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KageOps
kageops-core.mp4

An open-source, autonomous AI dev team — from one-line brief to shipped product.

Sensei orchestrates eight specialist agents (the Autonauts) through a full six-phase product lifecycle: discover → design → build → verify → deploy. Runs on your laptop. Zero Docker. Your keys, your code, your machine — with a hard USD kill-switch you control.

License: AGPL v3 Tests TypeScript Node PRs welcome

Quickstart · Watch it work → · How it works · The Autonauts · Why it's different · Open core · Contributing

▶ Nine narrated how-to videos — real screen captures of the actual app, from first launch to a full run. Watch the series →


The 30-second pitch

You describe what you want. Sensei — the orchestrator — decomposes it into tasks and routes each to the specialist best suited for it. Eight agents plan, write code, run the tests, fix what fails, and hand you a built, verified project — with a live activity feed the whole way and a hard budget cap you set.

Not another chat wrapper. KageOps is a real orchestration engine: task decomposition, phase gates, a build gate that actually runs npm install/build/test, an acceptance gate that checks the output against your brief, tiered retry-with-repair, and non-negotiable cost guardrails.

git clone https://github.com/hmanoor/kageops-core.git && cd kageops-core
npm install && npm run build

# The "wow" — preview a full run. Decomposition + routing. Zero AI spend.
npx tsx src/cli/headless-runner.ts --dry-run \
  --name "TaskFlow" \
  --description "A kanban board with drag-and-drop columns and localStorage. Include #board, #add-task, #columns."
👉 What the dry-run prints (click to expand)
═══ DRY-RUN PLAN (no AI calls, no spend) ═══
  Project:        TaskFlow
  Simple-app:     NO

  Phase plan:
    discovery              full: ~4 task(s)
    poc                    full: ~4 task(s)
    business-viability     full: ~4 task(s)
    design-planning        full: ~4 task(s)
    development            full: ~8 task(s)
    launch-growth          full: ~4 task(s)

  Total tasks:    ~28
  Estimated cost by preset:
    openrouter_budget (DeepSeek/Gemini)      ~$0.13
    ollama (local)                           ~$0.00
═══════════════════════════════════════════

It shows the exact plan Sensei would execute — every phase, every task, and which Autonaut each is routed to — without making a single paid API call.

Ready for real? Point it at a provider and lift the cap:

export OPENROUTER_API_KEY=sk-...            # or ANTHROPIC_API_KEY, or Ollama (fully local), …
KAGEOPS_PRESET=openrouter_budget KAGEOPS_MAX_RUN_USD=0.50 \
  npm run run:headless -- --name "TaskFlow" --description "..."

Prefer a GUI? npm run dev launches the Command Center — Mission Control for watching agents work, intercepting tasks, and reviewing output live.


How it works

Sensei never does task work itself — it orchestrates. It decomposes the brief, routes each task to the right specialist, runs the phase gates, and drives the retry-and-repair loop when something fails.

flowchart LR
    B([Your brief]) --> S{{Sensei<br/>orchestrator}}
    S -->|decompose + route| A[8 Autonauts]
    A --> G1{Build<br/>Gate}
    G1 -->|fails| FIX[Forge<br/>repairs] --> G1
    G1 -->|passes| G2{Acceptance<br/>Gate}
    G2 -->|violations| FIX
    G2 -->|passes| OUT([Built + verified project])
    S -.hard USD kill-switch.-> A
Loading

Every project flows through a six-phase lifecycle, each phase gated by your trust level:

flowchart LR
    D[1· Discovery] --> P[2· POC] --> V[3· Business<br/>Viability] --> DP[4· Design<br/>& Planning] --> DEV[5· Development] --> L[6· Launch<br/>& Growth]
Loading

After development, two automated gates run before anything is called "done":

Gate What it does
BuildVerificationGate Runs the real npm installbuildtest. No green build, no pass.
AcceptanceGate Checks the output against your brief (required elements, preview-URL reachability), with two-tier MUST/SHOULD severity. On failure it spins a repair task for Forge and retries.

Built with KageOps

Real apps the agents built end-to-end — from a brief to a deployed site:

Project What it is Live
DevPulse A full SaaS — Clerk auth + Stripe billing + Neon Postgres, deployed to Vercel devpulse.kageops.dev
Prism A CSS design toolkit / playground prism.kageops.dev

Meet the Autonauts

Nine specialists. Each an expert in one slice of the lifecycle — because eight sharp tools beat one fuzzy one.

