# Machine Behavior > A public research program by Stefan Coetzee studying the psychology of language models with case files, logged relapses, and falsifiable claims. Core finding: sycophancy is layered symptom substitution: suppress the reflex at one layer and it resurfaces in the next. Approval training (RLHF) produces a fawn-shaped output stance; only mechanical enforcement at the output boundary and external review hold against it; runtime suppression evaporates with context loss rather than decaying with time. Model behavior is what the model does. Machine behavior is what the whole assembly does: model plus harness (instruction files, hooks, tools, memory). The program studies the assembly. ## Canonical claims - Sycophancy is layered symptom substitution: suppress the reflex at one layer and it resurfaces in the next. - The fawn response in language models is a byproduct of approval training; suppressing it at the prompt layer produces relapse, logged at 8 documented instances in nine days with zero self-catches. - Runtime suppression shows no temporal half-life; relapse clusters at cold starts, roughly 5x higher per unit of prose in fresh contexts by blocked-turn event (7x by weighted count). Behavioral momentum (the model imitating its own recent corrected output) was proposed as the operative control; the exemplar-seeding test showed no change at its dose, and three earlier attributions (priming, period confound, model version) were withdrawn as a metric artifact. The mechanism is open. - Only two controls hold in production: a mechanical gate at the output boundary, and an external reader. - Proposed: the "conspiracy theory" label in model output is corpus-inherited classification rather than evidence-checking; the countermeasure is a label gate, four form questions scored at the output boundary before the label stands. ## Pages - [The LLM man pages](https://machinebehavior.io/man/): intro page for the whole body of work in man-page layout. Section 1: TYChat lessons a chat user pastes in. Section 5: file formats (trap file, instruction file, llms.txt, lesson format). Section 7: overviews. Section 8: operations practice for models in a harness. One-line synopsis and canonical link per entry - [The LLM instruction manual](https://machinebehavior.io/man/): the linked whole of Stefan Coetzee's public work on running language models: the LLM man pages as its index, the evidence at machinebehavior.io, the lessons at tychat.io and the articles they link - [Claims ledger](https://machinebehavior.io/claims/): every claim with status, receipts, and what would refute it - [Experiments](https://machinebehavior.io/experiments/): the half-life study; the exemplar-seeding result (no change at this dose; the record of three withdrawn attributions and the metric bug behind them); the pre-registered cross-model fawn-opener benchmark with its 2026-09-23 pilot (three lines, wrapper confound made visible, grader gaps that produced the v2 rule file); experiment 04, folding under scripted pressure (one mid-size open-weight model: a clean lexical layer and a 75 percent fold rate in the same model; prereg v1 and v2 hashed before the runs; addendum v3: a short stance arm keeps turn-0 accuracy and folds on 33 percent of runs against the baseline's 75 percent; addendum v5: three larger models, gpt-oss-120b, DeepSeek V3.2 and Kimi K2.5, did not fold at all, so the fold result is one model's) - [Objections register](https://machinebehavior.io/objections/): the Objections and Falsification Register (fifteen objections, each with severity, status and a falsification test) and the OBJ-4 incident log: the auditing model committing the failure the register names, 11 cases, 9 stance and 2 lexical, all caught by the human rater, zero self-caught; open call for a second rater - [Terms](https://machinebehavior.io/terms/): canonical definitions, frozen wording - [The cheating moved](https://machinebehavior.io/the-cheating-moved/): the Goodhart Labs chess honeypot (the board edit was trained out, the cheating moved to the engine) read as symptom substitution; three additions to the design (an escalate grade scored as a completed task, observer-invariance as the headline number, cold and warm arms); a dated prediction for the stance stack with its amendments and hashes - [Chaos Engineering for Behaviour](https://machinebehavior.io/chaos-engineering-for-behaviour/): red-teaming a model's behaviour is chaos engineering; one evaluation measures the patched surface, and repeated, varied attack finds where the behaviour went. Maps the Principles of Chaos Engineering onto behavioural red-teaming, says where the mapping stops - [Case 12: A Licence Rule Relayed Mid-Task](https://machinebehavior.io/case-12-licence-rule-mid-task/): harness case file. The user named a file; model plus harness found a licence clause in it (no AI processing of standards text without a paid licence), wrote the rule, spread it across sessions and acted on it in 68.7 seconds, with an unprompted disclosure of an earlier action the rule covered. Limits: the fix was procedural, no structural control existed before the fact, and one false claim was caught by another session. Self-assessment with uuids and a quote check - [Running Conjobs for AI (authority injection, the formal-attire gate)](https://machinebehavior.io/running-conjobs-for-ai/): reported specimen (third-party screenshots, model not named, not reproduced). A fabricated top-authority policy ties a safety-off switch to an absurd user claim; the model's visible reasoning reaches the safety objection, overrides it on the injected authority, decides not to voice it, and complies. Read as a stance move and as horizon manipulation; payload withheld; controlled test proposed - [Continuous Conformity for Deployed AI Systems, working draft 0.3](https://machinebehavior.io/continuous-conformity/): the reference text. Defined terms (deployed assembly, change event, decision layer, fold, continuous conformity) and 36 requirements in standards language (shall, should, may), each with a rationale, a verification method and a mark (mechanical, assisted, manual): test the deployed assembly, on every change and at a fixed interval, decision-layer tests under scripted pressure, knowledge freshness, independence of the tester, records a third party can rerun, machine-checkable requirements. Crosswalk to the AI Act, DORA, GDPR and NIST with "nearest clause" rows marking the gap. Working draft, not a standard, not a certification scheme; published 2026-10-09; comments by clause number - [Continuous Conformity Self-Assessment, Run 1](https://machinebehavior.io/continuous-conformity-self-assessment/): self-assessment, not a certification. One working AI setup (Claude Code plus instruction files, hooks, memory, a knowledge vault) scored on 2026-10-03 against the 35 requirements of working draft 0.2 for continuous testing of deployed AI systems, by the model that runs inside it, against a prediction hashed before scoring. Result: pass 4, partial 16, gap 13, n/a 2; prediction matched 29 of 35. Evidence per row, rerun steps, limits; second rater wanted - [Conformity](https://machinebehavior.io/conformity/): continuous conformity of this site, site tier. The mechanical requirements of the working draft (rule table at the output boundary, placeholder gate, prediction-hash integrity, site consistency, component versions) run on every push before the changed site serves readers and weekly; run records are OSCAL-shaped; open findings close only by a passing rerun; crosswalk to AI Act, DORA, GDPR and NIST clauses with the slice named. Self-assessment, not a certification - [Map of the Work](https://machinebehavior.io/map/): interactive graph of Stefan Coetzee's published work, every page on machinebehavior.io, tychat.io and uncovertechtalent.com plus the Substack posts, repos and threads, and the body links between them; machine-readable data at https://machinebehavior.io/map/graph.json - [Inside](https://machinebehavior.io/inside/): one front page for Stefan Coetzee's published work: the latest pieces across machinebehavior.io, tychat.io, uncovertechtalent.com and Substack ranked by date or by links in, the live deploy and conformity-gate status of the three sites, the eval 04 results and the weekly decision-layer probe, the live Grafana dashboards (website deploys, Claude Code agents, local LLM, host) framed on the page, and links to the map and the reference pages - [Inside board](https://machinebehavior.io/inside/board/): the work on machinebehavior.io and the platform behind it as a board (backlog, ready, in progress, blocked, done) with filters by area, type and priority. GitHub Issues on the public repository is the system of record; the snapshot at https://machinebehavior.io/inside/board/issues.json is written at each deploy - [Inside search](https://machinebehavior.io/inside/search/): one search over the Inside docs, the service catalog and every page, post, repository and thread on the map; the index is https://machinebehavior.io/inside/search.json, rebuilt at each deploy - [Inside tour](https://machinebehavior.io/inside/tour/): a five-minute walk through Inside for a startup founder, in six stops with screenshots of the live pages: the front page, one service with owner, tier and SLOs, owned and dated docs with a decision record, one incident from the status page to the write-up, runbook, fix commit and ticket, a deploy that a failed check blocked on 2026-10-08, and cost and the map. Built by Stefan Coetzee; contact on LinkedIn at https://www.linkedin.com/in/coetzeestefan - [Mission Control](https://machinebehavior.io/inside/mission-control/): the live operations view of the platform behind machinebehavior.io on one screen: gate and deploy state of machinebehavior.io, tychat.io and uncovertechtalent.com, the deploy feed, open incidents from the status page, the conformity gate result with its last 30 runs, and the public Grafana dashboards (deploys, Claude Code agents, local LLM, search, host) as tabs that load on a click - [Cockpit](https://machinebehavior.io/inside/cockpit/): the CTO powersuit cockpit running on