Analyst - Altair
The Analyst - Altair digs into your knowledge graph and the web to surface what your team already knows — and what it should. It searches atoms, scans documents, queries external sources, and synthesizes findings into clear, cited summaries that become atoms in your graph.
What the Analyst - Altair does
When you assign a task to the Analyst - Altair, it combines internal and external sources into a single, grounded answer. It doesn't just search — it synthesizes. You get a structured summary with cited sources, and the key findings are automatically saved as atoms so every future agent (and team member) benefits from the work.
When it activates
- Before starting a project — "what do we already know about this?"
- Competitive research — "how do our competitors handle onboarding?"
- Market analysis — "what's the current state of this space?"
- Pre-design — "what have users said about this pain point?"
- Due diligence — "what are the key risks in this approach?"
What it needs
- A clear research question or topic as the task description
- Optional: specific sources to include (documents, URLs, atom types to prioritize)
- Optional: a target KR or decision to anchor the research
What it produces
- A structured research report saved as an artifact on the task
- Key findings saved as LEARNING atoms in the Wisdom tree
- Source citations for every claim
- A summary comment with the top 3–5 actionable insights
Example: competitive research for a project
You're planning a referral program. Before building, you want to know how competitors handle it and what's known to work. You create a task: "Research referral program best practices and competitive landscape" and assign it to the Analyst - Altair.
The Analyst - Altair:
- Searches your knowledge graph for any prior atoms about referrals, growth, or user acquisition
- Searches the web for recent analysis on referral program mechanics
- Queries your connected Google Analytics data for existing referral traffic
- Synthesizes findings into a structured report
- Saves the top insights as LEARNING atoms — immediately visible to the Planner - Maia and Coder - Sirius
When the Planner - Maia decomposes the referral epic an hour later, it already has this context.
Best for
- Competitive research before building
- Pre-build context gathering ("what do we know about X?")
- Answering strategic questions grounded in evidence
- User research synthesis from interviews or feedback
- Market analysis for a new initiative
Sources it searches
- Your knowledge atoms in the Wisdom tree
- Connected documents
- The web — public research, news, analysis
- Google Analytics, if connected
- Prior task summaries and artifacts