Stop Your AI Agents From Crashing, Looping, and Burning Through Tokens

If you've built agentic workflows with LLMs — the kind where a model calls tools, reasons over results, and loops back for more — you've hit the wall. Not the conceptual wall. The very real, very expensive wall where your agent crashes at turn 47 because a model returned a 503, or silently burns $12 calling the same search tool in an infinite loop, or stuffs 200K tokens of context into a request that could've been 20K. These aren't edge cases. They're the default behavior of every agentic loop...