AI & Brain Overview

What is the Brain?

The Brain is Connie’s AI orchestration engine. Every AI feature you see — the inbox reply suggestions, the workflow LLM nodes, the slash-AI on pages, the copilot you chat with — routes through it. In one sentence: you send the Brain a message, it picks the right model, runs whatever tools it needs across Temporal, and streams the answer back as it’s being produced.

Dual-model orchestration. Connie isn’t single-vendor. The Brain blends models from Anthropic (Claude Opus 4.6, Sonnet 4.6) and OpenRouter (GPT-4o family, Gemini, others) — picked per request based on intent, latency, and cost.

How a request flows

When something — a user, a workflow, or another module — calls the Brain:

Budget + cache check

The Brain checks your workspace credit balance and looks up the FAQ cache for a quick exact-match hit. A standalone question with no context, no mentions, and no attachments may return instantly from cache.

Plan

For a multi-step request, the Brain writes an agent plan — a list of sub-tasks with the tools and model each will use. The plan streams to the UI so you can watch it being built.

Execute

A Temporal workflow runs the plan: calls tools, runs sub-models, accumulates state. Each step’s result is streamed via Supabase realtime so the UI updates token-by-token.

Return

The final response is persisted to the conversation, credits are deducted, and tokens are tallied for usage tracking.

Why Temporal?

Long-running AI work is hard. A research task might take 4 minutes; a browser automation might take 15. Temporal gives the Brain durable execution — if a worker crashes mid-tool-call, the task picks up where it left off. From your perspective: requests don’t lose state if a deploy lands during a long run.

Limits per request

Limit	Value
Max message length	50,000 words
Conversation history sent to model	100 messages
Per-message size	50 KB
Tool calls per conversation	200 cumulative
Workspace concurrency	20 requests / 45-minute window

After 200 cumulative tool calls in a single conversation, the Brain blocks further calls and asks you to start fresh. This protects against runaway agent loops.

Brain plans

A brain plan is the AI’s working memory for a multi-step task. It’s the thing you see when the UI says “Researching the company → Pulling LinkedIn → Drafting the email”. Each plan carries:

A goal (the user’s high-level intent)
A list of steps, each with status: pending | running | completed | failed
The tool and model chosen for each step
The result payload as steps finish

Plans live at /api/brain/plans and update live via Supabase Realtime — so any client subscribed sees step state change without polling.

AI Chat

AI Chat is the persistence layer for every conversation with the copilot. A conversation holds:

A title (auto-generated from the first prompt, editable)
An ordered list of messages — user / assistant / tool
Optional attachments (files dropped into the chat)
Optional artifacts (workspace objects pinned for context — see below)
A link to a project for grouping
is_archived to soft-delete

Conversation operations

What	Endpoint
List conversations	`GET /api/ai-chat/conversations`
Search by title or content	`GET /api/ai-chat/conversations/search`
Embed a conversation for retrieval	`POST /api/ai-chat/conversations/embed`
Backfill missing embeddings	`POST /api/ai-chat/conversations/backfill`
Send a new message	`POST /api/ai-chat/messages`

Conversations are embedded into the vector store as they grow so the copilot can recall prior discussions in semantic search.

Attachments

Drop a file into a conversation and the AI reads it as part of its context.

Supported	Used for
Text — txt, md, csv, json, html, xml	Direct context — the file body is appended to the prompt
PDF	Extracted to text + indexed for retrieval
Images — jpeg, png, gif, webp	Vision input on vision-capable models
Code — js, ts, py, java, c, cpp	Sent as code blocks
Office — xlsx, docx	Parsed to structured text

Max 50 MB per attachment. Attachments are scoped to the conversation — they aren’t visible to other conversations or the workspace at large.

Browser Tasks

The AI can drive a real browser for tasks like “go to Stripe, find the failed invoices from last week, screenshot them” or “fill in this form on our partner portal”. Browser tasks run in E2B sandboxes — isolated headless browsers Connie spins up on demand. What you can see while a task runs:

A live-view URL — embeddable iframe that streams the browser as the AI drives it
A progress message that the agent updates as steps complete (“opened Stripe”, “filtered by failed”, “found 3 invoices”)
The final result — usually a structured JSON payload plus screenshots

Task lifecycle: pending → running → completed | failed | cancelled. Tasks have a configurable timeout and are auto-killed if they hang past it.

