How Hyperagent fits together
Agents carry a job into threads; skills, memories, invocations, teams, and the Library make that work reusable.
Hyperagent is where you staff AI teammates for ongoing work. An agent carries a defined job, tools, context, and controls. Every time that agent works, it does so in a thread. The other parts of the product help the role start, remember, improve, share, and keep its output.
The pieces
Agent
The configured teammate. It owns the role, model, tools, knowledge access, controls, and invocations. Agents
Thread
Where one run happens. It holds messages, tool calls, files, decisions, and the output from that conversation. Threads
Skill
A reusable method. It teaches an agent how to perform a specific kind of work. Skills
Memory
Saved context. It carries facts and preferences forward without turning the whole chat history into the brief. Memories
Project
A home for related goals, threads, files, and working documents.
Team
The sharing and governance surface for agents, skills, memories, and other work people should access together. Teams
Library
The gallery of outputs produced across threads, ready to find, reuse, publish, or share. Library
Agent is who shows up. Thread is where a run happens. Skill is the method. Memory is saved context.
Why the parts matter together
Each part removes a different kind of repeated setup:
- Improve a skill once, and every linked agent uses the better method
- Save the right memories, and you stop re-briefing standing facts
- Add an invocation, and the job starts from Slack or a schedule without rebuilding the agent
- Share a stable agent with a team, and other people run the same role and controls
- Keep outputs in the Library, and work from older threads stays findable
The model can change while the role stays intact. That is the point of separating the agent's job and context from the reasoning model that runs it.
One Monday pipeline brief
Imagine a pipeline update that should arrive every Monday without someone restaffing the work.
Staff the role
Create a RevOps agent with CRM access, a clear job description, and the model the judgment deserves.
Teach the method
Attach a Weekly Pipeline Summary skill so the checklist and output format stay consistent.
Keep the facts
Link memories for risk thresholds, reporting preferences, and the delivery audience. Set the knowledge boundary before the agent is shared.
Start each run
Add a Monday schedule. The schedule starts the work, but the run still happens in a thread.
Keep and share the result
The brief appears in the thread and its reusable output lands in the Library. Share the agent with the sales team when they should run the same role themselves.
Start with Agents when you are staffing a recurring role. Start with Skills when you already have a method worth teaching once.