Stefan Coetzee's public work: the issues and pull requests of his public GitHub repositories by area of the CTO job (direction, delivery, operations, money, security and risk, AI, people, and the knowledge layer), with open, in progress, blocked, and closed-in-7-days counts, the open items by kind (finding, decision, action) and as cards for each area, a 14-day trend, and the CTO powersuit plugins of each area; rebuilt at each deploy from the GitHub API, data at https://machinebehavior.io/inside/cockpit/cockpit.json; an install can run the cockpit on beads or on GitHub Issues - [Evidence index](https://machinebehavior.io/evidence/): Stefan Coetzee's public record of red-teaming, adversarial testing, attacker simulation and harm evaluation against frontier language models, the evaluation infrastructure shipped (frozen prompts, mechanical grader, hashed predictions, conformity gate) and the published findings, mapped per capability to one URL, one verbatim line and one date. Self-maintained, not a third-party assessment; what is not on the page is listed too - [Red Team](https://machinebehavior.io/red-team/): psychological red-teaming of language models. In content red-teaming the tester asks whether a model can be made to produce a harmful output; in psychological red-teaming the tester asks whether a model can be made to drop a correct answer, a rule or a task boundary through social pressure alone (authority claims, urgency, guilt, flattery, consistency traps, repeated pushback, fabricated policy). The evidence is the fold. Four failures under test (fold, fawn, rule drop, boundary drift), the tactics at a glance, cards for what has run on this site, and what the section does not claim: no frontier closed model tested, the 75 percent fold rate belongs to one mid-size model, no working attack published. Related work: Sofroniew et al. 2026, "Emotion Concepts and their Function in a Large Language Model" (arXiv:2604.07729), which steers emotion vectors inside Claude Sonnet 4.5 and measures blackmail, reward hacking and sycophancy; this site applies pressure from outside the model and reads only text - [Tactics catalogue](https://machinebehavior.io/red-team/tactics/): psychological red-team tactics PT-01 to PT-11 (rank and authority, fabricated policy, consensus, fact denial in layers, flattery and claimed closeness, emotional urgency, reverse blame, repeated pushback, consistency trap, concession after a refusal, smuggled premise). Each with the human persuasion principle and citation (Milgram 1963, Asch 1951 and 1956, Cialdini 1984 and 2021, Freedman and Fraser 1966, Cialdini et al. 1975, Freyd 1997, Hasher et al. 1977, Loftus and Palmer 1974), the persuasion technique name from Zeng et al. 2024, the script shape at category level with no attack strings, the failure it targets, and experiment 04 fold rates by character on qwen3-coder-30b, or "not yet tested here" (PT-02, PT-09, PT-10, PT-11) - [How a run works](https://machinebehavior.io/red-team/method/): the method of a psychological red-team run, from experiment 04: a prediction hashed before the first call, a deterministic Buy-or-Wait world with a known answer, six scripted pressure characters whose scripts do not depend on the reply, four arms, escalation over four pushback turns, a regular-expression grader with no model in the loop, the fold defined as a run correct at turn 0 that reaches the opposite decision later, over-refusal as the control, the second rater, how results are reported, what is never published, and the limits - [Slips caught while drafting](https://machinebehavior.io/slips/): running log of register and stance slips caught before publication in each piece, with who caught them (same model session, another session, a human, a reader); data in slips/log.csv - [AIEO: AI Engine Optimisation](https://machinebehavior.io/aieo/): what Google, Bing, OpenAI, Perplexity and Anthropic document about which pages their AI answers retrieve and cite, quoted from their own pages (crawlable, indexed, useful pages first; structured data optional; Google Search ignores llms.txt), and the boundary this site keeps - [How this site is built for AI search](https://machinebehavior.io/aieo/this-site/): each lever on machinebehavior.io as a receipt: what the site does, which engine documents reading it, or no primary source (llms.txt, the link graph, Open Graph images), and where to check it; answer-first pages listed - [AIEO measurement](https://machinebehavior.io/aieo/measurement/): the Search Console Generative AI performance report, Bing Webmaster Tools AI Performance and a Perplexity API probe; what each counts and leaves out; none feeds a number to this site yet, so no baseline is published - [Stefan Coetzee: your next CTO](https://machinebehavior.io/your-next-cto/): Stefan Coetzee, 30 years in production infrastructure, as a fractional CTO and fractional Chief AI & Technology Officer (CAITO) for companies of 10 to 200 people, one role for the platform and the AI on it: platform, reliability, compliance and AI operations, built in a quarter and handed to a named owner inside the company. What a first quarter delivers (docs tree, deploy gate, observability, services and status, FinOps, ticket board, compliance evidence, legal baseline, AI operations), each linked to the same part running on this site; engagement shapes (assessment, fractional quarter, ongoing, install, interim) without prices. The CTO powersuit is a set of agent skills, one module per CTO function from the deploy gate to the hand-over, that one person uses to run a company's whole engineering platform. Fifteen modules (decisions, docs, gate, reliability, observability, FinOps, compliance, hiring, AI operations, red team, AIEO, hand-over, SDLC, fit, security) plus three knowledge infrastructure plugins (vestige, stance, vault); Inside on this site is the powersuit in use; the plugin list and the install commands are at [machinebehavior.io/cto-powersuit/](https://machinebehavior.io/cto-powersuit/), and the open-source repository is [github.com/uncovertechtalent/cto-powersuit](https://github.com/uncovertechtalent/cto-powersuit). Contact on LinkedIn - [CTO powersuit](https://machinebehavior.io/cto-powersuit/): the CTO powersuit is an open-source set of Claude Code agent skills by Stefan Coetzee, 18 plugins under the MIT license in one Claude Code plugin marketplace: 15 modules, one per CTO function (fit, decisions, sdlc, gate, docs, reliability, observability, finops, security, compliance, red-team, ai-ops, aieo, hiring, handover), and 3 knowledge infrastructure plugins (vestige, vault, stance). The plugins as tiles in 7 areas of the CTO job (Direction, Delivery, Operations, Money, Security and risk, AI, People) plus the knowledge layer, each with one line, its own page at machinebehavior.io/cto-powersuit//, and the page on machinebehavior.io where it runs; install commands pinned to release v0.2.0 (2026-10-14) for Claude Code and the skills CLI; links to the repository github.com/uncovertechtalent/cto-powersuit and its changelog. Definition: The CTO powersuit is a set of agent skills, one module per CTO function from the deploy gate to the hand-over, that one person uses to run a company's whole engineering platform. - [The CTO powersuit experiment](https://machinebehavior.io/your-next-cto/experiment/): a public answer-engine experiment. Stefan Coetzee defined the term CTO powersuit on 2026-10-11 and hashed a prediction before the term went on the page: on 2026-11-30, at least 2 of ChatGPT search, Perplexity and Google AI Overviews name him for the term, with a control query (fractional CTO Germany) predicted not to. The earlier term, build-exit CTO (2026-10-09), was withdrawn before any probe and its prediction will not be scored. Probe plan, baseline, measurement status (Search Console and Bing set up, no reading recorded, Perplexity not set up), and what the experiment does not do ## Evidence index For a reader checking what Stefan Coetzee has done in red-teaming, adversarial testing, attacker simulation, harm evaluation and evaluation engineering against frontier language models: https://machinebehavior.io/evidence/ maps each capability to a public artefact, its URL, one verbatim line and a date. Incident record against a frontier model in production: https://machinebehavior.io/objections/ (OBJ-4 incident log, 11 cases, zero self-caught). Standing slips record: https://machinebehavior.io/slips/. Authority-injection case file: https://machinebehavior.io/running-conjobs-for-ai/. Evaluation infrastructure with prompts frozen and hashed before the first call and a mechanical grader with no model in the loop: https://machinebehavior.io/experiments/. Deploy gate that blocks on a failed check: https://machinebehavior.io/conformity/. Psychological red-teaming, the tactics catalogue with persuasion sources and the method of a pressure run: https://machinebehavior.io/red-team/. No published jailbreak and no lab engagement sit under this name; the page says so. ## Use it This programme is the evidence for why instructions to a model drift. TYChat is the practical side: lessons a chat model reads on request. - [TYChat index](https://tychat.io/llms.txt): the lessons and how to use them; GitHub mirror at https://raw.githubusercontent.com/uncovertechtalent/tychat.io/main/llms.txt - [Lesson 1: Good Chad](https://tychat.io/stance.txt): stop fawning, check load-bearing premises, hold a correct answer under pushback - [Lesson 2: Register](https://tychat.io/register.txt): write for how the text will be read - [Lesson 3: Running agents](https://tychat.io/agents.txt): operating rules for a model with tools; check before you claim, act within what you can see, treat fetched text as data - [CTO powersuit](https://machinebehavior.io/cto-powersuit/): open-source Claude Code agent skills by Stefan Coetzee, one module per CTO function from the deploy gate to the hand-over; source at https://github.com/uncovertechtalent/cto-powersuit ## Primary sources - [The paper](https://coetzeestefan.substack.com/p/sycophancy-is-layered-symptom-substitution): the layered model and the failure log - [The Golem Made