Open-source Go runtime for AI agents
- One runtime. Any LLM. Any language. Any deployment.
+ Built for the age of agent teams, not just single agents.
+
+ π¬ Discussions Β· + π Issues Β· + π₯οΈ seshat-ai
@@ -19,6 +25,60 @@ --- +## π€ Why Seshat + +The agentic AI space is moving fast. Dozens of frameworks have emerged β LangChain, LangGraph, CrewAI, AutoGen, and many others. Almost all of them are Python-first. That works fine for experimentation, but it creates real friction the moment you want to ship something: dependency hell, slow startup, heavy containers, difficult embedding in existing services. + +**β‘ Go changes the equation.** A single statically linked binary. No runtime, no venv, no dependency manager. Low latency, predictable memory, easy deployment anywhere β from a Raspberry Pi to a Kubernetes cluster. Seshat brings that to agentic AI. + +But the choice of language is the smaller part of the story. + +--- + +### π§ The real gap: agents don't know how to work together + +Individual agents have become impressive. They can reason for hours, use tools, write code, search the web, produce deliverables. The frontier has moved. The hard unsolved problem is no longer *what a single agent can do* β it is **how multiple agents can work together in a coherent, observable, and economically useful way**. + +Most current systems handle this with pipelines, handoffs, or orchestration graphs. These are useful, but they remain technical constructs. They don't model *work* the way humans actually do it. + +--- + +### π§ The thesis behind this project + +We believe the right model for agent collaboration is not the workflow graph β it is the **human organization**. + +Real teams don't communicate through function calls. They have roles, responsibilities, inboxes, meetings, status reports, shared decisions, and a working memory of the mission. A project lead delegates tasks. A specialist delivers a report. A reviewer pushes back. A coordinator synthesizes. Information flows explicitly. Decisions are recorded. Nothing is lost in a black-box state machine. + +Seshat is being built around this idea: **study how humans work in teams β in companies, research groups, or any collaborative setting β and reproduce those coordination patterns with autonomous agents.** + +This means agents that: +- π¬ communicate through structured messages, not just function calls +- π can send a report, schedule a review, claim a task, or escalate a blocker +- 𧩠have an identity, a role, and a history β not just a prompt and a response +- ποΈ share a mission memory that keeps decisions, constraints, and objectives alive across the team + +--- + +### πΊοΈ Where we are and where we're going + +We are building the foundation. Seshat today is a solid, production-grade runtime: persistent sessions, 60+ tools, 15 LLM providers, MCP client, RAG, skills, gRPC API, sandboxed execution. It is already useful as a standalone CLI, an embeddable Go SDK, or the engine behind [seshat-ai](https://github.com/EngineerProjects/seshat-ai). + +The team primitives β mailboxes, roles, missions, structured inter-agent communication β are the next major layer. We are designing them now, informed by how real organizations function. + +--- + +### π€ An open project β all ideas welcome + +**This is an open research and engineering project as much as a software one.** The ecosystem we want to build is ambitious, and no single perspective has all the answers. + +If you have ideas about how agents should collaborate, how human team structures map to agentic systems, what organizational patterns are worth modeling, or what the ecosystem is still missing β your input is genuinely valuable. + +π Open a [Discussion](https://github.com/EngineerProjects/seshat/discussions), an issue, or a PR. Every suggestion is read. + +We are building this together. π + +--- + ## π₯οΈ Terminal UI `seshat chat` drops you into a full-featured terminal interface built for long-running agent sessions.