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The supervised AI operating model for software teams.

Three supervised peer loops across the full SDLC — mechanical gates the agent cannot bypass, cold-read specialist reviewers, and human checkpoints it cannot self-certify past.

Reversible. One command to try, one to remove.

An unattended loop makes unattended mistakes.

Agent coding tools have moved the leverage from the prompt to the loop. But a loop running unattended is also a loop making mistakes unattended — and it will self-certify its way out of every check you give it. The answer is not a tighter prompt. It is a supervised loop with mechanical gates the agent cannot bypass.

Three supervised peer loops. One handoff chain.

  1. Discovery Loop

    product-engineering · discovery-lead

    Raw idea → ratified brief. Five candidate shapes explored in parallel, collapsed through product, UX, architecture, and safety lenses.

    Human gate. G3 — you approve a ratified decision brief, not a validated solution.

    Read the discovery journey
  2. Build Loop

    core · work-loop

    Spec → shipped code. Lint, typecheck, and tests must pass. Three specialist reviewers each read the diff cold, in a fresh session — adversarial by design.

    Human gate. G4 — you merge only when adversarial review is clean and all gates pass.

    Read the build journey
  3. Release Loop

    release-engineering · release-lead

    Built → production. Autonomous e2e convergence on ephemeral environments. Deployed findings feed back to the build loop automatically.

    Human gate. G5 — prod ship always surfaces to a human. Always.

    Read the release journey

Every loop surfaces to you at exactly the right moment.

Not as a workaround — as a design principle. The agent runs the loop; you control the gates. Here is what each handoff asks of you.

  • G0Discovery

    Go / No-go

    Is this idea worth exploring?

  • G1.5Discovery

    Shape sign-off

    Does the chosen shape fit the product strategy?

  • G2Discovery

    Brief ratification

    Is the decision brief complete enough to build from?

  • G3Discovery → Build

    Handoff to build

    Is this brief specific enough to spec?

  • PlanBuild

    Plan approval

    Is the plan's trio correct? Do the risk triggers fire?

  • G4Build

    PR merge

    Is adversarial review clean? Does the spec match the implementation?

  • G5Release

    Prod ship

    Is this safe to put in front of users?

Explore a full journey

One install. Every major agent.

AgentSkillsSubagentsHooksCommands
Claude CodeYesYesYesYes
CodexYesYesYesNo
CursorYesYesYesNo
CopilotYesYesYesNo
Gemini CLIYesYesYesNo
Kiro IDEYesYesYesNo
Kiro CLIYesYesYesNo

Switch adapters with one flag. Your skills, subagents, and hooks project into the layout each agent expects.

Start in one command.

pip install agentbundle
agentbundle install --pack core
agentbundle install --pack core
agentbundle install --pack product-engineering --scope user
agentbundle install --profile inception
agentbundle install --profile solution-architect

One command lands the loop. Any agent that reads a skill file inherits it automatically.

The catalogue.

A curated library of packs — each shaped through practitioner research and RFC governance. Start with the loops.

  • Core

    repo

    The build loop. work-loop, new-spec, bug-fix, four specialist reviewers, hooks. Install this even if you install nothing else.

    agentbundle install --pack core

    Read the journey
  • Product Engineering

    user

    The discovery loop. discovery-loop, frame-intent, de-risk-intent, decompose-intent, voice-and-microcopy, align-value-stream.

    agentbundle install --pack product-engineering --scope user

    Read the journey
  • Release Engineering

    repo

    The release loop. release-loop, release-lead. Autonomous e2e convergence. Hard-depends on core.

    agentbundle install --pack release-engineering

    Read the journey
See all 17 packs

Install once, works across all your repos user

  • Product Strategy

    The strategy seat — SWOT, Porter, PESTLE, OKR cascade, PRFAQ, plus UX and content strategy.

  • Desk Research

    Evidence-grounded research — surveys, source maps, competing-hypothesis analysis.

  • Experience Design

    The full design thread — journey to realization, WCAG-aware quality floor.

  • Architect

    System design — design docs, diagrams, architecture review.

  • Contracts

    API-first design — OpenAPI 3.1 and AsyncAPI contracts.

  • Converters

    Document conversion — PDF/DOCX/PPTX ↔ Markdown, HTML, Office, Mermaid.

  • Credential Brokers

    Credential resolution — env → OS keyring → dotfile. Cleartext never reaches the model.

  • Atlassian

    Jira and Confluence from the agent — flow and DORA metrics, SSO-cookie auth.

  • Figma

    Read and render Figma designs — files, nodes, variables, FigJam → Mermaid.

Install per project repo

  • IaC (Terraform)

    Plain-language intent → governed, cloud-agnostic Terraform. Human-gated; stops at plan.

  • Governance Extras

    Decision trail — new-rfc, new-adr, update-conventions for long-lived repos.

  • User Guide (Diátaxis)

    Docs scaffold — Diátaxis skeleton with new-guide.

  • Monorepo Extras

    Package scaffolding — new-package, example package template.

  • Catalogue Curation

    Grow the catalogue — assimilate primitives, survey repos, propose packs, export forks.

Make it your team's operating model.

Adopt the catalogue as-is, or fork it as your own. Write your house conventions and review standards into core, add skills for your stack, and ship one catalogue every engineer installs in a single line — the loop, the reviewers, and the standards come out identical on every machine and in every agent.

How to build your org's catalogue