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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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usage.md
+13 -6
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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
```