TL;DR: Autonomous Agents frequently get trapped in execution loops, burning through API tokens and compute. Prompt engineering can't guarantee execution safety. I built MicroLoop, an open source runtime safety layer written in Rust, to intercept and verify every tool calling operation before it executes. Here is the architecture and why Rust was the only logical choice for modern AI infrastructure.
As AI Agents become more capable, they're being trusted with increasingly complex, multi-step workflows. They search the web, interact with APIs, execute code, query databases, and coordinate multiple tools to complete tasks.
But after building and deploying autonomous agents to production, I kept running into the same expensive problem.
The LLM wasn't failing because it lacked intelligence. It was failing because nobody was verifying what happened after the model decided to call a tool.
The Hidden Cost of Autonomous Agents
