# I built an AI team that ships real work — and shows you the conversation

> Source: <https://dev.to/forifor/i-built-an-ai-team-that-ships-real-work-and-shows-you-the-conversation-251a>
> Published: 2026-09-12 15:44:18+00:00

Most "multi-agent" demos are bots narrating to each other. The log is the product; the work is secondary. I wanted the opposite: one request in, real files out, and a trail I could audit afterwards.

**Agent Team** is an open-source (MIT), local-first runtime where a Master plans, a Researcher / Builder / Reviewer actually do the work, and you get the artifacts **plus** the real bot-to-bot messages, a timeline, and verification bound to each artifact revision.

Repo: [https://github.com/FORIFOR/Multibot](https://github.com/FORIFOR/Multibot) · Site + 59s intro: [https://forifor.github.io/Multibot/](https://forifor.github.io/Multibot/)

`message.sent` events — messages that were really delivered to another bot's mailbox. A question from the Builder wakes the Researcher, which answers with `reply_to`. Acknowledgements never wake a model.
The default connection runs every agent session through the local `claude -p`. Claude Code owns the loop for one session; the team's tools (`send_message`, `publish_artifact`, `run_check`, …) are exposed to it as MCP tools through a small stdio proxy that forwards each call to the runtime's ToolGateway. Policy, budget and the event log are identical to the API path; Claude Code's own built-in tools are disabled for these sessions. Cost and usage are read from the CLI's JSON result, and the model it actually used comes from `modelUsage`, never from the model's own claims.

Claude API (official SDK), any OpenAI-compatible chat endpoint and local Ollama work the same way, per bot.

On 2026-09-13 I ran this request through the local Claude Code CLI: *"From this product description, build a Japanese launch page and three social-post drafts. Record assumptions for anything missing. Stop before publishing. Have the Reviewer verify."*

| Model (reported by the provider) | `claude-opus-5` | 
| Plan | Master chose 1 builder task + 1 reviewer task and skipped the researcher; 8 recorded assumptions (no prices, no invented numbers, placeholder URLs only) | 
| Deliverables | `index.html` (single-file page),`posts.md` ,`HANDOFF.md` ,`final-report.md` | 
| Verification | 10 programmatic checks → all pass; reviewer verdict 6/6, plus 4 optional findings sent back as a real message | 
| Usage | 39 model turns · 35 tool calls · $1.66 list-price equivalent · 18 min 37 s | 
| Status | completed | 

The generated files, the final report and the 77-event JSONL log are committed under `docs/evidence/` without edits. Four runs total: run 1 finished *partial* and exposed a bug (a reviewer verifying two tasks had only its last verdict applied — fixed), runs 2–3 hit limits that were then tuned. One request is not a benchmark, and the prompts are original seeds.

The demo video on the site drives the real UI and runtime with a **scripted test provider** (labelled on screen) so it is deterministic and free to reproduce.

Stack: Python 3.12 / FastAPI / SQLite (WAL, append-only events, SSE), React + TypeScript. macOS seatbelt sandbox for builder commands (no network, writes only inside the task workspace); elsewhere a plain subprocess that says so in every result.

```
git clone https://github.com/FORIFOR/Multibot && cd Multibot
cd backend && uv venv .venv --python 3.12 && uv pip install --python .venv/bin/python -e '.[dev]'
cd ../frontend && pnpm install && pnpm build && cd ../backend
.venv/bin/agentteam probe    # real capability check through `claude -p`
.venv/bin/agentteam serve    # http://127.0.0.1:8787
```

I'd love feedback on two things: whether the review → revise → re-review loop bound to revisions holds up on your tasks, and where "fewer messages, more evidence" (workers get their task, artifact refs and inbox — not the history) breaks down.