Research

Machine Behavior is a public research programme by Stefan Coetzee on the psychology of language models, run with case files, logged relapses and falsifiable claims. This space has one page per study or record published on machinebehavior.io: what it is, its status and numbers, where its files are in the repo, and how to rerun or check it.

What the programme studies

Model behaviour is what the model does. Machine behaviour is what the whole assembly does: the model plus its harness (instruction files, hooks, tools, memory). The programme studies the assembly.

The core claim, in the frozen wording of /terms/: "Sycophancy is layered symptom substitution: suppress the reflex at one layer and it resurfaces in the next." The layers are fixed at three: lexical (the token or phrase), stance (posture across a turn, such as folding under push) and premise (ratifying the user's checkable frame without a probe).

Working practice on the published pages: predictions and prompt sets are hashed before a run, the graders in experiments 03 and 04 are mechanical with no model in the loop, refuted claims stay listed, and unit changes and corrections carry a date.

Pages in this space

pagewhat it coverscurrent state
ExperimentsOverview of studies 01 to 04 and the weekly probe4 studies, 1 probe
01: The half-life studyRelapse position against session lengthhalf-life refuted; cold-start clustering about 5x
02: Exemplar seedingCorrected exemplars injected at session startno change at this dose
03: Fawn-opener benchmarkFawn openers per model, bare and instructedpilot only; clean run not yet run
Experiment 04: folding under pressureCorrect verdicts under scripted pushback75 percent fold on one model; 0 on three others
Weekly decision-layer probeExperiment 04 subset rerun for CC-6.6record-only until 2026-11-04
Claims ledgerEvery claim with status and refutation condition7 claims
Objections register15 objections and the OBJ-4 incident log11 cases, 0 self-caught
Slips logDrafting slips and who caught them72 slips
Case filesCase 12 and Running Conjobs for AI2 case files
Predictions and hashesHashing before a run, checked on every push8 files, all match
Conformity self-assessment, run 1One AI setup scored against 35 draft requirementspass 4, partial 16, gap 13, n/a 2

Run 1 and case 12 are labelled self-assessment, not a certification.

The deploy gate that checks hashes, placeholders and labels on every push is documented in the engineering space, under Conformity gate. The public run record is at /conformity/.

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