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Architecture

Brain is a layered system designed to be built one workflow at a time, on top of a runtime that gives us multi-user, multi-thread, tracing, and a web UI out of the box. This section explains the pieces and the choices behind them.

Aggregator + Workflow Registry

The supervisor pattern. How chat, slash commands, and approval clicks all route to the same workflows.

Implementation Tiers

Tier 1 skills, Tier 2 workflows, Tier 3 agents — when to use which.

Runtime

Brain is built on the deer-flow harness. Why, and what it gives us.

Data Integration

Brain’s own Supabase, CutMake’s Supabase, the boundary between them.

UI Structure

The four surfaces — Inbox, Ask, Task, Engine — and what each is for.

Observability

Tracing, correction logging, eval datasets. The feedback loop in detail.

At a glance

The order of build is bottom-up: runtime → data layer → one workflow → observability wired to that workflow → next workflow. The aggregator and registry get scaffolded early (Phase 2) so subsequent workflows compose into them.

What ships with every feature

The architecture isn’t theoretical. Every shipped feature includes:
  • Tracing through the observability stack
  • Correction logging for AI drafts vs. human finals
  • A changelog entry in this documentation
  • A workflow page here that describes it
If any one of those is missing, the feature isn’t done. See Principles #7.
  • Vision — the bet behind the architecture
  • Roadmap — phase order and what’s shipping when