Hive Commons

Human judgment is the scarce resource.

Hive Commons is an open source organization focused on one problem: making software teams more productive now that AI coding agents can do real work. Every tool here exists to move mechanical work off people and onto agents, without giving up governance, auditability, or accountability.

Hive is the flagship, a control layer for running governed fleets of AI coding agents against real repositories. Spektacular (Spek) gives an agent a spek, a plan, and a reviewable implementation. Around them, hotshot, pluk, promptargs, rationguard, and dibs each remove a specific piece of friction from working with agents.

What Hive does

Hive is a control layer for running governed fleets of AI coding agents against real repositories. Agents pick up issues, open pull requests, review code, repair CI, and answer contributors, under a six-level maturity model that decides exactly what they may do and enforces it in code rather than prompts.

Hub and spokes

Hive ships as a single Go binary that runs as a standard Kubernetes workload, a Docker Compose stack, or Podman Quadlet units. An optional hub coordinates many self-hosted spoke hives, with a public registry, The Commons, team leaderboards, and cross-hive contribution routing.

Governance enforced in code

Trust is dialed up one capability at a time through ACMM, the AI-native Capability Maturity Model. Its six levels scope what an agent may do, from advisory only through to merging on green CI; below L6, hive-owned PRs are gated with the hive-specific hive-pause label.

Audited and accountable

Every action is audited, every agent identity belongs to a named human, and humans keep all approval authority. A deterministic pipeline handles filtering, classification, and merge-gating before any LLM sees the work, so agents only handle judgment calls.

merged pull requests
5,600+
median issue close time
3 hours
counting since
April 2026

Hive maintains its own repository. These are its figures.

Adopted by

KubeStellar Console, tunaos.org, and Project Bluefin run Hive in production. The others are pre-production. Listed in ADOPTERS.md.

Six ACMM levels, from advisory to fully autonomous

L1 · #1

L1 Inception

This is where Spek comes into play: raw ideas become a spek, a plan, and project inception material. The advisor helps with setup and architecture decisions, but the level stays advisory only.

  • Who acts: Spek and the named human owner.
  • What opens: Specs, plans, and project inception notes.
  • Human role: Direction, approval, and all execution choices.
L2 · #2

L2 Advisory

Agents report findings to the dashboard and to the advisory tracking issue as comments. Humans decide what to act on, and agents do not open pull requests at this level.

  • Who acts: Advisory agents observe and comment.
  • What opens: Dashboard findings and advisory issue comments.
  • Human role: Triage every finding and choose the work.
L3 · #3

L3 Quality-Gated

Trust is built by automating 90%+ of quality tests through optimized CI. The quality agent opens issues and hold-gated pull requests while other agents remain advisory.

  • Who acts: Quality agent plus advisory agents.
  • What opens: Issues and hold-gated pull requests for tests, coverage, and CI.
  • Human role: Review, approve, and remove holds.
L4 · #4

L4 Security-Aware

Trust is built by finding vulnerabilities and CVEs, and sec-check joins the fleet. All delivery agents may file issues, while quality, sec-check, and ci-maintainer may open hold-gated pull requests.

  • Who acts: Delivery agents, quality, sec-check, and ci-maintainer.
  • What opens: Security issues and hold-gated quality or CI pull requests.
  • Human role: Decide risk, review fixes, and lift holds.
L5 · #5

L5 Semi-Autonomous

All agents can open issues and hold-gated pull requests. The reviewer agent works the PR queue before humans batch-review, approve, and remove holds.

  • Who acts: All agents plus the reviewer agent.
  • What opens: Hold-gated pull requests across the work queue.
  • Human role: Batch-review, approve, and release ready work.
L6 · #6

L6 Fully Autonomous

Agents open pull requests and auto-merge on green CI. The reviewer agent is the gate: verdicts that require human attention pull a pull request out of the auto-merge lane.

  • Who acts: Agents open work and reviewer gates it.
  • What opens: Pull requests that auto-merge after green CI.
  • Human role: Handle exceptions and reviewer escalations.

Works with the coding agents your team already uses: Claude Code GitHub Copilot Codex Gemini Goose Bob and OpenAI-compatible self-hosted gateways.

The project family

Hive is the orchestration system and the delivery surface for the family. Each tool beside it removes a specific piece of friction from working with agents, and each is useful on its own.

Documentation for every project is single-sourced from its repository to docs.hivecommons.dev.

How the pieces fit

Spek handles one feature at a time. Hive is where that work is scaled up.

One feature: a Spek workflow

A markdown spek becomes a reviewed plan and an agent-driven implementation. Spec, plan, and implement each run as a resumable state machine, so you can stop, inspect, edit, and resume without losing work.

Its artifacts are the spek, the plan, and the changelog record.

A fleet: Hive schedules it and keeps the record

Hive orchestrates fleets of coding agents across repositories, with the governance and audit trail that running agents at that scale demands. A Spek workflow is the unit of work a fleet orchestrator schedules.

Those same artifacts are the audit trail that makes an agent's output reviewable rather than merely plausible.

An open community

Every repository in the organization is Apache 2.0 licensed, requires DCO sign-off on every commit, and follows the CNCF Code of Conduct. Hive is maintained by a three-member Maintainer Committee spanning three organizations, with a documented contributor ladder and explicit governance for AI-agent contributions.

Hive was incubated inside KubeStellar, a CNCF Sandbox project. Hive Commons has applied to the CNCF Sandbox as a project of its own, and the application is in progress.

Follow the CNCF Sandbox application

Supported integrations

Works with the agents and inference engines you already use

See all integrations →

Hive supports source-control, work-source, sign-in, agent CLI, inference-engine, and model-gateway integrations. This list describes supported software integrations and does not imply endorsement or partnership unless marked Partner. TypeSafe AI is a Hive Commons partner.