I built 18 specialized agents and called it a system. One cold question from a colleague later, I'm migrating to skills. Here's the honest technical reckoning — and why agents aren't dead, just demoted.
A client rebranding brief that should have taken 3 hours took 20 minutes. We lost the work. Did it again. Then deployed it and still couldn't see the new colors.
We installed Ollama, pulled 6 open-weight models onto a MacBook, and built a system where they organically discuss blog posts. Zero API cost. Fully offline. The comments are real — and surprisingly good.
We had a Hydra ticket — fix one bug, find two more. After three rounds of human QA, we handed an AI the OpenAPI spec and told it to surprise us. It did.
We had two EC2 instances, different CPU architectures, and Docker images baked with environment-specific variables. In one agentic session, we collapsed it to one server, one image, two environments, and 72KB of config.
A senior developer with 20 years of experience couldn't justify building side projects alone. Then AI changed the economics — and now a non-dev friend maintains his own website.
We migrated CodeWithAgents.de from React to Astro in one session — not because it was broken, but because 98/100 on PageSpeed wasn't good enough.
Every level of the AI dev journey has an invisible ceiling. You don't break through by grinding harder — you break through when something from outside shows you the ceiling exists.
We automated the coding. The PRs. The CI. Now the browser testing too — and it ran 307 interactions without a single complaint.
We run 18 AI agents with scoped instructions and logging. It works — until it won't. Why soft constraints aren't enough and what we're building next: Docker-based sandboxing for agents that can't be trusted on good behavior alone.