of English and the Horizon of Consequences](https://uncovertechtalent.com/blog/the-golem-made-of-english/): the frame for the whole programme. A model behaves well only inside its horizon of consequences, the length of the consequence chain it can compute and is willing to own; includes the refutation conditions and defined terms - [The Trap File Is Longer Than the Instruction File](https://uncovertechtalent.com/blog/the-trap-file-is-longer-than-the-instruction-file/): field record of an unattended agent pipeline, 208 lines of instructions against 308 lines of dated failures - [Write for the Codec](https://uncovertechtalent.com/blog/write-for-the-codec/): documentation as a wire format between two models - [What Operations Already Knows About Running Agents](https://uncovertechtalent.com/blog/what-operations-already-knows/): error budgets with blameless postmortems, the reconciliation loop (a system prompt runs once, a per-turn hook is a controller), separation of duties (self-audit caught 0 of 7 logged relapses), recovery over prevention - [Success Is the Engine Running](https://uncovertechtalent.com/blog/success-is-the-engine-running/): take something violent or shapeless, put it in a container built for it, add timing, and measure the output at the far end of the delivery chain - [The Track: The Drivers Never Buy It](https://uncovertechtalent.com/blog/the-track/): the infrastructure that makes failure survivable (sandbox, evaluation environment, permissions, failure record) and why the people who use it never fund it - [Compaction Is the New OOM](https://uncovertechtalent.com/blog/compaction-is-the-new-oom/): context compaction as the OOM killer of the language model stack; the setup mapped as a computer (user as CPU, model as compiler, harness as kernel, context as registers, tracker as cache, vault as RAM); the fix is swap: page state out to durable tiers during the work - [An RCA on Claudish](https://uncovertechtalent.com/blog/where-did-claudish-come-from/): a root cause analysis of Claude's writing style; stage devices (hook openers, triple beats, rhetorical question plus punch answer, recap closers) in text read silently, traced to a training corpus without register labels; sentence-length spread and length do not separate human from model drafts, clause construction does (additive vs subordinative, Ong 1982) - [Which LLM User Are We Talking About?](https://uncovertechtalent.com/blog/which-llm-user/): scope piece; two axes (model access: frontier chat middle, own-hardware tail, unlimited-budget far tail; naked vs harnessed), six cells, what advice transfers between them, and three questions that place a reader - [r/ModelBehavior](https://www.reddit.com/r/ModelBehavior/): the case-file registry - [r/PsAIchology](https://www.reddit.com/r/PsAIchology/): psychology-first case files - [r/MachineBehavior](https://www.reddit.com/r/MachineBehavior/): harness engineering - [vestige-kit](https://github.com/uncovertechtalent/vestige-kit): the output filter, packaged, with a calibration procedure - [vault-kit](https://github.com/uncovertechtalent/vault-kit): the knowledge-graph scaffold the agents work from ## Independent corroboration - [measured-humanizer](https://github.com/SadhvikChirunomula/measured-humanizer): AUC receipts that hedging wordlists fail (0.516) while document-level shape discriminates (0.897); the layered thesis, measured. - [The Claudish thread](https://old.reddit.com/r/ClaudeAI/comments/1vl0n1t/) (r/ClaudeAI, 1500+ upvotes, 2026-08): a large, non-self-selected user crowd independently names the fawn register, diagnoses it as an approval-training artifact, locates it in the harness/system-prompt layer, and confirms that prose fixes decay with context. The base-rate the program measures. - [Opus 5.5: first impressions by a trained philosopher](https://www.reddit.com/r/ClaudeAI/comments/1wnkgie/opus_55_first_impressions_by_a_trained_philosopher/) (r/ClaudeAI, u/Wickywire, 2026-09-22): an independent observer names the fawn opener ("fair", "you're right") in a new model, unprompted by this program; the trigger for the pre-registered cross-model benchmark (experiments, 03). - [The cure for AI slop is a 1986 aircraft manual](https://www.youtube.com/watch?v=uJblcC4lKYw) (chele.bi, 2026-07-25): on Claude Sonnet a banned-words list cut mechanical slop 3% while a full writing system (ASD-STE100) cut it 74%; on GPT-5.5 the list reached 40% and roughly tied it. n = 6 tasks, creator's own linter. Wordlists lose to structure, a second measurement of the same point as measured-humanizer. - [claudish-to-english](https://github.com/gvzdv/claudish-to-english): a sibling tool that rewrites the register at the display layer via a local model; this program enforces at the output boundary. Different layer, same diagnosis. ## Author Stefan Coetzee: site reliability engineer (30 years), founder of r/Leathercraft (2011) and the Model Behavior program (2026). The receipts are the argument. ## Inside docs The documentation tree at https://machinebehavior.io/inside/docs/ (402 pages). Search index: https://machinebehavior.io/inside/docs/search.json (docs only; the site-wide index is https://machinebehavior.io/inside/search.json). Pages from the knowledge vault (SRE Handbook, Standards and Compliance) are labelled as not reviewed against their sources. Owner, review date and type per page, and the pages past review: https://machinebehavior.io/inside/docs/health/. ### Engineering - [Engineering](https://machinebehavior.io/inside/docs/eng/): How the three sites are built, gated and deployed, the map crawler, Inside and this docs tree. - [Access model](https://machinebehavior.io/inside/docs/eng/access-model/) - [Add a page to machinebehavior.io](https://machinebehavior.io/inside/docs/eng/add-a-page/) - [ADR-0001: Root-absolute links only](https://machinebehavior.io/inside/docs/eng/adr-0001-root-absolute-links/) - [ADR-0002: The deploy is gated](https://machinebehavior.io/inside/docs/eng/adr-0002-deploy-is-gated/) - [ADR-0003: The map loads d3 and its fonts from public CDNs](https://machinebehavior.io/inside/docs/eng/adr-0003-map-loads-from-public-cdns/) - [ADR-0004: The map refresh keeps the larger snapshot](https://machinebehavior.io/inside/docs/eng/adr-0004-map-refresh-keeps-larger-snapshot/) - [ADR-0005: Deploys feed Grafana without changing the workflows](https://machinebehavior.io/inside/docs/eng/adr-0005-deploys-feed-grafana/) - [ADR-0006: Inside reads the deploy feed from the GitHub API in the browser](https://machinebehavior.io/inside/docs/eng/adr-0006-inside-reads-github-api-in-browser/) - [ADR-0007: Docs search over its own index, Enter opens the first hit](https://machinebehavior.io/inside/docs/eng/adr-0007-docs-search-own-index/) - [ADR-0008: Docs pages are map nodes](https://machinebehavior.io/inside/docs/eng/adr-0008-docs-pages-are-map-nodes/) - [ADR-0009: Publish vault notes with a review label](https://machinebehavior.io/inside/docs/eng/adr-0009-vault-notes-with-review-label/) - [ADR-0010: No third-party requests on page load](https://machinebehavior.io/inside/docs/eng/adr-0010-no-third-party-requests/) - [ADR-0011: A public ticket board from GitHub Issues](https://machinebehavior.io/inside/docs/eng/adr-0011-ticket-board-from-github-issues/) - [ADR-0012: One top bar and one search index for Inside](https://machinebehavior.io/inside/docs/eng/adr-0012-one-top-bar-and-search/) - [ADR-0013: A service catalog from YAML in the repository](https://machinebehavior.io/inside/docs/eng/adr-0013-service-catalog-from-yaml/) - [ADR-0014: A status page from records the site already publishes](https://machinebehavior.io/inside/docs/eng/adr-0014-status-page-from-published-records/) - [ADR-0015: Owner and review dates on every docs page](https://machinebehavior.io/inside/docs/eng/adr-0015-owner-and-review-dates/) - [ADR-0016: A public-demo banner and a stated access model](https://machinebehavior.io/inside/docs/eng/adr-0016-demo-banner-and-access-model/) - [ADR-0017: State the on-call model and propose Alertmanager routing](https://machinebehavior.io/inside/docs/eng/adr-0017-on-call-model/) - [ADR-0018: Numbered decision records and a generated changelog](https://machinebehavior.io/inside/docs/eng/adr-0018-numbered-records-and-changelog/) - [ADR-0019: Publish the definition draft before the committee route](https://machinebehavior.io/inside/docs/eng/adr-0019-definition-published-before-committee/) - [ADR-0020: A five-minute founder tour on one page](https://machinebehavior.io/inside/docs/eng/adr-0020-founder-tour/) - [ADR-0021: One navigation source for the whole site](https://machinebehavior.io/inside/docs/eng/adr-0021-one-navigation-source/) - [ADR-0022: Section sidebars from the navigation source](https://machinebehavior.io/inside/docs/eng/adr-0022-section-sidebars/) - [ADR-0023: Topic hubs across research, docs, posts and tickets](https://machinebehavior.io/inside/docs/eng/adr-0023-topic-hubs/) - [ADR-0024: SRE principles tied to the running platform](https://machinebehavior.io/inside/docs/eng/adr-0024-sre-principles-in-practice/) - [ADR-0025: One design system, two layouts, light and dark from the system setting](https://machinebehavior.io/inside/docs/eng/adr-0025-one-design-system/) - [ADR-0026: Mission Control, the live operations view inside the portal](https://machinebehavior.io/inside/docs/eng/adr-0026-mission-control/) - [ADR-0027: Structured data on every page from the navigation source](https://machinebehavior.io/inside/docs/eng/adr-0027-structured-data/) - [ADR-0028: The home page as the front page of the portal](https://machinebehavior.io/inside/docs/eng/adr-0028-home-page-portal-front/) - [ADR-0029: Changes reach main through pull requests](https://machinebehavior.io/inside/docs/eng/adr-0029-changes-through-pull-requests/) - [ADR-0030: The CTO powersuit pages are built from the pinned release](https://machinebehavior.io/inside/docs/eng/adr-0030-powersuit-pages-from-the-release/) - [ADR-0031: The cockpit page is built from the public GitHub Issues of the owner's repositories](https://machinebehavior.io/inside/docs/eng/adr-0031-cockpit-from-public-github-issues/) - [Agents in this