The agentic engineering OS
A 50+ agent pipeline that plans, implements, audits, tests, and ships — with reliability guardrails and host-resource governance.
This is the multi-agent system behind bretmcgee.com and my independent engineering work. It is not a slide-deck concept: it runs daily, orchestrating autonomous coding agents across a strict-TypeScript monorepo with real-services quality gates.
The OS treats agent work like production infrastructure — bounded tasks, explicit handoffs, audit checkpoints, and automated verification before anything merges.
Pipeline phases
Five phases map to the agent graph: plan, implement, audit, test, and ship. Each phase has a dedicated agent role and explicit entry/exit criteria.
Phase 1 · Plan
Decompose intent into bounded, verifiable tasks.
A planner agent breaks features into scoped work units with acceptance criteria, dependency order, and disclosure constraints. Long-horizon work is captured in a decision ledger so context survives across sessions.
Phase 2 · Implement
Parallel specialist agents execute in isolated scopes.
Domain specialists (UI, API, tests, infra) work concurrently within guardrails — strict TypeScript, lint gates, and provider-agnostic LLM routing. Subagent monitoring tracks progress and host-resource usage.
Phase 3 · Audit
Independent review before code is trusted.
An auditor agent checks diffs against standards: type safety, accessibility, disclosure policy, and architectural fit. Findings block progression until resolved — no silent drift.
Phase 4 · Test
Verify against real services, not mocks.
Integration and unit tests run against real APIs and backends where possible. Automated lint, typecheck, and test gates must pass before the pipeline advances.
Phase 5 · Ship
Synthesize, commit, and deploy with traceability.
A synthesizer agent reconciles outputs, prepares commits, and hands off to CI/CD. Every merge carries an auditable trail — what changed, why, and which gates cleared.
Production guardrails
Agent throughput only matters if output is trustworthy. These constraints keep long-running orchestration stable and production-safe.
Host-resource governance
Caps on concurrent agents, memory, and run duration prevent runaway orchestration from destabilizing the dev environment.
Disclosure-aware output
Public copy, résumé bullets, and case studies pass automated scans — client names and sensitive metrics stay gated until reviewed.
Reduced-motion paths
Visual pipeline motifs degrade to accessible text lists under prefers-reduced-motion — motion never carries essential information.
Zero-any TypeScript
Strict typing across the monorepo; agents inherit the same standards as human contributors.
At scale
50+ orchestrated subagents are in active production use — not a demo count. Throughput is self-measured; methodology is documented on the about page.
How metrics are measured · Live demo (coming soon)