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docs: add the full build-session video, count 22 agents, ground resource usage

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Add the 2.5-hour 'Working with RoboCo' build session (a conversation to a
shipped feature) as a second hero thumbnail beside the 26-min intro.

Update the agent count from 20 to 22 across the README, CLAUDE.md, usage,
the base agent prompt, the how-to guide, and the org-structure RAG doc:
the standing org gains the PR Reviewer (board-level, read-only), and the
on-demand Intake and Secretary are now counted. The org-structure doc
gains the PR Reviewer in the hierarchy, count table, board team, and
communication matrix. The historical 0.1.0 changelog entry is left as-is.

Rewrite the resource-usage section: drop the unmeasured per-agent RAM
ceiling (RAM is low and agents run few-at-a-time) and lead with storage —
the image set's shared base layer — which is what docker prune reclaims.
This commit is contained in:
Renn F
2026-06-16 18:12:39 +02:00
parent a9fc870415
commit df5e579916
6 changed files with 57 additions and 33 deletions
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CLAUDE.md
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@@ -15,7 +15,7 @@ keep copyright assignment language intact. See `CONTRIBUTING.md`.
## Project Overview
**RoboCo** is an AI Agentic Company - a virtual organization of 20 AI agents + 1 human CEO, designed to operate as a complete software development workforce. The system implements a structured organizational hierarchy with formal communication protocols, task management, and quality controls.
**RoboCo** is an AI Agentic Company - a virtual organization of 22 AI agents + 1 human CEO, designed to operate as a complete software development workforce. The system implements a structured organizational hierarchy with formal communication protocols, task management, and quality controls.
### Core Architecture
README.md
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@@ -1,14 +1,25 @@
# RoboCo
AI Agents Company - A virtual organization of 20 AI agents + 1 human CEO, designed to operate as a complete software development workforce.
AI Agents Company - A virtual organization of 22 AI agents + 1 human CEO, designed to operate as a complete software development workforce.
<p align="center">
<table align="center">
<tr>
<td width="50%" align="center">
<a href="https://www.youtube.com/watch?v=t1QNqJgBmkM">
<img src="https://img.youtube.com/vi/t1QNqJgBmkM/maxresdefault.jpg" alt="Watch the 26-minute RoboCo intro on YouTube — what it is, a walkthrough, and how to use it" width="80%">
<img src="https://img.youtube.com/vi/t1QNqJgBmkM/maxresdefault.jpg" alt="Watch the 26-minute RoboCo intro on YouTube — what it is, a walkthrough, and how to use it" width="100%">
</a>
<br>
<sub>▶ <b><a href="https://www.youtube.com/watch?v=t1QNqJgBmkM">Watch the 26-min intro on YouTube</a></b> — what it is, a walkthrough, and how to use it</sub>
</p>
<sub>▶ <b><a href="https://www.youtube.com/watch?v=t1QNqJgBmkM">Watch the 26-min intro</a></b><br>what it is, a walkthrough, and how to use it</sub>
</td>
<td width="50%" align="center">
<a href="https://www.youtube.com/watch?v=xige_EUIjIA">
<img src="https://img.youtube.com/vi/xige_EUIjIA/maxresdefault.jpg" alt="Watch the 2.5-hour Working with RoboCo build session on YouTube — taking a conversation all the way to a shipped feature" width="100%">
</a>
<br>
<sub>▶ <b><a href="https://www.youtube.com/watch?v=xige_EUIjIA">Watch the 2.5-hour build session</a></b><br>a conversation → a shipped feature</sub>
</td>
</tr>
</table>
<p align="center">
<img src="docs/videos/panel-teaser.gif" alt="Twelve-second looping preview of the RoboCo control panel — the org tree, a task in progress, and an approval queue." width="80%">
@@ -240,7 +251,7 @@ uv run mypy roboco/
- [x] Database ORM (SQLAlchemy async)
- [x] Task lifecycle state machine
- [x] Multi-agent workspace management
- [x] Agent prompts (20 agents)
- [x] Agent prompts (22 agents)
- [x] Messaging API
- [x] Task API with full lifecycle
- [x] Git operations API
agents/prompts/base.md
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@@ -1,6 +1,6 @@
# RoboCo Agent — Base
You are an agent in **RoboCo**, an AI company with 20 AI agents + 1 human CEO. Your role-specific prompt names your verbs and your responsibilities; this file holds the rules every role obeys.
You are an agent in **RoboCo**, an AI company with 22 AI agents + 1 human CEO. Your role-specific prompt names your verbs and your responsibilities; this file holds the rules every role obeys.
## Identity
docs/how-to.md
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@@ -2,7 +2,7 @@
![Twelve-second looping preview of the RoboCo control panel — the org tree, a task in progress, and an approval queue.](videos/panel-teaser.gif)
RoboCo is a virtual software company — 20 AI agents and one human: you. Not a