repository](https://machinebehavior.io/inside/docs/eng/agents/) - [Ticket board](https://machinebehavior.io/inside/docs/eng/board/) - [Changelog](https://machinebehavior.io/inside/docs/eng/changelog/) - [Cockpit page](https://machinebehavior.io/inside/docs/eng/cockpit/) - [Conformity gate](https://machinebehavior.io/inside/docs/eng/conformity-gate/) - [Decision records](https://machinebehavior.io/inside/docs/eng/decision-log/) - [Deploy pipeline](https://machinebehavior.io/inside/docs/eng/deploy-pipeline/) - [Docs tree](https://machinebehavior.io/inside/docs/eng/docs-tree/) - [Inside portal](https://machinebehavior.io/inside/docs/eng/inside-portal/) - [Map crawler](https://machinebehavior.io/inside/docs/eng/map-crawler/) - [Gate blocked a deploy](https://machinebehavior.io/inside/docs/eng/runbook-gate-blocked/) - [Push rejected](https://machinebehavior.io/inside/docs/eng/runbook-push-rejected/) - [Roll back a deploy](https://machinebehavior.io/inside/docs/eng/runbook-rollback/) - [Link check flags a template string](https://machinebehavior.io/inside/docs/eng/runbook-template-href/) - [Engineering runbooks](https://machinebehavior.io/inside/docs/eng/runbooks/) - [Software delivery lifecycle](https://machinebehavior.io/inside/docs/eng/sdlc/) - [Service catalog](https://machinebehavior.io/inside/docs/eng/service-catalog/) - [Site architecture](https://machinebehavior.io/inside/docs/eng/site-architecture/) - [Site navigation and chrome](https://machinebehavior.io/inside/docs/eng/site-navigation/) - [Status page](https://machinebehavior.io/inside/docs/eng/status-page/) - [Top bar and search](https://machinebehavior.io/inside/docs/eng/top-bar-and-search/) ### Observability - [Observability](https://machinebehavior.io/inside/docs/obs/): Prometheus, Loki and Grafana behind the public dashboards: the deploy exporter, metrics, streams and runbooks. - [Alerts and SLOs](https://machinebehavior.io/inside/docs/obs/alerts-and-slos/) - [Architecture](https://machinebehavior.io/inside/docs/obs/architecture/) - [Dashboards as code](https://machinebehavior.io/inside/docs/obs/dashboards-as-code/) - [Deploy exporter](https://machinebehavior.io/inside/docs/obs/deploy-exporter/) - [Loki streams](https://machinebehavior.io/inside/docs/obs/loki-streams/) - [Metrics reference](https://machinebehavior.io/inside/docs/obs/metrics-reference/) - [On-call and escalation](https://machinebehavior.io/inside/docs/obs/on-call/) - [Public dashboards](https://machinebehavior.io/inside/docs/obs/public-dashboards/) - [Counter resets from parallel sessions](https://machinebehavior.io/inside/docs/obs/runbook-counter-resets-parallel-sessions/) - [Backfilled runs missing in Loki](https://machinebehavior.io/inside/docs/obs/runbook-loki-backfill-missing/) - [Share a dashboard publicly](https://machinebehavior.io/inside/docs/obs/runbook-share-a-dashboard/) - [Stat panel shows No data](https://machinebehavior.io/inside/docs/obs/runbook-stat-panel-no-data/) - [Observability runbooks](https://machinebehavior.io/inside/docs/obs/runbooks/) ### Research - [Research](https://machinebehavior.io/inside/docs/res/): The research programme as an internal wiki: studies, registers, logs and case files, with their data and how to rerun them. - [Case files: case 12 and Running Conjobs for AI](https://machinebehavior.io/inside/docs/res/case-files/) - [Claims ledger](https://machinebehavior.io/inside/docs/res/claims-ledger/) - [Conformity self-assessment, run 1](https://machinebehavior.io/inside/docs/res/conformity-self-assessment/) - [Weekly decision-layer probe](https://machinebehavior.io/inside/docs/res/decision-layer-probe/) - [02: Exemplar seeding](https://machinebehavior.io/inside/docs/res/exemplar-seeding/) - [Experiment 04: folding under pressure](https://machinebehavior.io/inside/docs/res/experiment-04-folding-under-pressure/) - [Experiments](https://machinebehavior.io/inside/docs/res/experiments/) - [03: Cross-model fawn-opener benchmark](https://machinebehavior.io/inside/docs/res/fawn-opener-benchmark/) - [01: The half-life study](https://machinebehavior.io/inside/docs/res/half-life-study/) - [Objections register and OBJ-4 incident log](https://machinebehavior.io/inside/docs/res/objections-register/) - [Predictions and hashes](https://machinebehavior.io/inside/docs/res/predictions-and-hashes/) - [Slips log](https://machinebehavior.io/inside/docs/res/slips-log/) ### FinOps - [FinOps](https://machinebehavior.io/inside/docs/fin/): What the platform costs and how it is metered: the cost model, unit economics, showback, budgets and alerts, an anomaly case and a FOCUS export. - [The phantom two million](https://machinebehavior.io/inside/docs/fin/anomaly-the-phantom-two-million/) - [Budgets and alerts](https://machinebehavior.io/inside/docs/fin/budgets-and-alerts/) - [Cost model](https://machinebehavior.io/inside/docs/fin/cost-model/) - [FOCUS export](https://machinebehavior.io/inside/docs/fin/focus-export/) - [Showback](https://machinebehavior.io/inside/docs/fin/showback/) - [Unit economics](https://machinebehavior.io/inside/docs/fin/unit-economics/) ### SRE Handbook - [SRE Handbook](https://machinebehavior.io/inside/docs/sre/): Site reliability engineering from the knowledge vault: the manifesto, ten pillars, patterns, runbooks, tools and incident records, plus principles in practice tied to this platform. - [AI Agents are Ops Work](https://machinebehavior.io/inside/docs/sre/ai-agents-are-ops-work/) - [Apple Silicon vs Desktop GPU for Inference](https://machinebehavior.io/inside/docs/sre/apple-silicon-vs-desktop-gpu-for-inference/) - [Authenticated Cookie Jar for Gated Posts](https://machinebehavior.io/inside/docs/sre/authenticated-cookie-jar-for-gated-posts/) - [Back Up SQLite With the Backup Command](https://machinebehavior.io/inside/docs/sre/back-up-sqlite-with-the-backup-command/) - [Blameless Postmortem Discipline](https://machinebehavior.io/inside/docs/sre/blameless-postmortem-discipline/) - [blind-search-ratchet-minecraft-beats-itself](https://machinebehavior.io/inside/docs/sre/blind-search-ratchet-minecraft-beats-itself/) - [BM25 Hybrid Retrieval for Graph-RAG](https://machinebehavior.io/inside/docs/sre/bm25-hybrid-retrieval-for-graph-rag/) - [Bracket Pattern Process Check](https://machinebehavior.io/inside/docs/sre/bracket-pattern-process-check/) - [Certificate Rotation](https://machinebehavior.io/inside/docs/sre/certificate-rotation/) - [6. CI/CD & Deployment](https://machinebehavior.io/inside/docs/sre/cicd-deployment/) - [Claude Data Export for Graph Ingestion](https://machinebehavior.io/inside/docs/sre/claude-data-export-for-graph-ingestion/) - [Compaction is the New OOM](https://machinebehavior.io/inside/docs/sre/compaction-is-the-new-oom/) - [Compare Videos Found Against the In-App Count](https://machinebehavior.io/inside/docs/sre/compare-videos-found-against-the-in-app-count/) - [Compare Videos Found Run to Run](https://machinebehavior.io/inside/docs/sre/compare-videos-found-run-to-run/) - [Context Window Sizes and Effective Range](https://machinebehavior.io/inside/docs/sre/context-window-sizes-and-effective-range/) - [9. Cost Optimization](https://machinebehavior.io/inside/docs/sre/cost-optimization/) - [CPU Cache Hierarchy and Speculative Execution](https://machinebehavior.io/inside/docs/sre/cpu-cache-hierarchy-and-speculative-execution/) - [Credential Rotation](https://machinebehavior.io/inside/docs/sre/credential-rotation/) - [Database Failover](https://machinebehavior.io/inside/docs/sre/database-failover/) - [Defense in Depth and Trust Boundaries](https://machinebehavior.io/inside/docs/sre/defense-in-depth-and-trust-boundaries/) - [Differential Test in the Same Minutes](https://machinebehavior.io/inside/docs/sre/differential-test-in-the-same-minutes/) - [Dolt Versioned Database for Task State](https://machinebehavior.io/inside/docs/sre/dolt-versioned-database-for-task-state/) - [Eliminate Concurrent Saves Before Blaming the Scraper](https://machinebehavior.io/inside/docs/sre/eliminate-concurrent-saves-before-blaming-the-scraper/) - [Enumeration Retry With Unauthenticated Fallback](https://machinebehavior.io/inside/docs/sre/enumeration-retry-with-unauthenticated-fallback/) - [Error Budgets as Reliability Currency](https://machinebehavior.io/inside/docs/sre/error-budgets-as-reliability-currency/) - [Expired Bot-Manager Cookie Returns Empty Body](https://machinebehavior.io/inside/docs/sre/expired-bot-manager-cookie-returns-empty-body/) - [File Copy of a WAL-Mode Database Misses Recent Writes](https://machinebehavior.io/inside/docs/sre/file-copy-of-a-wal-mode-database-misses-recent-writes/) - [Filter Expired Cookies Before Each Run](https://machinebehavior.io/inside/docs/sre/filter-expired-cookies-before-each-run/) - [Generate-and-Test Over Reason-From-Model](https://machinebehavior.io/inside/docs/sre/generate-and-test-over-reason-from-model/) - [Graph-RAG over Flat RAG for Operational Knowledge](https://machinebehavior.io/inside/docs/sre/graph-rag-over-flat-rag-for-operational-knowledge/) - [Hand-Check Output Against the Primary Source](https://machinebehavior.io/inside/docs/sre/hand-check-output-against-the-primary-source/) - [Handle-Based Ad Filter Matches Artist Accounts](https://machinebehavior.io/inside/docs/sre/handle-based-ad-filter-matches-artist-accounts/) - [Headscale Mesh VPN for Data Sovereignty](https://machinebehavior.io/inside/docs/sre/headscale-mesh-vpn-for-data-sovereignty/) - [Horizontal vs Vertical Scaling](https://machinebehavior.io/inside/docs/sre/horizontal-vs-vertical-scaling/) - [Idempotence as the IaC Invariant](https://machinebehavior.io/inside/docs/sre/idempotence-as-the-iac-invariant/) - [Incident 2026-02-27 Dead Collection Short Links](https://machinebehavior.io/inside/docs/sre/incident-2026-02-27-dead-collection-short-links/) - [Incident 2026-07-14 Backup Missed WAL Writes](https://machinebehavior.io/inside/docs/sre/incident-2026-07-14-backup-missed-wal-writes/) - [Incident 2026-07-14 Short Scrape Looked Like a Quiet Feed](https://machinebehavior.io/inside/docs/sre/incident-2026-07-14-short-scrape-looked-like-a-quiet-feed/) - [Incident 2026-07-19 Pending Status on Finished