POST   /api/ai-chat/browser-tasks          # Create
GET    /api/ai-chat/browser-tasks          # List
PATCH  /api/ai-chat/browser-tasks          # Update status / progress
POST   /api/ai-chat/browser-tasks/timeout  # Force timeout on stale tasks

Artifacts

Artifacts are workspace objects you pin to a conversation so the AI has them in context. Today’s artifact types:

Type	What it scopes
`page`	A whole page — the AI can read and edit it
`page_article`	A single article inside a page
`table`	A Flows table — the AI can query and write rows
`workflow`	A workflow definition — the AI can read or modify the graph

Pinning is live — if you rename the underlying object, the artifact label updates in real time. Artifacts give the AI scoped, intentional context instead of forcing it to crawl the whole workspace.

Artifacts are about bringing context in, not about the AI generating outputs to share. The “shareable AI output” pattern is on the roadmap but artifacts today are inbound-only.

AI Cache

The Brain has an automatic FAQ cache for standalone questions that don’t depend on conversation history. A request is cache-eligible if it has:

No artifact mentions
No file attachments
No prior conversation history
No custom AI settings
And the message shape matches FAQ heuristics (length, structure)

When a hit lands, the cached response returns with cacheLatencyMs in the metadata so you can tell. Cache is workspace-scoped — your tone and prior answers don’t bleed into other workspaces. Cache management is mostly automatic but the API exposes manual control for invalidation:

GET    /api/ai-cache       # Search
POST   /api/ai-cache       # Store
DELETE /api/ai-cache       # Invalidate

AI Usage

Token usage is tracked per user and per workspace.

GET /api/ai-usage

Returns daily and monthly token totals plus a percentUsed summary against your workspace budget and resetAt timestamp. Admins can append ?workspace=true to see the whole-workspace total. Usage gates new requests — when the workspace credit budget is depleted, /api/brain/start returns 402 Insufficient Credits until plan-change or the next cycle.

Credit deduction is post-charge: a request that fails after the charge has been applied is not refunded. Be deliberate about expensive tool budgets.

Common workflows

Drop a PDF into a conversation and ask questions about it

Open a fresh AI chat
Drop the PDF — it’s uploaded as an attachment and extracted to text
Ask questions — the Brain pulls relevant chunks from the PDF into every prompt

Pin a page and ask the AI to update it

Pin a workspace page as an artifact in your chat
Say “rewrite the introduction to focus on X”
The Brain edits the page directly and confirms in the chat

Run a browser task from a workflow

Build a workflow with a Browser Task node
Configure the prompt: “log into Stripe, find failed invoices, return as JSON”
The workflow blocks on the task, gets the JSON result, and continues to downstream nodes

API reference

Brain

Send messages, stream responses, cancel and resume.

Plans

Inspect and update agent plans for in-flight requests.

AI Chat

Persistent conversations, messages, and embedding management.

Attachments

File uploads scoped to a conversation.

Browser Tasks

AI-driven browser automation in E2B sandboxes.

Artifacts

Pin pages, tables, and workflows to a conversation.

AI Cache

Manual cache lookup, storage, and invalidation.

Usage

Token consumption per user and workspace.

​What is the Brain?

​How a request flows

​Why Temporal?

​Limits per request

​Brain plans

​AI Chat

​Conversation operations

​Attachments

​Browser Tasks

​Artifacts

​AI Cache

​AI Usage

​Common workflows

​Drop a PDF into a conversation and ask questions about it

​Pin a page and ask the AI to update it

​Run a browser task from a workflow

​API reference

Brain

Plans

AI Chat

Attachments

Browser Tasks

Artifacts

AI Cache

Usage

What is the Brain?

How a request flows

Why Temporal?

Limits per request

Brain plans

AI Chat

Conversation operations

Attachments

Browser Tasks

Artifacts

AI Cache

AI Usage

Common workflows

Drop a PDF into a conversation and ask questions about it

Pin a page and ask the AI to update it

Run a browser task from a workflow

API reference