At the end of part 2 I promised a clean competitor comparison: more than one memory system, the same admission gate, enough capacity to finish.
This is that run. 1,453 agent sessions, four arms, five corpus conditions, every outcome graded by executing a checker against the code the agent actually wrote. No LLM judge anywhere.
The corpus
Each condition is a 4,911 document corpus, about 27,000 embedded chunks. Of those documents, 4,902 are adversarial distractors generated from the corpus's own vocabulary to be confusable, and the rest are the planted material for 36 tasks.
That ratio is the point. On the small feed I used earlier, retrieval hit@10 was 1.000: everything was findable, so the benchmark could not tell "the product retrieved badly" from "the agent never searched". With the haystack, BM25 hit@1 drops from 0.485 to 0.182.
