2 posts tagged with "Agent"

If you've used Claude Code for complex tasks, you've probably experienced this:

You ask it to replace all fetch calls with axios, grab a coffee, come back — and it's done three files and stopped waiting for approval. Repeat seven or eight times, and your coffee is cold.

Or you ran /loop overnight to watch a PR, wake up to find it got stuck on a git merge conflict at 2 AM. The window has been open all night.

Or you launched three sub-agents to research independently — and ended up with three contradictory conclusions because none of them saw what the others were doing.

The root cause isn't that AI isn't smart enough. Claude Code is turn-based — each turn does one thing, then waits for you to decide the next step. To make it run continuously, decide autonomously, and work in parallel, you need orchestration mechanisms to bridge the gap.

Claude Code gives you five: /goal, /loop, sub-agent, Agent Teams, and Workflows.

Pick wrong, and you're not just wasting tokens — you're making things more complicated.

I've been working with Agent Skills for a while now. The most frustrating discovery: it's not that AI can't write code. It's that the code it writes only works on localhost, and it keeps ignoring the rules you set.

This article covers two things:

1. Making AI-generated code actually deployable — AI writes demo-quality code, full of security holes. The root cause: AI doesn't understand production environments.
2. Fixing "AI has Skills but won't use them" — activation rates can be as low as 20%. Here's how we pushed that to 84%.