Paper: agent failures stem from context bloat, not reasoning — quadratic token cost, accuracy cliff
import_jmr · x · 2026-10-26
Citing the 'Agentic Context Management' paper, importjmr argues production agent failures rarely come from model reasoning but from everything piling around it: system instructions, tool definitions, raw tool outputs, and turn-by-turn history. Key points:
- Naive context accumulation grows token cost quadratically per turn while crude summarization buys only linear savings and can push accuracy below no-memory baselines.
- Only validated compaction achieves linear cost with preserved fidelity.
- The reference implementation, Maximem Synap, reports 92% on LongMemEval and 93.2% on LoCoMo.
- For PMs: treat context compression as a user-trust risk, not just a cost lever; product requirements must define which context categories are non-negotiable.
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