IBM's Martin Keen walks through context engineering—the practice of managing what information receive—and identifies four major failure modes that degrade performance over time. Context rot occurs as models become less reliable; context poisoning happens when bad information is treated as fact; context distraction occurs when long histories overwhelm reasoning; and context confusion arises when too many tools competing for attention reduce accuracy.
Keen argues that adding more context often backfires. Instead, effective AI agents benefit from four fixes: validating information quality, compacting data representation, curating what's truly necessary, and pruning outdated or irrelevant material. The core insight is counterintuitive—AI agents often perform better when given less, but higher-quality context.
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