seeing that AI is finally delivering real value and are “inviting” everyone to quickly jump on the bandwagon.
Attending the First Italian Forum on Artificial Intelligence for Industry.
Hear me out… AI Skills should include tools. 🛠️
So you’ve decided to try AI-assisted development. Let me save you some frustration.
Talk about perfect timing! 🤯
How to visualize working with AI Agents 👇
if (3 days == 2 weeks) {🤯}
“AI started out being the assistant, but you were still in control … But now it’s switching around. The AI is doing the work, right? And you’re supervising what it’s doing.”
I took some time to test the BMAD agents within the GitHub Mission Control interface. It’s a very promising concept, and I’m a fan of the direction, but it feels like it will need a few more iterations to be truly seamless.
Weekend project: Test the BMAD Method on a real-world problem.
“I was highly skeptical, but now I’m a believer.”
That’s a phrase I find myself constantly repeating in recent conversations about LLMs and AI and it turns out, I’m far from alone! I’ve heard/read variations of this statement multiple times in the past few weeks.