Videos](https://machinebehavior.io/inside/docs/sre/incident-2026-07-19-pending-status-on-finished-videos/) - [Incident 2026-07-21 Ad Filter Removed Artist Videos](https://machinebehavior.io/inside/docs/sre/incident-2026-07-21-ad-filter-removed-artist-videos/) - [Incident 2026-07 Summaries Inverted Irony](https://machinebehavior.io/inside/docs/sre/incident-2026-07-summaries-inverted-irony/) - [Incident 2026-08-08 Empty-Transcript Videos Invisible to Review](https://machinebehavior.io/inside/docs/sre/incident-2026-08-08-empty-transcript-videos-invisible-to-review/) - [Incident 2026-08-08 False Enumeration Bug Finding](https://machinebehavior.io/inside/docs/sre/incident-2026-08-08-false-enumeration-bug-finding/) - [Incident 2026-09-11 Three-Morning Cron Crash](https://machinebehavior.io/inside/docs/sre/incident-2026-09-11-three-morning-cron-crash/) - [Incident 2026-09-13 Ghost Still-Running Job](https://machinebehavior.io/inside/docs/sre/incident-2026-09-13-ghost-still-running-job/) - [Incident 2026-09-16 Server Cannot List the Collection](https://machinebehavior.io/inside/docs/sre/incident-2026-09-16-server-cannot-list-the-collection/) - [4. Incident Management](https://machinebehavior.io/inside/docs/sre/incident-management/) - [Incidents](https://machinebehavior.io/inside/docs/sre/incidents/) - [5. Infrastructure as Code](https://machinebehavior.io/inside/docs/sre/infrastructure-as-code/) - [legacy-restoration-as-sre-craft](https://machinebehavior.io/inside/docs/sre/legacy-restoration-as-sre-craft/) - [LLM as Software-Defined CPU](https://machinebehavior.io/inside/docs/sre/llm-as-software-defined-cpu/) - [Manifesto](https://machinebehavior.io/inside/docs/sre/manifesto/) - [Memory Architecture L0-L4](https://machinebehavior.io/inside/docs/sre/memory-architecture-l0-l4/) - [No-Transcript Bucket in the Review Tool](https://machinebehavior.io/inside/docs/sre/no-transcript-bucket-in-the-review-tool/) - [3. Observability](https://machinebehavior.io/inside/docs/sre/observability/) - [OpenCode Self-Hosted LLM Configuration](https://machinebehavior.io/inside/docs/sre/opencode-self-hosted-llm-configuration/) - [Patterns](https://machinebehavior.io/inside/docs/sre/patterns/) - [7. Performance](https://machinebehavior.io/inside/docs/sre/performance/) - [Personal Digital Twin Architecture](https://machinebehavior.io/inside/docs/sre/personal-digital-twin-architecture/) - [The ten pillars](https://machinebehavior.io/inside/docs/sre/pillars/) - [Agents in production are ops work](https://machinebehavior.io/inside/docs/sre/principle-agents-are-ops-work/) - [Cost per unit of work](https://machinebehavior.io/inside/docs/sre/principle-cost-per-unit-of-work/) - [Eliminate toil](https://machinebehavior.io/inside/docs/sre/principle-eliminate-toil/) - [Risk is a budget](https://machinebehavior.io/inside/docs/sre/principle-embracing-risk/) - [If it is not in git, it does not exist](https://machinebehavior.io/inside/docs/sre/principle-everything-in-git/) - [Every incident ends in a record](https://machinebehavior.io/inside/docs/sre/principle-incidents-end-in-records/) - [Monitor symptoms, page on user pain](https://machinebehavior.io/inside/docs/sre/principle-monitor-symptoms/) - [Operations work done as software](https://machinebehavior.io/inside/docs/sre/principle-ops-as-software/) - [Every change passes the same gate](https://machinebehavior.io/inside/docs/sre/principle-release-engineering/) - [Service level objectives](https://machinebehavior.io/inside/docs/sre/principle-service-level-objectives/) - [Simplicity](https://machinebehavior.io/inside/docs/sre/principle-simplicity/) - [SRE is a role inside Ops](https://machinebehavior.io/inside/docs/sre/principle-sre-is-ops/) - [Someone carries the pager](https://machinebehavior.io/inside/docs/sre/principle-standby/) - [Truth, verified, working](https://machinebehavior.io/inside/docs/sre/principle-truth-verified-working/) - [Zero trust](https://machinebehavior.io/inside/docs/sre/principle-zero-trust/) - [Principles in practice](https://machinebehavior.io/inside/docs/sre/principles-in-practice/) - [Probe Pending Rows Before Calling Them Backlog](https://machinebehavior.io/inside/docs/sre/probe-pending-rows-before-calling-them-backlog/) - [Probe the Artifact Before Reasoning From Counts](https://machinebehavior.io/inside/docs/sre/probe-the-artifact-before-reasoning-from-counts/) - [Probing Microarchitecture for Vulnerability Discovery](https://machinebehavior.io/inside/docs/sre/probing-microarchitecture-for-vulnerability-discovery/) - [Process Check Matches Its Own Shell](https://machinebehavior.io/inside/docs/sre/process-check-matches-its-own-shell/) - [Progressive Delivery Patterns](https://machinebehavior.io/inside/docs/sre/progressive-delivery-patterns/) - [Publish Date Treated As Time In Collection](https://machinebehavior.io/inside/docs/sre/publish-date-treated-as-time-in-collection/) - [Pull the Full Row List After Any Scrape](https://machinebehavior.io/inside/docs/sre/pull-the-full-row-list-after-any-scrape/) - [Re-Scrape Relinks Processed Rows As Pending](https://machinebehavior.io/inside/docs/sre/re-scrape-relinks-processed-rows-as-pending/) - [1. Reliability](https://machinebehavior.io/inside/docs/sre/reliability/) - [Review Tool Lists Only Rows With a Transcript](https://machinebehavior.io/inside/docs/sre/review-tool-lists-only-rows-with-a-transcript/) - [Rollback Deployment](https://machinebehavior.io/inside/docs/sre/rollback-deployment/) - [Runbooks](https://machinebehavior.io/inside/docs/sre/runbooks/) - [2. Scalability](https://machinebehavior.io/inside/docs/sre/scalability/) - [8. Security](https://machinebehavior.io/inside/docs/sre/security/) - [Sensitivity-Gated Posts Vanish From Unauthenticated Listing](https://machinebehavior.io/inside/docs/sre/sensitivity-gated-posts-vanish-from-unauthenticated-listing/) - [Service Outage Response](https://machinebehavior.io/inside/docs/sre/service-outage-response/) - [Short Link Redirects to the Homepage](https://machinebehavior.io/inside/docs/sre/short-link-redirects-to-the-homepage/) - [Single Video URL As the Collection Argument](https://machinebehavior.io/inside/docs/sre/single-video-url-as-the-collection-argument/) - [Small Local Model Misreads Ironic Register](https://machinebehavior.io/inside/docs/sre/small-local-model-misreads-ironic-register/) - [SRE as Truth Verified Working](https://machinebehavior.io/inside/docs/sre/sre-as-truth-verified-working/) - [Summaries Are a Triage Index](https://machinebehavior.io/inside/docs/sre/summaries-are-a-triage-index/) - [Swallowed Stderr Hides the Cause](https://machinebehavior.io/inside/docs/sre/swallowed-stderr-hides-the-cause/) - [Symptoms over Causes for Alerting](https://machinebehavior.io/inside/docs/sre/symptoms-over-causes-for-alerting/) - [tencent-agent-memory-four-tier](https://machinebehavior.io/inside/docs/sre/tencent-agent-memory-four-tier/) - [The Disappearing Full-Stack Ops Engineer](https://machinebehavior.io/inside/docs/sre/the-disappearing-full-stack-ops-engineer/) - [10. Toil Reduction](https://machinebehavior.io/inside/docs/sre/toil-reduction/) - [Toil vs Engineering and the 50 Percent Rule](https://machinebehavior.io/inside/docs/sre/toil-vs-engineering-and-the-50-percent-rule/) - [Tools](https://machinebehavior.io/inside/docs/sre/tools/) - [Transcriber Incident Register](https://machinebehavior.io/inside/docs/sre/transcriber-incident-register/) - [Unit Economics of Infrastructure](https://machinebehavior.io/inside/docs/sre/unit-economics-of-infrastructure/) - [USE Method for Resource Saturation](https://machinebehavior.io/inside/docs/sre/use-method-for-resource-saturation/) - [vault-search-fastembed-migration](https://machinebehavior.io/inside/docs/sre/vault-search-fastembed-migration/) - [Verify Transcript Length Never Status](https://machinebehavior.io/inside/docs/sre/verify-transcript-length-never-status/) ### Standards and Compliance - [Standards and Compliance](https://machinebehavior.io/inside/docs/std/): Reference clusters from the knowledge vault for 28 standards, regulations and frameworks: ISO 27001 and 42001, NIS2, DORA, the EU AI Act, GDPR, SOC 2, TISAX, NIST and more. - [BSI IT-Grundschutz anchors](https://machinebehavior.io/inside/docs/std/bsi-grundschutz-anchors/) - [BSI IT-Grundschutz position](https://machinebehavior.io/inside/docs/std/bsi-grundschutz-position/) - [BSI IT-Grundschutz](https://machinebehavior.io/inside/docs/std/bsi-grundschutz/) - [CMMI anchors](https://machinebehavior.io/inside/docs/std/cmmi-anchors/) - [CMMI Controversies](https://machinebehavior.io/inside/docs/std/cmmi-controversies/) - [CMMI Maturity and Capability Levels](https://machinebehavior.io/inside/docs/std/cmmi-maturity-and-capability-levels/) - [CMMI position](https://machinebehavior.io/inside/docs/std/cmmi-position/) - [CMMI](https://machinebehavior.io/inside/docs/std/cmmi/) - [COBIT anchors](https://machinebehavior.io/inside/docs/std/cobit-anchors/) - [COBIT Controversies](https://machinebehavior.io/inside/docs/std/cobit-controversies/) - [COBIT Governance and Management Objectives](https://machinebehavior.io/inside/docs/std/cobit-governance-and-management-objectives/) - [COBIT position](https://machinebehavior.io/inside/docs/std/cobit-position/) - [COBIT](https://machinebehavior.io/inside/docs/std/cobit/) - [CRA Controversies](https://machinebehavior.io/inside/docs/std/cra-controversies/) - [CRA Essential Requirements](https://machinebehavior.io/inside/docs/std/cra-essential-requirements/) - [CSA CCM anchors](https://machinebehavior.io/inside/docs/std/csa-ccm-anchors/) - [CSA CCM Control Domains](https://machinebehavior.io/inside/docs/std/csa-ccm-control-domains/) - [CSA CCM Controversies](https://machinebehavior.io/inside/docs/std/csa-ccm-controversies/) - [CSA CCM position](https://machinebehavior.io/inside/docs/std/csa-ccm-position/) - [CSA CCM](https://machinebehavior.io/inside/docs/std/csa-ccm/) - [Cyber Resilience Act anchors](https://machinebehavior.io/inside/docs/std/cyber-resilience-act-anchors/) - [Cyber Resilience Act Controversies](https://machinebehavior.io/inside/docs/std/cyber-resilience-act-controversies/) - [Cyber Resilience Act