Developer shares real failures building an AI agent beyond the polished demo

A developer built an AI agent designed to monitor inputs, take action, or escalate decisions to a human — a setup more common than many realize. In real-world testing, the agent repeatedly reconsidered past decisions because conversation history and actual retrievable memory were never properly separated. A tool timeout combined with overlapping retry logic created an unintended near-infinite loop, fixed only by enforcing hard retry limits and a handoff mechanism. The agent also confidently attempted to call a non-existent internal function that fit naming conventions closely enough to seem valid, highlighting the risk of letting models select their own tools without schema validation. Ultimately, the developer found that most of the system's logic was hardcoded guardrails, with the model handling only one narrow judgment call — suggesting many so-called agent projects are better built as deterministic pipelines with AI applied selectively.