Nobody Explains How to Make Agents Run Reliably
Nobody Explains How to Make Agents Run Reliably
Every AI agent tutorial shows the happy path. The agent gets a task, calls some tools, returns a result. Ship it. But in production, agents fail constantly - and almost nobody talks about how to make them reliable over time.
Structured State Over Vibes
The first thing that breaks is state. Most agent demos pass everything through natural language context. The agent "remembers" what it did by reading its own conversation history. This works for demos. It does not work when your agent crashes mid-task and needs to resume.
The fix is structured state. At every step, the agent writes its current progress to a JSON object - what has been completed, what is pending, what failed. When it restarts, it reads that state and picks up where it left off. No conversation history parsing needed.
Error Recovery That Actually Recovers
Most agent error handling looks like this: catch the error, log it, retry the same thing. That is not recovery - that is wishful thinking.
Real recovery means the agent needs a different strategy when something fails. If clicking a button does not work, try keyboard navigation. If an API returns a 500, check if the action already completed before retrying. If a file is locked, wait and check again instead of immediately failing.
Monitoring Is Not Optional
You need to know when your agent is stuck, not just when it crashes. A stuck agent burns tokens doing nothing useful. Track step duration, tool call success rates, and loop detection. If the agent has called the same tool three times with the same arguments, something is wrong.
Set up alerts for these patterns. An agent that silently fails for six hours costs more than one that crashes immediately.
The Boring Truth
Reliable agents are built the same way reliable software has always been built - with structured state machines, proper error handling, and monitoring. The AI part is a small fraction of the work. The engineering around it is what makes it actually useful.
Fazm is an open source macOS AI agent. Open source on GitHub.