## Change Make native coding-agent execution the default AgentOps entry path with zero mandatory skills. Preserve full bundles and add repeatable `ao skills link --skill NAME` selection, validating the entire selection before writes. Align product, installation, architecture and generated command documentation. Extend the existing trial readout to separate endpoint test results, execution state and independently accepted work. Bind supplied judgments to exact content, acceptance and native evidence. Reject empty implementation subjects and require the caller's complete criterion ID set before reporting acceptance. Preserve genuine nonempty and deletion-only subjects, valid failures and missing-proof outcomes. ## Validation - Native onboarding from empty home/consumer directories produces no setup files; selective/full linking and failure boundaries are covered. - Actual RED/GREEN regressions cover empty subjects and the partial-criterion omission found by independent review. - Full Go build, vet and race/shuffle tests; affected Go lint; 88 Python readout/statistics tests passed. - All 73 gates, generated projections, strict documentation build and local aggregate passed (10 passed; one documented optional absence). - All nine PR checks succeeded at `7df0d42b12f35ffc22008cc10a40339afcfbb6a0`. - Fresh author-distinct review passed all six acceptance criteria over all 59 changed paths, with no findings or unchecked scope, after repairing the criterion-coverage finding. ## Evidence limits The real native coding repair demonstrates usability, not comparative skill uplift. The strict live-session machine replay remains NOT_PROVEN where execution/identity observations are unavailable; the source review PASS is retained separately. Existing cohort limits and the historical aggregate-enforcement gap remain unwaived. No new comparative cohort, scheduler, skill-corpus deletion, memory migration or global installation is included.
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AgentOps Practice Registry
Practice lineage and slug registry for this repo. Not product positioning and not the CDLC doctrine. Canonical CDLC framing lives in
docs/cdlc.md; product posture lives inPRODUCT.md; measurable fitness lives inGOALS.md.
What this is
The derivation root for practices: [slug] citations across skills, hooks,
evals, schemas, scripts, and CLI code. It names the practice lineage
AgentOps inherits from, records a short agent-context interpretation, and
defines the canonical slug registry validated by
scripts/validate-practice-citations.sh.
Use this file to answer "which proven practice does this primitive embody?"
Do not use it as a second product page. If the claim is core doctrine, put it
in docs/architecture/rpi-traversal.md, PRODUCT.md, or GOALS.md.
Lineage: reverse-traced from now to the 90s
Filtered to techniques engineers actually adopted at scale, with the canonical source. Only practices that survived contact with real production are listed.
2024-2026: agent-assisted dev, post-LLM operations
- LLM evaluation harnesses + golden-set canaries — Anthropic eval kits, OpenAI evals, DSPy. Proven for drift detection on prompt and model changes.
- Prompt-as-spec — Karpathy's "vibe coding"; chain-of-thought elicitation (Wei et al). Proven by transcripts shipping working systems.
- AI-assisted dev with verification harnesses — Cursor / Claude Code / Codex with tests-as-spec. Proven where teams ship and rollback signals exist.
- DORA-at-scale empirical research — Forsgren / Humble / Kim Accelerate (2018) plus the State-of-DevOps reports. Replicated across cohorts.
- Empirical agent-workflow measurement — Finster, "Agentic Workflows: Do
Agents Work?" (2026). Controlled 2×2×2 study (test-ordering × batch × authorship)
with hidden acceptance tests. Isolated which human practices transfer to
agents: refactor-after-every-green and small batches drive quality;
test-first ordering and split authorship do not. Sharpens the repo's
tddandrefactoringslugs.
2018-2023: cloud-native maturity, observability, platform engineering
- GitOps — Weaveworks 2017, Flux/ArgoCD. Proven: declarative reconcile loops survive operator turnover.
- Distributed tracing — Google Dapper paper (2010), Zipkin, Jaeger, OpenTelemetry. Proven everywhere.
- eBPF observability — Cilium, Pixie, Parca. Proven at hyperscale.
- Team Topologies — Skelton / Pais 2019. Proven via inverse Conway maneuvers in real reorgs.