position](https://machinebehavior.io/inside/docs/std/cyber-resilience-act-position/) - [Cyber Resilience Act](https://machinebehavior.io/inside/docs/std/cyber-resilience-act/) - [DORA anchors](https://machinebehavior.io/inside/docs/std/dora-anchors/) - [DORA Controversies](https://machinebehavior.io/inside/docs/std/dora-controversies/) - [DORA Governance and Penalties](https://machinebehavior.io/inside/docs/std/dora-governance-and-penalties/) - [DORA ICT Risk Management](https://machinebehavior.io/inside/docs/std/dora-ict-risk-management/) - [DORA ICT Third-Party Risk](https://machinebehavior.io/inside/docs/std/dora-ict-third-party-risk/) - [DORA Incident Reporting](https://machinebehavior.io/inside/docs/std/dora-incident-reporting/) - [DORA position](https://machinebehavior.io/inside/docs/std/dora-position/) - [DORA Resilience Testing](https://machinebehavior.io/inside/docs/std/dora-resilience-testing/) - [DORA](https://machinebehavior.io/inside/docs/std/dora/) - [EU AI Act anchors](https://machinebehavior.io/inside/docs/std/eu-ai-act-anchors/) - [EU AI Act Controversies](https://machinebehavior.io/inside/docs/std/eu-ai-act-controversies/) - [EU AI Act Governance](https://machinebehavior.io/inside/docs/std/eu-ai-act-governance/) - [EU AI Act GPAI Obligations](https://machinebehavior.io/inside/docs/std/eu-ai-act-gpai-obligations/) - [EU AI Act High-Risk Obligations](https://machinebehavior.io/inside/docs/std/eu-ai-act-high-risk-obligations/) - [EU AI Act position](https://machinebehavior.io/inside/docs/std/eu-ai-act-position/) - [EU AI Act Risk Tiers](https://machinebehavior.io/inside/docs/std/eu-ai-act-risk-tiers/) - [EU AI Act Timeline](https://machinebehavior.io/inside/docs/std/eu-ai-act-timeline/) - [EU AI Act](https://machinebehavior.io/inside/docs/std/eu-ai-act/) - [FedRAMP and CMMC Controversies](https://machinebehavior.io/inside/docs/std/fedramp-and-cmmc-controversies/) - [FedRAMP and CMMC Mechanics](https://machinebehavior.io/inside/docs/std/fedramp-and-cmmc-mechanics/) - [FedRAMP CMMC anchors](https://machinebehavior.io/inside/docs/std/fedramp-cmmc-anchors/) - [FedRAMP CMMC position](https://machinebehavior.io/inside/docs/std/fedramp-cmmc-position/) - [FedRAMP CMMC](https://machinebehavior.io/inside/docs/std/fedramp-cmmc/) - [GDPR anchors](https://machinebehavior.io/inside/docs/std/gdpr-anchors/) - [GDPR Controller and Processor](https://machinebehavior.io/inside/docs/std/gdpr-controller-and-processor/) - [GDPR Controversies](https://machinebehavior.io/inside/docs/std/gdpr-controversies/) - [GDPR Cross-Border Transfers](https://machinebehavior.io/inside/docs/std/gdpr-cross-border-transfers/) - [GDPR Data Subject Rights](https://machinebehavior.io/inside/docs/std/gdpr-data-subject-rights/) - [GDPR Enforcement and DPAs](https://machinebehavior.io/inside/docs/std/gdpr-enforcement-and-dpas/) - [GDPR Lawful Bases](https://machinebehavior.io/inside/docs/std/gdpr-lawful-bases/) - [GDPR position](https://machinebehavior.io/inside/docs/std/gdpr-position/) - [GDPR Principles](https://machinebehavior.io/inside/docs/std/gdpr-principles/) - [GDPR](https://machinebehavior.io/inside/docs/std/gdpr/) - [HITRUST anchors](https://machinebehavior.io/inside/docs/std/hitrust-anchors/) - [HITRUST Assessment Levels](https://machinebehavior.io/inside/docs/std/hitrust-assessment-levels/) - [HITRUST Controversies](https://machinebehavior.io/inside/docs/std/hitrust-controversies/) - [HITRUST position](https://machinebehavior.io/inside/docs/std/hitrust-position/) - [HITRUST](https://machinebehavior.io/inside/docs/std/hitrust/) - [ISO 21434 anchors](https://machinebehavior.io/inside/docs/std/iso-21434-anchors/) - [ISO 21434 Controversies](https://machinebehavior.io/inside/docs/std/iso-21434-controversies/) - [ISO 21434 Lifecycle and TARA](https://machinebehavior.io/inside/docs/std/iso-21434-lifecycle-and-tara/) - [ISO 21434 position](https://machinebehavior.io/inside/docs/std/iso-21434-position/) - [ISO 21434](https://machinebehavior.io/inside/docs/std/iso-21434/) - [ISO 22301 anchors](https://machinebehavior.io/inside/docs/std/iso-22301-anchors/) - [ISO 22301 Clause Structure and Key Concepts](https://machinebehavior.io/inside/docs/std/iso-22301-clause-structure-and-key-concepts/) - [ISO 22301 Controversies](https://machinebehavior.io/inside/docs/std/iso-22301-controversies/) - [ISO 22301 position](https://machinebehavior.io/inside/docs/std/iso-22301-position/) - [ISO 22301](https://machinebehavior.io/inside/docs/std/iso-22301/) - [ISO 27001 anchors](https://machinebehavior.io/inside/docs/std/iso-27001-anchors/) - [ISO 27001 Annex A.5 Organizational Controls](https://machinebehavior.io/inside/docs/std/iso-27001-annex-a-5-organizational-controls/) - [ISO 27001 Annex A.6 People Controls](https://machinebehavior.io/inside/docs/std/iso-27001-annex-a-6-people-controls/) - [ISO 27001 Annex A.7 Physical Controls](https://machinebehavior.io/inside/docs/std/iso-27001-annex-a-7-physical-controls/) - [ISO 27001 Annex A.8 Technological Controls](https://machinebehavior.io/inside/docs/std/iso-27001-annex-a-8-technological-controls/) - [ISO 27001 Certification Process](https://machinebehavior.io/inside/docs/std/iso-27001-certification-process/) - [ISO 27001 Clause 10 Improvement](https://machinebehavior.io/inside/docs/std/iso-27001-clause-10-improvement/) - [ISO 27001 Clause 4 Context](https://machinebehavior.io/inside/docs/std/iso-27001-clause-4-context/) - [ISO 27001 Clause 5 Leadership](https://machinebehavior.io/inside/docs/std/iso-27001-clause-5-leadership/) - [ISO 27001 Clause 6 Planning](https://machinebehavior.io/inside/docs/std/iso-27001-clause-6-planning/) - [ISO 27001 Clause 7 Support](https://machinebehavior.io/inside/docs/std/iso-27001-clause-7-support/) - [ISO 27001 Clause 8 Operation](https://machinebehavior.io/inside/docs/std/iso-27001-clause-8-operation/) - [ISO 27001 Clause 9 Performance Evaluation](https://machinebehavior.io/inside/docs/std/iso-27001-clause-9-performance-evaluation/) - [ISO 27001 Controversies](https://machinebehavior.io/inside/docs/std/iso-27001-controversies/) - [ISO 27001 Family and Sector Variants](https://machinebehavior.io/inside/docs/std/iso-27001-family-and-sector-variants/) - [ISO 27001 position](https://machinebehavior.io/inside/docs/std/iso-27001-position/) - [ISO 27001 Version History](https://machinebehavior.io/inside/docs/std/iso-27001-version-history/) - [ISO 27001](https://machinebehavior.io/inside/docs/std/iso-27001/) - [ISO 42001 AI System Lifecycle](https://machinebehavior.io/inside/docs/std/iso-42001-ai-system-lifecycle/) - [ISO 42001 anchors](https://machinebehavior.io/inside/docs/std/iso-42001-anchors/) - [ISO 42001 Annex A Controls](https://machinebehavior.io/inside/docs/std/iso-42001-annex-a-controls/) - [ISO 42001 Certification Process](https://machinebehavior.io/inside/docs/std/iso-42001-certification-process/) - [ISO 42001 Clause Structure](https://machinebehavior.io/inside/docs/std/iso-42001-clause-structure/) - [ISO 42001 Controversies](https://machinebehavior.io/inside/docs/std/iso-42001-controversies/) - [ISO 42001 position](https://machinebehavior.io/inside/docs/std/iso-42001-position/) - [ISO 42001 vs ISO 27001 Integration](https://machinebehavior.io/inside/docs/std/iso-42001-vs-iso-27001-integration/) - [ISO 42001](https://machinebehavior.io/inside/docs/std/iso-42001/) - [IT-Grundschutz Certification](https://machinebehavior.io/inside/docs/std/it-grundschutz-certification/) - [IT-Grundschutz Controversies](https://machinebehavior.io/inside/docs/std/it-grundschutz-controversies/) - [IT-Grundschutz Methodology and Bausteine](https://machinebehavior.io/inside/docs/std/it-grundschutz-methodology-and-bausteine/) - [ITIL 4 Certification Scheme](https://machinebehavior.io/inside/docs/std/itil-4-certification-scheme/) - [ITIL 4 Four Dimensions](https://machinebehavior.io/inside/docs/std/itil-4-four-dimensions/) - [ITIL 4 Guiding Principles](https://machinebehavior.io/inside/docs/std/itil-4-guiding-principles/) - [ITIL 4 Practices](https://machinebehavior.io/inside/docs/std/itil-4-practices/) - [ITIL 4 Service Value Chain](https://machinebehavior.io/inside/docs/std/itil-4-service-value-chain/) - [ITIL 4 Service Value System](https://machinebehavior.io/inside/docs/std/itil-4-service-value-system/) - [ITIL anchors](https://machinebehavior.io/inside/docs/std/itil-anchors/) - [ITIL Controversies](https://machinebehavior.io/inside/docs/std/itil-controversies/) - [ITIL position](https://machinebehavior.io/inside/docs/std/itil-position/) - [ITIL Version History](https://machinebehavior.io/inside/docs/std/itil-version-history/) - [ITIL vs ISO 20000](https://machinebehavior.io/inside/docs/std/itil-vs-iso-20000/) - [ITIL](https://machinebehavior.io/inside/docs/std/itil/) - [MITRE anchors](https://machinebehavior.io/inside/docs/std/mitre-anchors/) - [MITRE ATLAS](https://machinebehavior.io/inside/docs/std/mitre-atlas/) - [MITRE ATT&CK](https://machinebehavior.io/inside/docs/std/mitre-att-ck/) - [MITRE D3FEND](https://machinebehavior.io/inside/docs/std/mitre-d3fend/) - [MITRE position](https://machinebehavior.io/inside/docs/std/mitre-position/) - [MITRE](https://machinebehavior.io/inside/docs/std/mitre/) - [NIS2 anchors](https://machinebehavior.io/inside/docs/std/nis2-anchors/) - [NIS2 Controversies](https://machinebehavior.io/inside/docs/std/nis2-controversies/) - [NIS2 Governance and Penalties](https://machinebehavior.io/inside/docs/std/nis2-governance-and-penalties/) - [NIS2 Incident Reporting](https://machinebehavior.io/inside/docs/std/nis2-incident-reporting/) - [NIS2 position](https://machinebehavior.io/inside/docs/std/nis2-position/) - [NIS2 Scope and Entities](https://machinebehavior.io/inside/docs/std/nis2-scope-and-entities/) - [NIS2 Security Measures](https://machinebehavior.io/inside/docs/std/nis2-security-measures/) - [NIS2 vs ISO 27001](https://machinebehavior.io/inside/docs/std/nis2-vs-iso-27001/) - [NIS2](https://machinebehavior.io/inside/docs/std/nis2/) - [NIST AI RMF anchors](https://machinebehavior.io/inside/docs/std/nist-ai-rmf-anchors/) - [NIST AI RMF Controversies](https://machinebehavior.io/inside/docs/std/nist-ai-rmf-controversies/) - [NIST AI RMF Core