Why AI agents fail even when the underlying model is good
Altadigit · reddit · 2026-10-09
Drawing from enterprise AI project experience, the author argues that agent failures usually stem not from model quality but surrounding engineering issues: wrong context, missing information, bad tool descriptions, excessive permissions, unclear state, no evaluation or fallback.
- Real agent architecture is not LLM → answer but Context → LLM → Tools → Validation → Execution → Observability → Human escalation
- Common failure modes: context errors, missing info, poor tool descriptions, over-permissioned tools, unclear state, absent evals and fallbacks
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