- Data contracts / Data mesh — Zhamak Dehghani 2019; Andrew Jones Driving Data Quality with Data Contracts 2023. Proven for streaming pipelines that don't silently drift.
- Feature flags as control plane — LaunchDarkly + DevOps Handbook patterns; Etsy / Facebook discipline. Proven.
- Reproducible / hermetic builds — Bazel, Nix. Proven for supply-chain integrity.
- SLSA / SBOM / code signing — Google + OpenSSF. Proven post-Solarwinds.
- Service mesh — Linkerd thrived; Istio survived after years of bruising. Mixed-proven.
2013-2017: DevOps mainstream, microservices first wave, kubernetes
- The Phoenix Project — Kim / Behr / Spafford 2013. Synthesis of DevOps practices into one operational frame. Proven via mass adoption.
- Microservices — Newman Building Microservices (2015); Fowler / Lewis 2014. Proven AND criticized — the "microservices premium" lesson is itself proven.
- Site Reliability Engineering — Beyer et al, Google SRE Book 2016. Error budgets, toil reduction, on-call rotations. Proven.
- The 12-Factor App — Adam Wiggins / Heroku 2011-2012. Proven by every modern web service.
- Designing Data-Intensive Applications — Kleppmann 2017. Reference synthesis of distributed systems lessons.
- Continuous Delivery — Humble / Farley 2010. Proven via deployment frequency and MTTR data.
- Release It! — Nygard 2007 (2nd ed 2018). Circuit breakers, bulkheads, decoupling. Proven in every resilient service.
- Infrastructure as Code — Puppet 2005, Chef 2009, Terraform 2014.
- Docker — 2013, mainstreamed Linux containers. Proven.
2003-2012: DDD, refactoring, agile/XP maturity, CI/CD birth
- Domain-Driven Design — Eric Evans 2003. Bounded contexts, ubiquitous language, anti-corruption layer. Twenty years of survival in real architecture decisions. Load-bearing for AI-agent collaboration.
- Working Effectively with Legacy Code — Michael Feathers 2004. Seam-based testing. Proven for any team inheriting a codebase.
- Continuous Integration — Fowler article 2006; Jenkins / Hudson 2004. Proven universally.
- Refactoring — Fowler 1999 (2nd ed 2018); Opdyke 1992 PhD. Proven discipline.
- Test-Driven Development — Kent Beck Test-Driven Development: By Example 2003. Proven where teams sustain it.
- Behavior-Driven Development — Dan North 2006; Cucumber / Gherkin (Aslak Hellesøy). Proven on product-level acceptance flows.
- Hexagonal architecture / Ports and Adapters — Alistair Cockburn 2005. Proven for testable boundaries.
- Architecture Decision Records — Michael Nygard 2011. Proven by every team that uses them — light enough to actually maintain.
- Property-based testing — QuickCheck, Claessen / Hughes 2000. Proven for finding edge cases impossible to enumerate by example.
- Approval / golden / snapshot testing — Llewellyn Falco, Emily Bache. Proven for legacy characterization and lock-in regression detection.
- Event Sourcing / CQRS — Greg Young 2010. Proven in financial systems and high-event-volume domains.
- The Lean Startup — Eric Ries 2011. Build-measure-learn. Proven outside startups too.
1996-2003: Agile birth, Pragmatic Programmer, GoF, design contracts
- Agile Manifesto — Snowbird 2001 (Beck, Fowler, Cunningham, Cockburn, Jeffries, Schwaber, Sutherland, et al). Proven by displacing waterfall in general industry.
- Extreme Programming — Kent Beck XP Explained 1999, 2nd ed 2004. C3 project at Chrysler. Proven where teams maintain the discipline.
- The Pragmatic Programmer — Hunt / Thomas 1999, 20th-anniversary ed 2019. Tracer bullets, orthogonality, broken-window theory, DRY at the knowledge layer (not syntactic). Proven by practitioners worldwide.
- Code Complete — Steve McConnell 1993, 2nd ed 2004. Proven reference manual.
- Design Patterns / GoF — Gamma / Helm / Johnson / Vlissides 1994. Partly proven (creational and structural patterns); partly mocked (over-engineering risk). Take what survived.