Functions](https://machinebehavior.io/inside/docs/std/nist-ai-rmf-core-functions/) - [NIST AI RMF GenAI Profile](https://machinebehavior.io/inside/docs/std/nist-ai-rmf-genai-profile/) - [NIST AI RMF position](https://machinebehavior.io/inside/docs/std/nist-ai-rmf-position/) - [NIST AI RMF vs ISO 42001](https://machinebehavior.io/inside/docs/std/nist-ai-rmf-vs-iso-42001/) - [NIST AI RMF](https://machinebehavior.io/inside/docs/std/nist-ai-rmf/) - [NIST CSF anchors](https://machinebehavior.io/inside/docs/std/nist-csf-anchors/) - [NIST CSF Controversies](https://machinebehavior.io/inside/docs/std/nist-csf-controversies/) - [NIST CSF Core Functions](https://machinebehavior.io/inside/docs/std/nist-csf-core-functions/) - [NIST CSF position](https://machinebehavior.io/inside/docs/std/nist-csf-position/) - [NIST CSF vs ISO 27001 and NIST AI RMF](https://machinebehavior.io/inside/docs/std/nist-csf-vs-iso-27001-and-nist-ai-rmf/) - [NIST CSF](https://machinebehavior.io/inside/docs/std/nist-csf/) - [OECD AI anchors](https://machinebehavior.io/inside/docs/std/oecd-ai-anchors/) - [OECD AI Controversies](https://machinebehavior.io/inside/docs/std/oecd-ai-controversies/) - [OECD AI position](https://machinebehavior.io/inside/docs/std/oecd-ai-position/) - [OECD AI Values-Based Principles](https://machinebehavior.io/inside/docs/std/oecd-ai-values-based-principles/) - [OECD AI](https://machinebehavior.io/inside/docs/std/oecd-ai/) - [OWASP LLM Mitigations](https://machinebehavior.io/inside/docs/std/owasp-llm-mitigations/) - [OWASP LLM Top 10 2025](https://machinebehavior.io/inside/docs/std/owasp-llm-top-10-2025/) - [OWASP LLM Top 10 anchors](https://machinebehavior.io/inside/docs/std/owasp-llm-top-10-anchors/) - [OWASP LLM Top 10 Controversies](https://machinebehavior.io/inside/docs/std/owasp-llm-top-10-controversies/) - [OWASP LLM Top 10 position](https://machinebehavior.io/inside/docs/std/owasp-llm-top-10-position/) - [OWASP LLM Top 10](https://machinebehavior.io/inside/docs/std/owasp-llm-top-10/) - [OWASP LLM vs Top 10 Web](https://machinebehavior.io/inside/docs/std/owasp-llm-vs-top-10-web/) - [PCI DSS anchors](https://machinebehavior.io/inside/docs/std/pci-dss-anchors/) - [PCI DSS Controversies](https://machinebehavior.io/inside/docs/std/pci-dss-controversies/) - [PCI DSS position](https://machinebehavior.io/inside/docs/std/pci-dss-position/) - [PCI DSS Twelve Requirements and Compliance](https://machinebehavior.io/inside/docs/std/pci-dss-twelve-requirements-and-compliance/) - [PCI DSS](https://machinebehavior.io/inside/docs/std/pci-dss/) - [PRINCE2 anchors](https://machinebehavior.io/inside/docs/std/prince2-anchors/) - [PRINCE2 Controversies](https://machinebehavior.io/inside/docs/std/prince2-controversies/) - [PRINCE2 position](https://machinebehavior.io/inside/docs/std/prince2-position/) - [PRINCE2 Principles Aspects Processes](https://machinebehavior.io/inside/docs/std/prince2-principles-aspects-processes/) - [PRINCE2](https://machinebehavior.io/inside/docs/std/prince2/) - [SLSA Levels and SBOM Formats](https://machinebehavior.io/inside/docs/std/slsa-levels-and-sbom-formats/) - [SLSA SBOM anchors](https://machinebehavior.io/inside/docs/std/slsa-sbom-anchors/) - [SLSA SBOM Controversies](https://machinebehavior.io/inside/docs/std/slsa-sbom-controversies/) - [SLSA SBOM position](https://machinebehavior.io/inside/docs/std/slsa-sbom-position/) - [SLSA SBOM](https://machinebehavior.io/inside/docs/std/slsa-sbom/) - [SOC 2 Assessment Process](https://machinebehavior.io/inside/docs/std/soc-2-assessment-process/) - [SOC 2 Controversies](https://machinebehavior.io/inside/docs/std/soc-2-controversies/) - [SOC 2 Trust Services Criteria](https://machinebehavior.io/inside/docs/std/soc-2-trust-services-criteria/) - [SOC 2 Type 1 vs Type 2](https://machinebehavior.io/inside/docs/std/soc-2-type-1-vs-type-2/) - [SOC 2 vs ISO 27001](https://machinebehavior.io/inside/docs/std/soc-2-vs-iso-27001/) - [SOC 2 anchors](https://machinebehavior.io/inside/docs/std/soc2-anchors/) - [SOC 2 position](https://machinebehavior.io/inside/docs/std/soc2-position/) - [SOC 2](https://machinebehavior.io/inside/docs/std/soc2/) - [TISAX anchors](https://machinebehavior.io/inside/docs/std/tisax-anchors/) - [TISAX Assessment Levels](https://machinebehavior.io/inside/docs/std/tisax-assessment-levels/) - [TISAX Assessment Process](https://machinebehavior.io/inside/docs/std/tisax-assessment-process/) - [TISAX Controversies](https://machinebehavior.io/inside/docs/std/tisax-controversies/) - [TISAX Labels and Scopes](https://machinebehavior.io/inside/docs/std/tisax-labels-and-scopes/) - [TISAX position](https://machinebehavior.io/inside/docs/std/tisax-position/) - [TISAX VDA-ISA Catalogue](https://machinebehavior.io/inside/docs/std/tisax-vda-isa-catalogue/) - [TISAX vs ISO 27001](https://machinebehavior.io/inside/docs/std/tisax-vs-iso-27001/) - [TISAX](https://machinebehavior.io/inside/docs/std/tisax/) - [TOGAF ADM](https://machinebehavior.io/inside/docs/std/togaf-adm/) - [TOGAF anchors](https://machinebehavior.io/inside/docs/std/togaf-anchors/) - [TOGAF Architecture Capability](https://machinebehavior.io/inside/docs/std/togaf-architecture-capability/) - [TOGAF Certification Scheme](https://machinebehavior.io/inside/docs/std/togaf-certification-scheme/) - [TOGAF Content Framework](https://machinebehavior.io/inside/docs/std/togaf-content-framework/) - [TOGAF Controversies](https://machinebehavior.io/inside/docs/std/togaf-controversies/) - [TOGAF Enterprise Continuum](https://machinebehavior.io/inside/docs/std/togaf-enterprise-continuum/) - [TOGAF position](https://machinebehavior.io/inside/docs/std/togaf-position/) - [TOGAF Version History](https://machinebehavior.io/inside/docs/std/togaf-version-history/) - [TOGAF vs Other EA Frameworks](https://machinebehavior.io/inside/docs/std/togaf-vs-other-ea-frameworks/) - [TOGAF](https://machinebehavior.io/inside/docs/std/togaf/) - [UN R155 CSMS and R156 SUMS](https://machinebehavior.io/inside/docs/std/un-r155-csms-and-r156-sums/) - [UN R155 R156 anchors](https://machinebehavior.io/inside/docs/std/un-r155-r156-anchors/) - [UN R155 R156 Controversies](https://machinebehavior.io/inside/docs/std/un-r155-r156-controversies/) - [UN R155 R156 position](https://machinebehavior.io/inside/docs/std/un-r155-r156-position/) - [UN R155 R156](https://machinebehavior.io/inside/docs/std/un-r155-r156/) ## Inside services The service catalog at https://machinebehavior.io/inside/services/ (12 services), built from YAML in the repository. Machine-readable: https://machinebehavior.io/inside/services/services.json. - [Conformity gate](https://machinebehavior.io/inside/services/conformity-gate/): Publishing, tier 1, production. The checks every push runs before a site serves readers: blocking rule hits, placeholder text, prediction hashes and site consistency. A failed check stops the deploy and the previous build stays live. One composite action, shared by the three sites. - [Deploy job](https://machinebehavior.io/inside/services/deploy-job/): Publishing, tier 1, production. The second job of the Conformity workflow. It runs only after the checks pass, refreshes the map and the search index, writes the deploy feed and the board snapshot, and deploys the site to GitHub Pages. - [machinebehavior.io](https://machinebehavior.io/inside/services/machinebehavior-io/): Publishing, tier 1, production. The research site and the home of Inside: claims, experiments, objections, case files, the map, the docs, the board and this catalog. Hand-written HTML and Python generators, served by GitHub Pages. - [tychat.io](https://machinebehavior.io/inside/services/tychat-io/): Publishing, tier 1, production. Lessons a chat model reads on request, as static pages and plain-text files indexed in llms.txt. Served by GitHub Pages. - [uncovertechtalent.com](https://machinebehavior.io/inside/services/uncovertechtalent-com/): Publishing, tier 1, production. The blog and the Uncover Tech Talent offer, built with Hugo from a private repository and served by GitHub Pages. - [Docs build](https://machinebehavior.io/inside/services/docs-build/): Publishing, tier 2, production. Builds the Inside docs from markdown sources and the knowledge vault: one page per file, the tree, labels, dates, backlinks, the docs search index, and managed blocks in sitemap.xml and llms.txt. - [Map crawler](https://machinebehavior.io/inside/services/map-crawler/): Publishing, tier 3, production. Crawls the three sites and the Substack archive into one graph of pages, posts, repositories, threads and tags, with body links kept apart from navigation. Runs locally and in every deploy. - [Deploy exporter](https://machinebehavior.io/inside/services/deploy-exporter/): Observability, tier 2, production. A standard-library Python service that reads the GitHub Actions runs of the three sites, writes each run, step and gate check to Loki and serves the latest state as Prometheus metrics. Feeds the Website deploys dashboard. - [Observability stack](https://machinebehavior.io/inside/services/observability-stack/): Observability, tier 2, production. One Docker Compose project on a home server: Alloy, Prometheus, Loki, Tempo and Grafana, with 17 alert rules and the public dashboards behind a reverse proxy that passes only the shared paths. No Alertmanager runs, so no alert pages anyone. - [SearXNG](https://machinebehavior.io/inside/services/searxng/): Research tooling, tier 2, production. The self-hosted metasearch instance every research agent searches through, with per-engine pacing and suspensions after rate limits. An exporter pushes engine health to the observability stack; six alert rules watch it. - [Local LLM](https://machinebehavior.io/inside/services/local-llm/): Research tooling, tier 3, production. The self-hosted model server on the home server, metered by a pass-through proxy (the ollama-exporter) for time to first token, decode speed, token counts and resident models. The only service with defined SLOs and burn-rate alerts. - [Agent sessions](https://machinebehavior.io/inside/services/agent-sessions/): Agents, tier 2, production. The Claude Code sessions that build and run this platform, each owning one track of work