Agents with careers.
Every agent framework treats an agent as a static config — same capabilities on day 1 and day 1,000. Mentat gives agents careers: they earn trust, get promoted, and spawn and mentor juniors — all on a graph that stores the system's intelligence instead of bolting memory on afterward. It's the framework behind Ziggy.
The problem
Every agentic framework solves the same starter problem — get an LLM to use tools and follow instructions — and they all work, for simple agents. But the moment you want agents that improve over time, grow into new responsibilities, and teach each other, they hit the same wall: the data model was never built for it, and bolting it on creates the kind of architectural debt that makes senior engineers quit.
The solution
Mentat makes the graph the operating system. Agent profiles, conversations, tools, feedback, and every routing decision live as nodes and edges — so “which agent is best for this task?” is one scored query, not infrastructure you maintain. On that foundation, agents have careers, the system generates its own training data, and guardrails work at both the prompt and runtime level.
How it works
What it does differently.
Agents, conversations, tools, and feedback all live in one graph. Picking the right agent is a single scored query — not infrastructure you build and babysit.
Junior to Principal. Agents earn trust from real outcomes, get promoted automatically, and spawn juniors that inherit their specialization and hard-won lessons.
Every message emits training data as a side effect — prompt snapshots, context versions, routing decisions — exportable to fine-tune the system on its own history.
The build story
"Every framework hits the same wall — agents that can't grow. We built Mentat because we hit it ourselves."
Mentat was extracted from Ziggy — a production system handling real agent orchestration, not a weekend hackathon. It's the long bet under the rest of Labs: Gristle proved graph-first structure holds up, Ziggy put it into production coordinating agents, and Mentat generalizes it into a framework where the architecture, not the operator, decides how the system grows. TypeScript-first, graph all the way down.