- Object-Oriented Software Construction / Design by Contract — Bertrand Meyer 1988 / 1997. Eiffel-specific in form, but contract-by-design influenced everything from Java assertions to TLA+.
- The Mythical Man-Month — Brooks 1975, anniversary ed 1995. Conway's Law, second-system effect, no-silver-bullet. Foundational.
Pre-1996: still load-bearing
- TCP/IP, HTTP, robust internet engineering — Postel's Law (RFC 793, 1981): "be conservative in what you do, liberal in what you accept." The default protocol-design principle.
- The original wiki — Ward Cunningham 1994. The first knowledge surface agents and humans both edit. Pattern-language origin.
- Garbage collection, B-trees, query planning, leader election — distributed-systems and data-engineering foundations referenced throughout Kleppmann.
- Capability Maturity Model — SEI 1991. Process-maturity origins; partly proven, partly recipe-for-bureaucracy.
Synthesis
AgentOps is what every practice listed above looks like when the consumer is an AI agent with a finite context window, not just a human team.
The constraint changes the size and shape of the artifacts those practices produce. The practices themselves do not change.
Applying the registry to native execution
Select practices for the concrete engineering problem; this catalog is not a mandatory workflow. For this repository's native default:
- Use BDD examples to clarify ambiguous behavior, including consequential edge cases. A small clear change can use the existing issue and tests directly.
- Use DDD to keep work tracking, source content, execution, evidence and memory with their existing owners. Introduce an abstraction only for a real boundary.
- Prefer small batches, direct repairs and tests at the changed behavior's seam. A behavioral fix benefits from a right-reason failing test; a documentation edit does not need a manufactured RED or an executable test of every sentence.
- Link to current sources and retrieve them on demand. An index earns its cost when it solves an observed discovery problem; no per-task INDEX or packet is required.
- Run the repository's required integration checks and obtain one fresh review of the exact accepted change. Review depth follows risk and unresolved facts.
- Reuse reviewed external knowledge when applicable. Preserve support and limitations; later task evidence must establish benefit. Capturing a lesson does not itself prove compounding.
A native goal and existing tracker can preserve intent and handoff facts. Discovery, planning, implementation and review do not each need a new artifact.
What does NOT change
- The practices listed above were correct before AI; they are correct after.
- TDD/BDD didn't fail because of agents; it failed because teams didn't keep specs and code in sync. Agents make that failure mode louder, not new.
- Pragmatic engineering is still pragmatic. We do not ship perfection; we ship the simplest tracer that proves the architecture, then thicken (Hunt / Thomas).
- Conway's Law still applies (Brooks). Repo structure mirrors the human-AI collaboration topology, not the other way around.
- Postel's Law still applies (RFC 793). Robust under input variation, conservative on output.
Implication for this repo
Keep artifacts with their source owner: code, tests, contracts, and only the navigation or evidence a real consumer needs. Before adding process material, name that consumer, the decision it supports, the observed defect and the condition under which it can be retired. A new program written only to consume an otherwise unnecessary artifact does not justify it.
Use the smallest acceptance-advancing action. None of these practices requires installing or invoking an AgentOps skill; skills are optional guidance for specific uncertainties. The registry does not prove that every practice helps every task or that the skill library outperforms native model judgment.
Practice slugs (canonical registry)
Every Primitive in this repo (skill, hook, eval suite, CLI command, schema)
declares which practices it embodies via a practices: [slug, slug, ...]
field in its frontmatter or header doc. Slugs are kebab-case, stable, and
listed here. Add new slugs by appending — never rename silently.
The registry is the source of truth for scripts/validate-practice-citations.sh.