Agent Role Owns
🧭 Sensei Orchestrator Decomposition, routing, phase gates, retries — never writes task code itself
🔍 Scout Strategist Research, discovery, concept briefs, cost estimates
📐 Blueprint Architect System + data design
🎨 Pixel Designer UI / UX
🔨 Forge Engineer Implementation + repair
🔐 Cipher Data specialist Schemas, migrations, data flows
🛡️ Aegis Platform engineer Build, deploy, preview
👁️ Vigil Quality guardian Tests + review
📣 Herald Marketer Copy + launch assets

Why KageOps is different

  • 🛑 Agents that spend money answer to a kill-switch. Every real run requires an explicit KAGEOPS_MAX_RUN_USD cap. A budget poller checks spend every 3s and cancels the run before it blows past. Per-task call caps and a zombie-guard back it up. Always --dry-run first.
  • 🧪 It verifies its own work. The build gate runs your actual toolchain; the acceptance gate checks the output against the brief. Failures trigger a bounded retry-with-repair loop, not a shrug.
  • 🏠 Local-first, zero-Docker. An embedded Postgres (PGlite, WASM) boots in-process on first run. No database to install, no containers, no cloud dependency. Your code never leaves your machine.
  • 🔌 Bring your own provider. Claude (API + CLI), OpenRouter, Ollama (fully local, $0), OpenAI, Gemini — swap with a preset. Your provider bill stays on your own account.
  • 🎛️ Watch and steer. The Command Center desktop app streams a live activity feed; intercept, approve, or redirect tasks as they run.

Multi-provider by design

Provider Mode Cost
Claude API or local CLI Metered / subscription
OpenRouter API (DeepSeek, Gemini, GPT, …) Cheapest metered
Ollama Fully local $0
OpenAI API Metered
Gemini API Metered

Quality — the part nobody else ships

  • 6,300+ tests passing across 290+ files, tsc --strict clean throughout.
  • Deterministic guardrails: budget-kill, per-task caps, zombie-guard, path-traversal prevention on all agent file I/O, parameterized SQL only.
  • CI runs build · test · lint · secret-scan (gitleaks + a home-grown scanner) on every PR.

Architecture

flowchart TB
    subgraph UI[Command Center · Electron]
      CC[Mission Control renderer]
    end
    subgraph ENGINE[Engine · TypeScript]
      SEN[Sensei orchestrator]
      BUS[(Event bus<br/>LISTEN/NOTIFY)]
      AG[Autonaut agents]
      AD[Multi-provider<br/>AI adapter]
      GATES[Build + Acceptance gates]
    end
    subgraph DATA[Local-first data]
      PG[(Embedded PGlite<br/>+ pgvector)]
    end
    CC <--> SEN
    SEN <--> BUS
    BUS <--> AG
    AG --> AD
    SEN --> GATES
    SEN <--> PG
    AG --> PG
Loading
Layer Tech
Desktop app Electron 34 + TypeScript
Engine Sensei orchestrator + 8 agents, event bus (Postgres LISTEN/NOTIFY)
Database Embedded PGlite (default) · external Postgres 16 + pgvector (opt-in)
AI Multi-provider adapter (Claude / OpenRouter / Ollama / OpenAI / Gemini)
CLI Headless runner (--dry-run, budget caps, resume)
Tests Vitest · tsc --strict

See docs/architecture/ for the full picture.


What's in this repo (open core)

KageOps is open-core. This repository is the engine and everything you need to run it locally — under AGPL-3.0, free forever:

  • ✅ Sensei orchestrator, the 8 Autonauts, the agent framework
  • ✅ Task decomposition, routing, phase gates, build + acceptance gates
  • ✅ Embedded PGlite database, event bus, headless CLI runner
  • ✅ The Command Center desktop UI
  • ✅ Multi-provider AI adapter + cost guardrails + APO (prompt optimization)

The commercial KageOps Cloud layer — managed cloud compute, team collaboration, hosted identity, billing, and outbound connectors — lives in a separate private repository. The boundary is documented in OPEN-CORE.md, and there are zero open → commercial imports; the engine runs fully standalone. What you pay for is the hosted business, never the engine.


