# I Built an AI Agent Team That Fixes Its Own Mistakes — Here’s the Full, Tested Code > Source: > Published: 2026-07-12 14:30:09+00:00 Member-only story # I Built an AI Agent Team That Fixes Its Own Mistakes — Here’s the Full, Tested Code ## Most agent tutorials show you the happy path. This one shows you what happens when an agent fails — and how to make the system heal itself instead of crashing. All codes given in thsi article are available on Github : [Self-Healing-Agent-] Every agentic AI demo looks the same: a clean prompt goes in, a perfect tool call comes out, everybody claps. Then you deploy it, a worker agent hits an edge case it wasn’t built for, throws an exception, and your “autonomous” system falls over in front of a customer. The pattern that separates toy agents from production agents isn’t a bigger model or a longer prompt. It’s **what happens after something fails.** In this article we build **SelfHeal**, a small but genuinely production-shaped multi-agent system that implements the **Supervisor-Worker pattern with automatic error recovery**: when a worker agent fails, the Supervisor doesn’t crash or return a raw stack trace — it catches the failure, reroutes the task to a fallback agent with a different strategy, and logs exactly how it healed itself. Every line of code in this article was written and executed in a sandboxed…