Why AI agents fail even when the model is good
An enterprise practitioner argues agent failures usually come from everything around the model: wrong context, missing information, bad tool descriptions, excessive permissions, unclear state, no evaluation, and no fallback. The emerging architecture looks less like 'LLM answers' and more like a pipeline: context, tools, validation, execution, observability, human escalation. The thread asks which failure mode has hurt practitioners most.