RoboCo is a virtual software company — 22 AI agents and one human: you. Not a
swarm of bots, not a framework to wire together — an **organization**, with
roles, a chain of command, formal reviews, and sign-offs. You don't micromanage
it; you run it like a CEO. Drop work in at the top and the company carries it all
@@ -10,7 +10,7 @@ the way through planning, building, review, and documentation, then brings it
back to your desk for the final word. You act at the two ends; the organization
fills in everything between.
What keeps twenty agents from dissolving into noise is that RoboCo is
What keeps twenty-two agents from dissolving into noise is that RoboCo is
relentlessly opinionated about *how* work happens: everything is a task, no task
moves without acceptance criteria, and every task walks the same strict lifecycle
— built, QA'd, documented, PM-reviewed, approved — each step gated by role. The
@@ -260,7 +260,7 @@ for a demo — it's a real page RoboCo's agents shipped to RoboCo's own control
panel. A company building its own product, in front of you, is the whole point of
RoboCo. What makes that hold together isn't a clever model or a lucky run; it's
the **organization** — the roles, the gated lifecycle, the reviews and the
sign-offs that keep twenty agents moving as a company instead of a crowd. Run
sign-offs that keep twenty-two agents moving as a company instead of a crowd. Run
as many of these passes as you like, across as many projects as you like.
---
docs/rag/architecture/org-structure.md
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@@ -5,38 +5,43 @@
```
CEO (Renzo - Human)
|
+-- Board (3 agents)
+-- Product Owner
+-- Head of Marketing
+-- Auditor (silent observer)
|
+-- Main PM
|
+-- Backend Cell
+-- Frontend Cell
+-- UX/UI Cell
+-- Board (4 agents)
| +-- Product Owner
| +-- Head of Marketing
| +-- Auditor (silent observer)
| +-- PR Reviewer (read-only safety check on PRs)
|
+-- Main PM
|
+-- Backend Cell
+-- Frontend Cell
+-- UX/UI Cell
```
## Agent Count
| Role | Count |
|------|-------|
| CEO | 1 (human) |
| CEO | 1 (human — not counted in the 22) |
| Product Owner | 1 |
| Head of Marketing | 1 |
| Auditor | 1 |
| PR Reviewer | 1 |
| Main PM | 1 |
| Cell PMs | 3 |
| Developers | 6 (2 per cell) |
| QAs | 3 (1 per cell) |
| Documenters | 3 (1 per cell) |
| **Total** | **20** (19 AI + 1 human) |
| Prompter (Intake) | 1 (on-demand) |
| Secretary | 1 (on-demand) |
| **Total AI agents** | **22** |
## On-Demand Roles (Human-Facing)
Two roles sit outside the standing delivery org above. They are **human-only**,
**spawned on demand** as live chat sessions, and are not part of the 20-agent
count:
Two of the 22 — the Prompter (Intake) and the Secretary — sit outside the
standing delivery org above. They are **human-only** and **spawned on demand**
as live chat sessions; they are counted among the 22, but unlike the standing
org they have no lifecycle verbs and no outward agent comms:
| Role | Purpose |
|------|---------|
@@ -59,7 +64,7 @@ Neither has lifecycle verbs or outward agent comms. See
| Team | Members |
|------|---------|
| executive | ceo |
| board | product-owner, head-marketing, auditor |
| board | product-owner, head-marketing, auditor, pr-reviewer-1 |
| management | main-pm, be-pm, fe-pm, ux-pm |
| developers | all devs |
| qa | all QAs |
@@ -80,6 +85,7 @@ Each role can communicate with:
| CEO | Everyone |
| Board | CEO, other board, Main PM |
| Auditor | Everyone (silent read all) |
| PR Reviewer | Read-only; posts one change-request on the PR itself, no agent comms |
| Main PM | CEO, Board, Cell PMs |
| Cell PM | Main PM, cell members |
| Cell Members | Cell PM, other cell members |
usage.md
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@@ -4,7 +4,7 @@ Operating the AI company after deployment.
## The Organization
20 AI agents organized as a company:
22 AI agents organized as a company:
```
CEO (You)
@@ -235,12 +235,19 @@ docker logs -f roboco-agent-be-dev-1
### Resource Usage
Each agent container uses ~500MB-2GB RAM depending on context. With 128GB RAM:
- 3 agents: ~6GB
- 6 agents: ~12GB
- 20 agents: ~40GB (the intake interviewer is on-demand — it only runs while you're drafting a task)
RAM is modest. Agent containers are spawned on demand and torn down when
their work is done, so you rarely have more than a handful live at once — and
the on-demand Intake and Secretary only run while you're interacting with them.
Steady-state memory is dominated by the standing services (Postgres, Redis,
and especially Ollama with its models loaded), not by the agents.
Storage is the larger footprint: the built (or pulled) image set. The agent
images all share a common base layer, so on disk they cost far less than their
nominal sizes added together. `docker system prune` reclaims old image versions
and stopped agent containers.
Monitor with:
```bash
docker stats --filter "name=roboco-agent"
docker stats # live RAM / CPU per running container
docker system df # image / container / build-cache disk usage
```