Structure the request
Turn a natural-language goal into scope, constraints, and acceptance criteria.
MULTI-AGENT ENGINEERING CONTROL PLANE
Run AI like an engineering team, not another chat window.
Choose developer and reviewer models independently. Pi partitions the work across parallel sub-agents and connects requirements, gates, review, merge, and release in one observable delivery chain.
LIVE ORCHESTRATIONOne run. One accountable loop.
01
RequestStory
02
PlanPlanner
03
BuildSub-agents
04
GateChecks
05
ReviewReviewer
06
ReleasePublish
↳ round 2 · repair
01Model roles
Choose Developer and Reviewer independently
02Parallel isolation
A dedicated worktree for every sub-agent
03Gates first
typecheck · lint · test before AI review
04Human control
Approval precedes merge and release
01 — MODEL ROUTING
Implementation speed and review judgment
don't need the same model.
Pin a provider and model to each role for every run. Let an implementation model focus on code while an independent reviewer examines a controlled snapshot—without asking the author to grade its own work.
Developer modelDeepSeekanalyze · edit · test
PiROLE ROUTER
Reviewer modelOpenAIindependent snapshot · structured findings
provider/modelimmutable per runverified credentials
02 — DELIVERY GRAPH
From one request to an accepted release.
The Planner maps complexity and dependencies. Sub-agents execute in conflict-free waves. The Integrator assembles their work, deterministic gates run, and only then does independent review begin.
PASSED
Partition and parallelize
Build dependency waves and isolated branches without file conflicts.
Integrate and gate
Assemble changes, then run typecheck, lint, and test commands.
Review independently
Return structured findings and route scoped issues into the next repair round.
Approve and release
Keep a Human Gate before explicit merge and environment promotion.
03 — OBSERVABILITY
Every agent, repair round, and decision in one operational view.
The real console exposes six workflow nodes, the live event stream, model roles, check results, and the Reviewer → Developer repair loop.
04 — CONTROL PLANE
Put autonomy inside engineering boundaries.
Agents work in server-controlled Git directories. Paths, tools, plugins, budgets, deadlines, model credentials, and release actions have explicit constraints and auditable outcomes.
Isolated execution
Every task gets a worktree; overlapping files never share a parallel batch.
Determinism first
Failed checks block reviewer spend and send concrete evidence back to repair.
Convergence controls
Finding fingerprints, round limits, and decision briefs prevent endless loops.
Explicit release
Review approval still requires a Human Gate; merge and publish remain separate actions.
EXPLORE THE SYSTEM
Not a feature pile.
A delivery discipline.
01
Parallel multi-agent development
See how PiGO maps dependencies, builds conflict-free execution waves, and runs sub-agents in isolated Git worktrees before controlled integration.
02Model-separated code review
Assign distinct Developer and Reviewer models, run deterministic gates first, and review a controlled code snapshot with structured, traceable findings.
03Requirements to acceptance
Structure natural-language requests into Story goals, scope, constraints, and acceptance criteria that stay connected to planning, checks, review, and release.
04Secure agent execution
Learn how PiGO constrains agent execution with registered server workspaces, path controls, isolation, plugin policy, encrypted credentials, and audit events.
05Staging-to-production promotion
PiGO separates Human Gate, merge, release request, staging verification, and production promotion while checking the same commit and image digest.
OPEN SOURCE · AGPL-3.0
Give the next request to an AI engineering team you can direct.
Read the source, inspect the workflow, or deploy PiGO on your infrastructure.
Open the GitHub repository