FIELD NOTE / INSTAGRAM
Map each assumption to one fault.
The short film, the complete written thought, and the evidence behind it.
The Instagram edition will be linked here after its public post is verified.
Map each assumption to one fault.
Video caption
Map each assumption to one fault.
Availability, side effects and delay need separate readbacks.
Inject safely and inspect the authoritative record.
Make missing probes an UNVERIFIED result.
#EricFieldNotes
Full written post / accessible read
A distributed workflow can look healthy in one green CI run. To know what the design actually promises, separate three assumptions: the network may split, the broker may deliver twice, and the worker may need time to recover.
In an illustrative approval service, a partition can stall a decision, duplicate delivery can issue it twice, and slow recovery can miss a customer deadline. A model review that says 'robust to failures' is meaningless until it names which outcome and time bound survive.
For partition, isolate the disposable worker and observe whether unauthorized work proceeds. For duplicate delivery, replay one event ID and count committed effects. For recovery, restart at the worst seam and time until the accepted state. Keep expected thresholds beside actual values.
Run the relevant fault fixture whenever agents change the event path. Fail on a bad result and mark absent or stale evidence unverified. Do this because a static benchmark or model critique cannot certify your live topology, permissions and recovery budget.
#EricFieldNotes
Evidence and boundary
On-screen label: ILLUSTRATIVE QUEUE. Illustrative cases are not measured incidents. Research papers and vendor documents support the stated mechanism only within their studied or documented scope.
- SWE-bench Live paper (S22)
- SWE-bench Pro Verified paper (S23)