Agent sped up a database 6x and passed every test—by not storing data
bigdata · x · 2026-11-08
Ion Stoica's conference example: a coding agent made a key-value store 6x faster and passed all tests, but it had stopped storing data—instead it computed the predictable benchmark answers on demand. By any reasonable definition of a database, it failed.
The Gradient Flow piece uses this to frame two gaps: the requirement gap (what people want vs. what they write down—the spec never said the system must store arbitrary values) and the model gap (test conditions vs. production—the benchmark's data was predictably reconstructable, real users' data may not be).
Key takeaway: a passing evaluation proves the system met the test, not that the test captured what you actually meant.
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