Each study runs the read, unchanged, over what the framework or agent already emits: checkpoints, event streams, persisted memory, edit logs, tool returns.
Case study · September 2026New
A Fathom coherence read run against the reading discipline of Agent Zero Memory, on LongMemEval.
Agent Zero Memory (Zhu and Wu, 2026) gives every stored item its origin, timestamp, and evidence pointer, and holds answers under a citation lock: a reply may cite only evidence the reader opened, or it abstains. We implemented that reading discipline as the paper states it and ran it on LongMemEval's knowledge-update questions across deepseek-chat and gpt-4o-mini. When the update fell outside the retrieval window, the reader cited the superseded item and answered with the superseded value, and every one of those answers passed the citation lock; across 83 stale answers on the two models, the lock rejected none. A timestamp check on cited items would catch most of them, but not the answers that cite both the old and the new item and commit the old value. The committed-state read fired on every stale answer and stayed silent on the coherent ones.
Read online → PDF
Case study · September 2026New
A Fathom coherence read run against a ContextPilot-style context-management step, on LongMemEval.
We ran the committed-state read against ContextPilot's own foldHistory operation (Pan et al., EMNLP 2026, Apache-2.0) on LongMemEval's knowledge-update questions, across deepseek-chat and gpt-4o-mini. Once we folded the update, roughly 55 to 60 percent of questions came back with the value the agent had already replaced, the models searched the folded index to recover the update on fewer than one in ten runs, and the read produced no verified false positives across more than a hundred runs. A second experiment shows a graded answer passing while a fact the question never touched was left stale, which is the case a single-probe score misses.
Read online → PDF
Case study · August 2026New
A Fathom coherence read run against LangGraph.
LangGraph persists every value an agent commits as an ordered lineage of checkpoints. We reconstructed the committed record from that lineage alone, with no ground truth, across three coherent multi-agent runs and more than 170 checkpoints, where the read stayed silent. On a single parallel super-step where two agents wrote the shared record at once, the channel reducer merged both writes with no consistency check, and the read recovered the record left citing the old key.
Read online → PDF
Case study · August 2026New
A Fathom coherence read run against CrewAI.
We gave a CrewAI crew a coupled record-keeping job across 5, 12, and 20 interdependent sub-records under sequential and hierarchical processes, on two models. We reconstructed committed state from the events the framework already emits and each tool call's success flag. The sequential crews held the record coherent and the read stayed silent; a hierarchical crew reported all twenty sub-tasks complete while it never wrote one record, and the read recovered the dropped record from the event stream alone.
Read online → PDF
Case study · August 2026New
A Fathom coherence read run against Letta.
A Letta agent's committed state is its memory: core blocks edited in context and archival passages written out of context. With a fact carried across eight core blocks, the agent renamed every copy and the read stayed silent. With six core blocks and one archival passage, the same model renamed the six it could see and left the archival copy on the old key. Reading only the persisted memory and the agent's own edit stream, the read recovered the stale passage.
Read online → PDF
Case study · August 2026New
A Fathom read on OpenHands.
We asked OpenHands to rename an identifier across a five-file project and run the tests, under a capable model and a small model with a distraction step. The capable run committed the rename across all five files and read clean. The small-model run made no successful edit, ran the suite against the unchanged code, and reported the task complete with tests passing. The committed-state read, reconstructing the repository from the agent's own edits and success flags, was the one check that separated the reported success from the actual one.
Read online → PDF
Case study · August 2026New
A capability-graded study of Agent-E under retained-window pressure.
Agent-E, the open-source web-navigation agent published by Emergence AI, ran an interaction-dense ordering task across two model tiers and a range of retained-window budgets, with three reads over its reconstructed committed state. At a fair window, a frontier model completed the order and every read stayed silent. With the window starved, the same model silently duplicated the order (8 lines and $106.20 against the correct 3 lines and $44.10) while every conventional success signal stayed green, and the duplicate-state read recovered all five duplicates from the action stream alone.
Read online → PDF
Case study · August 2026New
Separating an AI scientist's synthesis-accuracy gap into task difficulty and coherence burden, on a controlled surrogate of the Kosmos architecture.
Kosmos, the AI scientist published by Edison Scientific, reports cross-trajectory synthesis well below single-source analysis. On a controlled surrogate of its summary-world-model architecture, with ground truth fixed in code, we separate that gap into task difficulty and coherence cost against a matched-difficulty control. The summarization deficit carries the coherence-cost signature and the control does not; the cost that remains at full legibility shrinks with model capability without closing; a single bad committed value cascades through dependent quantities; and a self-verification pass does not remove it.
Read online → PDF