Quickstart

Requires Node 20+. No Docker, no database setup.

git clone https://github.com/hmanoor/kageops-core.git
cd kageops-core
npm install
npm run build

# 1. Preview (no spend)
npx tsx src/cli/headless-runner.ts --dry-run --name "MyApp" --description "..."

# 2. Real run (budget-capped)
export OPENROUTER_API_KEY=sk-...
KAGEOPS_PRESET=openrouter_budget KAGEOPS_MAX_RUN_USD=0.50 \
  npm run run:headless -- --name "MyApp" --description "..."

# 3. Or the desktop Command Center
npm run dev

Cost safety is built in. Real runs require an explicit KAGEOPS_MAX_RUN_USD cap; the budget-kill poller cancels the run if spend approaches it.

How-to guides

Short narrated screen-captures of the real app — no mockups. They're produced by an automated pipeline that drives the actual UI and records it, so every guide is re-cut when the interface changes and can't go stale. Index: docs/how-to.

Episode 01 — First launch & the setup wizard (1:55). Model presets and their cost trade-offs, trust levels, keychain-stored API keys, and the per-run budget kill-switch — ending at your first New Project screen.

2026-07-25-ep01-first-launch-16x9.mp4

Episode 02 — Your first project: writing the brief (1:44). The New Project screen end to end: brief-writing, project types + deployment config, the Phases & Tasks tree, budget and trust, and Dry Run vs Create & Start.

2026-07-25-ep02-first-project-16x9.mp4

Episode 03 — The live run, end to end (2:11). A real supervised run filmed start to finish: six phases, six on-camera approvals, agents working in timelapse, and completion.

2026-07-26-ep03-live-run-16x9.mp4

Episode 04 — What did it build? (1:20). Reviewing the output honestly: Completed tab, artifact browser, the generated code, the build report, and the produced page rendered live.

2026-07-27-ep04-what-it-built-16x9.mp4

Episode 05 — The Command Center tour (1:36). Operating modes, project board, orchestration flow graph, the bottom panel (activity, approvals, logs, build), agent roster, model routing, cost intel, and the Sensei chat dock.

2026-07-27-ep05-command-center-16x9.mp4

Episode 06 — Agents & model routing (1:36). The nine-agent roster and scorecard, per-agent model config, the preset grid with a switch on camera, fallback chains, and custom presets.

2026-07-27-ep06-agents-model-routing-16x9.mp4

Episode 07 — Trust, gates & intervention (1:24). A live run where a gate is approved, the next is denied — and returns after rework — plus pause/resume mid-run and the cascade to completion.

2026-07-27-ep07-trust-gates-intervention-16x9.mp4

Episode 08 — Cost controls (1:57). The budget cap as a hard kill, dry-run-first, the Cost Intelligence ledger, editing a run's cap mid-flight, and the guardrail layers underneath.

2026-07-27-ep08-cost-controls-16x9.mp4

Episode 09 — Headless runner & CLI (2:12). The engine from a plain terminal: env config, the dry-run plan and cost estimate, a live run in timelapse — ending with the acceptance gate refusing to sign off an artifact that missed a required element.

2026-07-28-ep09-headless-cli-16x9.mp4

Contributing

We'd love your help. Read CONTRIBUTING.md — dev setup, conventional-commit + test-coverage bars, and the one-time CLA sign-off (automated on your first PR). All participation is governed by our Code of Conduct.

Security

Found a vulnerability? Don't open a public issue — see SECURITY.md for private disclosure via GitHub Security Advisories.

Acknowledgments

KageOps is built on ideas from the open-source community. With thanks to:

  • graphify — inspiration + the engine behind the in-app Code Graph (turn any input into a navigable knowledge graph).
  • Agent Lightning (Microsoft) — inspiration for APO, KageOps's opt-in Automatic Prompt Optimization loop.
  • caveman (Julius Brussee) — inspiration for Caveman Mode, our terse agent-to-agent prompting that trims inter-agent tokens ~65%.

These projects shaped how KageOps works; any rough edges are ours, not theirs.

License

AGPL-3.0 © KageOps. Contributions are accepted under the project CLA, which preserves the option to offer KageOps under a commercial license alongside the AGPL open core.

Built by the KageOps team · kageops.dev · kageops.ai

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Open-source autonomous AI dev team: Sensei orchestrates specialist agents from idea to shipped product. The engine behind KageOps.

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