> ## Documentation Index
> Fetch the complete documentation index at: https://docs.gdilabs.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Multi-agent workforce

> Cerebrum runs as a team, not a single agent. Each request is classified, routed to the right specialist, executed, and verified — all without you needing to manage the choreography.

## How a request flows

1. **Classify.** A fast free-model agent reads your request and decides what kind of work it is.
2. **Plan.** A managerial agent (architect, tech lead, release manager, or a QA / security lead) sketches the approach.
3. **Execute.** A paid-model executor produces the actual output — code, document, decision.
4. **Verify.** An acceptance agent checks the result against the original ask. Pass/fail, with deltas.

If something fails, Cerebrum retries within the same level up to three times before moving the work up to a more capable agent.

## Why a team

* **Specialization beats generalization.** A planning agent uses different prompts and tools than an executor. Forcing one agent to do both leaves quality on the table.
* **The right tool for the work.** Free models handle classification and verification fast and cheap. Paid models earn their cost only on the hard problems. Cerebrum decides per step.
* **Escalation, not retry-spam.** When a level can't resolve a conflict, the work moves up — to a more capable agent — rather than burning attempts at the same level.

## What you see

* A streamed view of every step. As an executor produces tokens, you see them live.
* An audit log of every classification, escalation, and verification decision.
* A cost breakdown per job, broken out by model.