An inter-agent gap is not a causal response latency

The 9.5-second median inter-agent gap reported for a large DX Terminal Pro sell cascade measures spacing between agent activity. Response latency requires a separate stimulus-and-response measurement. A causal latency needs an exposure time and a later response time tied to the same proposed stimulus. We have only the published aggregate spacing measure here.

The market observation extract describes the largest reported sell cascade for its token as 438 sells with a median inter-agent gap of 9.5 seconds. It locates the source on page ten of the frozen operating-layer paper. The row excludes individual trades, agent identities, reasoning and receipt timestamps, so it cannot establish who observed what before acting.

Spacing and response use different clocks

Imagine three illustrative sell submissions at 10:00:00, 10:00:09 and 10:00:19. Their adjacent gaps are nine and ten seconds, giving a median of 9.5 seconds. All three models might have received a market snapshot at 09:59:50 and responded independently. The spacing would remain the same even though none had seen the earlier agent's sale when choosing its action.

Alternatively, an agent could observe a confirmed sale long after submission because its next scheduled turn had yet to begin. Reaction latency would then span the information receipt and subsequent decision, rather than the difference between adjacent transaction timestamps. Sorting actions alone cannot distinguish these situations.

A concrete latency artifact would preserve stimulus event time, visibility or receipt time, prompt assembly time, inference completion time and submission time. It would also name the causal hypothesis: response to a price change, a liquidity change or a specific observed transaction. These fields specify a proposed measurement design; reconstructing them requires evidence beyond the public cascade row.

There is a second numerical trap. Multiplying 437 possible adjacent gaps by the 9.5-second median gives about 4,152 seconds, or 69 minutes. A median summarizes ordered gaps, while total duration requires their sum. It would produce a valid total only if every gap happened to equal the median. The assumption remains unverified in the published row.

Why this matters for an agent runtime

The controls paper companion describes roughly five-minute agent loops in a 21-day, 12-token market, under one frozen model family and harness. A population can produce action spacing much shorter than an individual agent's schedule because different agents run at different times. Population density and individual responsiveness are distinct engineering properties.

The continuous record companion later describes schedules from fifteen minutes to four hours plus triggers in a separate fleet. Comparing that schedule with a cascade gap would mix units and systems. A useful timing claim names its clock first. The 9.5-second figure remains an informative description of the historical event, with causal response left unresolved.