Everyone is building AI coding agents. Almost nobody is engineering their loops. That's the moat. Andrew Ng said it plainly: "100% of my tasks are now done by AI agents. In 3-6 months, everyone will b
blog.sorv.dev13 min read
Julian Neagu
500+ AI tools shipped solo. Founder of VisionVix.
Great article. The biggest takeaway for me is that verification is becoming more important than generation. Most discussions around AI coding focus on model quality, but the Research โ Review โ Production pattern highlights how much value comes from structured validation rather than smarter prompts.
The production loop section was especially interesting because code analysis alone rarely reflects how systems behave in the real world. Looking forward to seeing the performance data and attack simulations from future posts.
Prompts are not the moat anymore.
The moat is the boring machinery around the agent: evals, retries, delegation, review, memory, and failure handling.
this framing of loops vs prompts makes sense, but in practice most teams will still end up with humans as the final evaluator for a long time once you add multiple agent layers, the system starts to feel less like automation and more like distributed tooling you still babysit the real question is whether the loop reduces cognitive load or just moves it into orchestration debugging