Discovery takes a Goal, Initiative, customer signal, or product hunch and turns it into Brief-level context. You can test the hunch in code, ideate in Figma, whiteboard with your team, or pull the AI into Hamster Chat. Whatever the surface, Discovery ends with an aligned Brief that can cross into Delivery.
This is where the 70% becomes possible to push toward 99%. The AI can draft something plausible from a prompt, but Discovery gives it the user need, constraints, evidence, and acceptance criteria that make the last 30% specific to your team.
Hamster Chat is a persistent canvas where you talk to the AI assistant and your team at the same time, with the Context Graph doing the lookup behind every reply.
Describe a hunch — "We're hearing first-time buyers drop off at the checkout step. What do we know about that?" — and Hamster pulls in the relevant Blueprint, recent Linear tickets, customer-call mentions, prior Briefs, and whatever else is connected, then replies with structured thinking. You ask follow-ups, push back, request a deeper pass, and pull in a teammate. The thread is the workspace; the AI is grounded in your team's real systems, not generic.
Hamster Chat is not only a wrapper around an LLM. It is where ambiguity gets sharpened against everything your team has accumulated, in one room, with the AI as a participant. When the picture is clear, you ask Hamster to turn the conversation into a Brief, and the first draft already references what Hamster Chat surfaced.
Research Agents are a deeper, structured Discovery pass for when a quick Hamster Chat thread isn't enough. You hand off a question — "Map our last six churn-cohort customer interviews against the activation funnel" — and the Research Agent does the legwork across the Context Graph and any external sources you allow.
Use Research Agents when you're scoping an Initiative, validating an assumption, or trying to understand a customer signal across the data your team has already accumulated. The output lands as a structured document you can attach to a Brief, so the work the Research Agent did stays connected to the work that ships.
A Brief starts as a hunch in Discovery and stays here while it's being refined. Scope clarifies, the Blueprint comes along as context, alignment votes get collected. The same artefact later crosses into Delivery, which is why every shipped PR can trace back to the conversation that started it.
Refinement is the rest of Discovery once a draft exists: sharpening scope, clarifying acceptance, gathering input from anyone who needs to weigh in. The AI assistant pushes back when scope is vague; you attach Figma frames, customer recordings, related Briefs, and the AI uses them as it tightens the draft. If refining the Brief surfaces something the Blueprint missed, the Blueprint update is proposed automatically — Knowledge stays current as Discovery happens.
When the Brief is good enough that humans and the AI both know what's being shipped, alignment votes go in, a Plan generates, and the Brief crosses into Delivery.
Discovery ends when the Brief is good enough that humans and AI both know what's being shipped. The team votes the Brief ready, a Plan generates, and the work crosses into Delivery.