That gate runs in report-only mode initially; after one clean cycle of
backfill, it promotes to required.
| Slug | Era | What it names |
|---|---|---|
llm-eval-harness |
2024-2026 | LLM evaluation harnesses + golden-set canaries |
prompt-as-spec |
2024-2026 | Prompt-as-spec / chain-of-thought elicitation |
ai-assisted-dev |
2024-2026 | AI-assisted dev with verification harnesses |
dora-metrics |
2024-2026 | DORA-at-scale empirical research (Accelerate) |
gitops |
2018-2023 | Declarative-reconcile-loop deployment (Flux / ArgoCD) |
distributed-tracing |
2018-2023 | Dapper / Zipkin / Jaeger / OpenTelemetry |
ebpf-observability |
2018-2023 | eBPF-based introspection (Cilium / Pixie / Parca) |
team-topologies |
2018-2023 | Skelton / Pais inverse-Conway maneuvers |
data-contracts |
2018-2023 | Schema-enforced streaming data contracts |
feature-flags |
2018-2023 | Feature flags as runtime control plane |
hermetic-builds |
2018-2023 | Bazel / Nix reproducible builds |
supply-chain-integrity |
2018-2023 | SLSA / SBOM / code signing |
service-mesh |
2018-2023 | Linkerd / Istio cross-cutting transport |
devops |
2013-2017 | The Phoenix Project operational frame |
microservices |
2013-2017 | One bounded context per service (incl. premium critique) |
sre |
2013-2017 | Google SRE Book: error budgets, toil, on-call |
twelve-factor-app |
2013-2017 | Heroku 12-Factor App |
distributed-systems-design |
2013-2017 | Kleppmann DDIA synthesis |
continuous-delivery |
2013-2017 | Humble / Farley deployment pipeline |
resilience-patterns |
2013-2017 | Release It! — circuit breakers, bulkheads |
infrastructure-as-code |
2013-2017 | Puppet / Chef / Terraform |
containers |
2013-2017 | Docker / Linux namespaces + cgroups |
ddd-bounded-context |
2003-2012 | Evans DDD: bounded context + ubiquitous language |
legacy-code-seams |
2003-2012 | Feathers Working Effectively with Legacy Code |
continuous-integration |
2003-2012 | Fowler CI; Jenkins / Hudson |
refactoring |
2003-2012 | Fowler 1999 / Opdyke 1992 |
tdd |
2003-2012 | Beck Test-Driven Development |
bdd-gherkin |
2003-2012 | North BDD + Cucumber/Gherkin |
hexagonal-architecture |
2003-2012 | Cockburn Ports and Adapters |
adr |
2003-2012 | Nygard Architecture Decision Records |
property-based-testing |
2003-2012 | QuickCheck (Claessen/Hughes) |
snapshot-testing |
2003-2012 | Approval / golden / snapshot (Falco / Bache) |
event-sourcing-cqrs |
2003-2012 | Greg Young event sourcing + CQRS |
lean-startup |
2003-2012 | Ries build-measure-learn |
agile-manifesto |
1996-2003 | Snowbird 2001 Agile principles |
xp |
1996-2003 | Kent Beck Extreme Programming |
pragmatic-programmer |
1996-2003 | Hunt / Thomas tracer bullets + orthogonality |
code-complete |
1996-2003 | McConnell reference manual |
design-patterns |
1996-2003 | GoF (with over-engineering caveat) |
design-by-contract |
1996-2003 | Meyer OOSC — preconditions / postconditions / invariants |
mythical-man-month |
1996-2003 | Brooks — Conway's Law, no-silver-bullet |
postels-law |
pre-1996 | RFC 793 — robust under input variation |
wiki-knowledge-surface |
pre-1996 | Cunningham wiki — first knowledge surface |
distributed-systems-foundations |
pre-1996 | Lamport / Brewer / leader election / B-trees |
cmm-process-maturity |
pre-1996 | SEI Capability Maturity Model (with bureaucracy warning) |
Slug count: 45.
See also
PRODUCT.md— what AgentOps is as a productGOALS.md— measurable fitness goalsAGENTS.md— operator vault contract for this reposkills/domain/SKILL.md— vocabulary corpus citing this practiceskills/provenance/SKILL.md— artifact lineage and source-chain tracingdocs/domain-practice-packets.md— product-facing packet contractdocs/context-packet.md— runtime context packet contractskills/rpi/references/phase-data-contracts.md— phase handoff contractdocs/architecture/primitive-chains.md— the concrete primitive layers (Mission / Discovery / Risk / Execution / Validation / Learning / Ratchet / Continuity) that compose the practice into chains