Open-source workflow engine

Durable workflows
for AI agents

Run coding, content, and custom workflows locally. Hive saves outputs, waits for approvals, and can retry interrupted stages.

Workflow examples

Coding Built-in

Nine stages: request → reviewed pull request Historical coding evidence below

  1. Inbox — Hive creates a task folder for the request. Its files become inputs for later stages. idea.md

    Build a scriptable screenshot CLI. Read every note, not just the first page.

  2. Brainstorm — Questions become requirements before implementation starts. brainstorm.md
  3. Plan — The plan records scope, implementation steps, and checks for the next agent. plan.md
  4. Execute — The builder receives the plan and works on the task branch. task.md
  5. Open PR — The change and its context are linked in a draft pull request. pr.md
  6. Review — In the recorded Screenote task, review caught notes disappearing after screenshot 100. reviews/
  7. Artifacts — Save check results and supporting artifacts for the final handoff. artifact.md
  8. Finalize — The PR, review history, and handoff notes stay together. summary.md
  9. Done — The task is archived with its artifacts. Completion does not promise an automatic merge. summary.md

Result: Reviewed pull request.

Writing Honeycomb

Seven stages: evidence → draft → editorial revisions → article Installable Writing Honeycomb · v1.0.2

hive workflow install honeycomb/writing
Writing 1.0.2 source · Install and configure

  1. Inbox — Specify the reader, angle, voice, freshness date, and sources the article must cover. brief.md

    For small teams: explain what a successful backup does—and does not—prove about recovery.

  2. Repo research — Inspect relevant repository files. Keep path-and-line references, candidate claims, and gaps that need external verification. repo-research.md
  3. Web research — Open the sources behind external claims. Record URLs, authors, dates, credibility limits, and unresolved questions. web-research.md
  4. Research — Synthesize the two research files into an outline and a claim map: supported, qualified, disputed, or unsupported. research.md
  5. Draft — Use brief.md and research.md to write a complete draft. Material factual claims must trace back to the source ledger. draft.md
  6. Editorial — A grounding editor checks claim support. An adversarial editor checks the argument and usefulness. The council can revise and recheck for up to five rounds. editorial.md
  7. Deliver — Write article.md and verification.md with claim support, revision deltas, editorial rounds, and the terminal reason. Delivery does not publish the article. article.md

Result: article.md with verification.md. This sample reaches editorial consensus. The real workflow can instead return a NOT PUBLISHABLE notice for unsupported claims or the five-round limit.

Architecture Honeycomb

Eight stages: repository + web evidence → reviewed architecture Installable Architecture Honeycomb · v1.0.4

hive workflow install honeycomb/architecture
Architecture 1.0.4 source · Install and configure

  1. Inbox — An idea is the outcome you want. Start in plain language; the workflow investigates what it will take. brief.md

    I want to run Hive in the cloud. Let people connect a repository, start a workflow, and come back to the result without leaving their laptop running.

  2. Repo research — Inspect how Hive starts agents, stores task state, uses worktrees, and handles credentials. Record the code evidence and what still needs investigation. repo-research.txt
  3. Web research — Check primary documentation for long-running workers, persistent storage, credential handling, and recovery. Save sources and limits for each option. web-research.txt
  4. Research — Read both evidence collections. Synthesize only what changes the decision; do not silently turn gaps into facts. research.md
  5. Draft — Describe components, data flow, failure paths, alternatives, rollout, rollback, and tests. Tie material decisions to the saved evidence. draft.md
  6. Review — Two reviewers examine missing evidence, tradeoffs, interfaces, and operational risks. The council can revise and recheck within a two-round limit. review.md
  7. Architecture — Write the final architecture with traceable evidence, a test plan, owner decisions, and resolved, deferred, or rejected reviewer findings. architecture.md
  8. Done — Done is inert: no additional agent runs. The final design and its research and review trail remain together. architecture.md

Result: architecture.md with owner decisions and reviewer findings. The design includes isolated workers, saved task state, and a recovery test plan. Tenant isolation and operating costs still need validation before launch.

Artifacts remain saved when an attempt stops. Recovery can retry an eligible stage from recorded state; some failures need human intervention. Read about durability and recovery.

Also built in: the separate content workflow and Bench for evaluation campaigns. Or install a reviewed Honeycomb.

Task state and recovery

Saved artifacts

Stages write files such as research.md and outline.md. Later stages use those files; task history records the attempts.

research.md→ outline stage

Human approval

A human stage waits for a named decision, such as approving a report or sending the same task back for revision.

Waiting for your approval

Stage retry

A retry reruns the stage with its saved inputs. Recovery checks determine whether it can continue or needs human intervention.

Attempt 1 stopped→ attempt 2

Recovery behavior and limits →

Choose agents by stage

Use different agents for research, writing, or code review. Choose an agent and model for each stage.

Configure your agents →

See the setup guide for each agent’s installation and model requirements.

Reusable workflows: Browse reviewed Honeycombs →

Recorded coding run · Screenote

Two API bugs
found in review

Screenote’s screenshot CLI fetched only the first page of notes and hid rate-limit and server errors. Review sent both findings back for fixes.

Inspect merged PR #36 ↗

Recorded evidence, not a live run. Targeted API and Go checks passed; the full Rails suite was blocked by missing libvips. OAuth followed in PR #37.

Finding → fix → recheck From the task history

Review pass 1

Notes missing after screenshot 100

The CLI fetched only the first page. The fix paginated the full result.

Review pass 2

API errors returned exit 0

Rate limits and server errors were swallowed. The fix surfaced failures instead of returning incomplete results with exit 0.

Custom workflows

Define stages in YAML

Use a YAML descriptor to set stage instructions, output files, and human decisions.

This minimal custom gate is separate from the Writing and Architecture Honeycombs above. Here, research.md feeds report.md. Approval completes the report; rejection returns the task to synthesis. Neither publishes or sends it.

Build a custom workflow →
research-report.ymlCustom example
id: research-report
stages:
  - name: research
    kind: agent
    state_file: research.md
    instruction: ./research-report/research.md
  - name: synthesis
    kind: agent
    state_file: report.md
    instruction: ./research-report/synthesis.md
  - name: approval
    kind: human
    state_file: approval.md
    input: report.md
    outcomes:
      approve: { complete: true, artifact: report.md }
      reject: { to: synthesis }

Run locally

Install Hive

Open the local web UI, terminal UI, or CLI.

1. Install the CLI

macOS · Homebrew
brew install ivankuznetsov/hive/hive
Arch Linux · AUR
yay -S hive-bin
Linux · glibc x86_64 / aarch64
tmpdir="$(mktemp -d)" && trap 'rm -rf "$tmpdir"' EXIT \
  && curl -fsSL https://raw.githubusercontent.com/ivankuznetsov/hive/v0.8.0/install.sh \
       -o "$tmpdir/hive-install.sh" \
  && bash "$tmpdir/hive-install.sh"

Current release: v0.8.0. Native install requires Ruby 3.4, Git, and your configured agent CLIs. Coding also uses authenticated gh. Full prerequisites →

2. Open your project

hive setup
cd ~/Dev/your-project
hive init .
hive web status

Setup provisions the local services. Open the reported loopback URL, use hive tui, or drive tasks from your agent.

Follow the quickstart

Hive is MIT-licensed. Agent usage is billed by your providers or subscriptions; multi-agent coding can be token-heavy.

Hosted HiveDev

A hosted product built on Hive. Coming soon.

Join the HiveDev waitlist ↗