Why many agents fail because they cannot tell whether they are making progress
orvi2014 · reddit · 2026-07-25
A Reddit post argues that most agent failures are not intelligence problems but progress detection problems.
The core claim is that many agents can plan, use tools, and produce coherent intermediate steps, yet still fail because the system lacks a reliable external signal that says whether the agent is actually moving toward the goal.
Typical failure pattern:
- the agent keeps calling tools
- arguments change only slightly each time
- context grows
- self-evaluation stays optimistic
- real progress remains flat
The post suggests more useful safeguards are structural and external:
- hard step/token budgets
- explicit progress predicates
- semantic distance between successive states
- tool-call fingerprinting to detect near-cycles
- separate critic models that judge progress only
The larger argument is architectural: if the model is both the actor and the sole judge of success, better models may just produce more confident and more expensive failures.
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