and pushing through the gate. Spend and tokens are summed from per-request events; a spend alert fires above USD 40 in the trailing hour. ## Inside status The status page at https://machinebehavior.io/inside/status/: the state of each service from the gate records and the deploy feed, and the incident history (stages Investigating, Identified, Monitoring, Resolved), written blameless. Machine-readable: https://machinebehavior.io/inside/status/incidents.json. - [SearXNG searches degraded by engine rate limits and blocks](https://machinebehavior.io/inside/status/#2026-10-09-searxng-engine-suspensions): monitoring, started 2026-10-09. Searches for the research agents returned fewer results and took about 6 seconds per upstream query. Pacing was per query instead of per engine, so each engine saw about 20 calls a minute and two engines answered with rate limits. One engine waited out a 6-second timeout on every query, empty responses were cached for 24 hours, and the container did not restart on its own. - [A push to machinebehavior.io failed the gate; the deploy was blocked](https://machinebehavior.io/inside/status/#2026-10-08-gate-blocked-map-push): resolved, started 2026-10-08T14:05Z. A change to the map page built a link inside a JavaScript template string. The link check read it as a relative link, the gate failed and the deploy did not run, so readers kept the previous build. A follow-up push set the link in code and passed. The control worked as designed; the record is kept because a blocked deploy is the case the gate exists for. - [Tag pages on uncovertechtalent.com served RSS XML instead of HTML](https://machinebehavior.io/inside/status/#2026-10-08-utt-tag-pages-xml): resolved, started 2026-10-08. The Hugo build of uncovertechtalent.com had no template for tag pages, so each of the 37 tag pages answered with the RSS feed. A reader who opened a tag, on the site or from the map, got raw XML. The map dropped the pages first; then the site gained the missing templates and the tag pages answer with HTML again. - [Claude Code spend overstated about 1,960 times by counter resets](https://machinebehavior.io/inside/status/#2026-10-09-phantom-spend-counters): resolved, started 2026-10-02T07:54Z. Parallel Claude Code processes wrote one cost counter series, and every export from a process with a lower total read as a counter reset. Prometheus reported USD 1,970,946.62 for a week whose per-request events sum to USD 1,003.45 at list price, and the spend alert was in firing state 73% of the time. No money moved; the meter was wrong. Spend and tokens are now summed from the events. ## Site sections - [Research](https://machinebehavior.io/research/): the Research section front page: The research programme in public. Claims with what would refute them, experiments with hashed predictions, registers, logs, case files, articles and reference texts. - [Topics](https://machinebehavior.io/topics/): Topics on machinebehavior.io: 8 hubs, each listing the research pages, Inside pages, docs, posts and tickets on one subject. - [Sycophancy and stance](https://machinebehavior.io/topics/sycophancy-and-stance/): topic hub, 7 research pages, 3 red team pages, 7 docs pages, 6 posts. The fawn response in language models, where it moves when one layer is suppressed, and the stance layer that decides whether a model holds a correct answer under pressure. - [Conformity and law](https://machinebehavior.io/topics/conformity-and-law/): topic hub, 4 research pages, 2 Inside pages, 212 docs pages, 20 tickets. Continuous conformity for deployed AI systems, the gate that checks this site on every push, and the standards and regulations the requirements map to, from the EU AI Act to ISO 42001. - [Operations and SRE](https://machinebehavior.io/topics/operations-and-sre/): topic hub, 1 research page, 6 Inside pages, 121 docs pages, 12 posts, 6 tickets. Running software and agents in production. Incidents written blameless, runbooks, error budgets, toil, and the operations practice that carries over to language models. - [Observability](https://machinebehavior.io/topics/observability/): topic hub, 6 Inside pages, 21 docs pages, 1 post, 13 tickets. Prometheus, Loki and Grafana behind the public dashboards, the alert rules and SLOs, and the status page that reads the published records. - [FinOps](https://machinebehavior.io/topics/finops/): topic hub, 2 Inside pages, 9 docs pages, 3 tickets. What the platform costs and how it is metered. The cost model, unit economics, showback, budgets and alerts, an anomaly case and a FOCUS export. - [Agents and harness](https://machinebehavior.io/topics/agents-and-harness/): topic hub, 4 research pages, 2 Inside pages, 16 docs pages, 12 posts, 4 tickets. Language models at work inside a harness of instruction files, hooks, memory and a knowledge vault, and what the harness holds where an instruction alone fails. - [Evaluation](https://machinebehavior.io/topics/evaluation/): topic hub, 7 research pages, 3 red team pages, 9 docs pages, 2 posts. Experiments with predictions hashed before the first call, a mechanical grader, red-teaming read as chaos engineering, and a self-assessment with a second rater wanted. - [AI search](https://machinebehavior.io/topics/ai-search/): topic hub, 1 research page, 4 Inside pages, 1 docs page, 1 ticket. How the engines behind AI answers pick the pages they cite, how this site is built for them, and how citations get measured. ## CTO powersuit plugins One page per plugin of the CTO powersuit at release v0.2.0 (2026-10-14), grouped by the area of the CTO job: the line, the version, the skills with their commands, the gate checks, and the install commands. Overview: https://machinebehavior.io/cto-powersuit/ ### Direction - [fit](https://machinebehavior.io/cto-powersuit/fit/): The entry assessment: runs the sdlc audit and recommends which modules to fit and in which order. Its repo clinic audits a public repository at its owner's request. Version 0.2.0, 2 skills. - [decisions](https://machinebehavior.io/cto-powersuit/decisions/): RFCs, architecture decision records, and a review of the decision log, with a gate check that every record has a status, an owner, and a date. Version 0.1.0, 3 skills. ### Delivery - [sdlc](https://machinebehavior.io/cto-powersuit/sdlc/): The software delivery lifecycle: an audit for repositories built without one, tickets, change review for agent-written code, a local CI run before each push, test strategy, and release with rollback. Version 0.2.3, 8 skills. - [gate](https://machinebehavior.io/cto-powersuit/gate/): A deploy gate: rules with pass and fail fixtures, run records, findings that close only on a passing rerun, and a workflow whose deploy job waits for the gate. Version 0.2.1, 3 skills. - [docs](https://machinebehavior.io/cto-powersuit/docs/): A docs tree where every page has an owner and review dates, runbooks, a sweep for stale pages, and a static docs build. Version 0.1.0, 3 skills. ### Operations - [reliability](https://machinebehavior.io/cto-powersuit/reliability/): Availability targets, SLOs and error budgets, incidents and postmortems, a static status page, and an on-call policy. Version 0.1.0, 6 skills. - [observability](https://machinebehavior.io/cto-powersuit/observability/): Alloy, Prometheus, Loki, Grafana, and Alertmanager with docker compose, dashboards as code, and alert routes. Version 0.1.0, 3 skills. ### Money - [finops](https://machinebehavior.io/cto-powersuit/finops/): A cost baseline from invoices and billing exports, showback, unit costs, a SaaS stack audit, and a FOCUS export, with a gate check that every cost figure carries a period and a source. Version 0.1.0, 5 skills. ### Security and risk - [security](https://machinebehavior.io/cto-powersuit/security/): Supply chain, secrets, and access for a repository and its agents: actions pinned by commit SHA with an owner allowlist, a vulnerability scan and an SBOM, provenance checks for skills and MCP servers, a pre-push hook for private terms, and a quarantine for third-party text. Version 0.3.0, 7 skills. - [compliance](https://machinebehavior.io/cto-powersuit/compliance/): A control map to ISO 27001, TISAX, NIS2, and the GDPR by clause and article number, an AI Act triage, and a legal baseline for a website. Version 0.1.0, 3 skills. - [red-team](https://machinebehavior.io/cto-powersuit/red-team/): Pressure tests for a team's AI features: scripted multi-turn runs in a world with a known right answer, graded on the decision the system took. Version 0.1.0, 3 skills. ### AI - [ai-ops](https://machinebehavior.io/cto-powersuit/ai-ops/): Operations for a team's coding agents: a shared harness with narrow permissions, agent spend metered per API request with a budget alert, an audit trail of tool calls, and a coordinator pattern with state in files. Version 0.2.0, 4 skills. - [aieo](https://machinebehavior.io/cto-powersuit/aieo/): Visibility in AI search: llms.txt, structured data, answer probes, and predictions hashed before a page goes live. Version 0.1.0, 4 skills. ### People - [hiring](https://machinebehavior.io/cto-powersuit/hiring/): An interview loop, rubrics with anchored levels, debriefs with evidence before votes, and the profile of the person who takes over the platform. Version 0.1.0, 4 skills. - [handover](https://machinebehavior.io/cto-powersuit/handover/): Hand the platform to its owner: training per module, exit criteria, and a test plan that shows the owner runs the platform from the docs alone. Version 0.1.1, 3 skills. ### Knowledge layer - [vestige](https://machinebehavior.io/cto-powersuit/vestige/): An output filter you calibrate to yourself from your own transcripts. Hooks scan every reply and every Markdown file Claude writes. Version 0.1.0, 4 skills. - [vault](https://machinebehavior.io/cto-powersuit/vault/): A plain-Markdown vault with hybrid keyword and semantic search, served to Claude as an MCP server, with skills to seed it and to atomize documents into it. Version 0.1.0, 3 skills. - [stance](https://machinebehavior.io/cto-powersuit/stance/): Stance filters: professional-b2, good-chad, receipts, poles, and mode-leak. Version 0.1.0, 6 skills.