Do GitHub stars tell me whether a framework is right for my team?
No. The star count measures interest, not fit. What matters is where run state persists, what starts a run, where secrets live, and who reviews a change before it reaches production.
A framework's GitHub repository holds the library and its documentation. The runtime, the review step, and the company memory a team depends on usually live outside it. This guide shows what to check before you commit. Kortix is the open-source AI Operating System that runs and governs the agents.
Rival details come from each project's own repository, checked October 2026.
| Criteria | Open source | What lives in the repo | What you still run yourself | Where company memory and secrets live | How changes are reviewed | How it reaches production | Whether the operator is part of the product |
|---|---|---|---|---|---|---|---|
| Kortix | Yes. Read it, fork it, audit it. | Agents, skills, memory, connectors, and triggers as files, with kortix.yaml. | Self-host is free; otherwise Kortix Cloud runs the sessions. | Memory is files in the repo; secrets are encrypted per project. | Work reaches main through a change request a person reviews. | A person merges the change request; the platform carries the runtime. | Yes. The sessions, the review, and the audit are the product. |
| LangGraph | Yes | The library and its docs; you write the graph. | The application, its model calls, and its deployment. | In your checkpointer and store; you manage the keys. | Interrupts you place; otherwise you build the review. | You deploy the graph to your own infrastructure. | No. It is a library; the operator is your code. |
| CrewAI | Yes | The Python framework and its docs; you write the crews. | The Python app, its environment, and its deployment. | In CrewAI's memory store and your environment variables. | A human review step you add to a task. | You ship the Python app to your own infrastructure. | No. The control plane is a separate commercial suite. |
| AutoGen | Yes | The Python framework and its docs; you build the app. | The application, its runtime, and its deployment. | In saved state and your environment variables. | Agents act autonomously or work alongside people. | You ship the Python app to your own infrastructure. | No. It is a framework you operate yourself. |
| OpenHands | Yes | The Agent Canvas front end and its local-stack orchestration. | The host and the agent backends you run. | In the state directory you mount and your own keys. | You review the conversations and the changes yourself. | You run the control center and its agent backends. | Yes. Agent Canvas is a self-hosted control center. |
# yaml-language-server: $schema=https://kortix.com/schema/kortix.v2.schema.jsonkortix_version: 2default_agent: kortixagents: kortix: file: agents/kortix.md connectors: all secrets: all skills: all kortix_permissions: allOne file declares the agents, what each may reach, and the triggers, connectors, and secret names of the project.
Read the repository as a statement of scope: what the maintainers intend to own and what they leave to you. Seven things are worth checking before you commit.
Each answer tells you who owns the runtime after the first demo.
A framework repository holds the code that defines agents: prompts, tools, and control flow. It does not hold the machine a run works on, the branch it commits to, the review gate, or the audit trail, unless the project documents them. Those parts belong to the application your team operates, and the framework or platform page sets out the split.
Kortix is the open-source AI Operating System that takes the other side of it. Agents, skills, and company memory are files in one git repo you own, each session runs on its own cloud computer, and work reaches main through a change request a person reviews.
You do not have to discard the library. Keep the prompts and the tool definitions you already wrote, and move where they run. Describe each agent as a file, declare the connectors and secret names it needs in kortix.yaml, and let a session start it on demand or from a trigger. The how to build an AI agent guide walks the first agent from an empty directory to a change request.
No. The star count measures interest, not fit. What matters is where run state persists, what starts a run, where secrets live, and who reviews a change before it reaches production.
The README's first paragraph, because a good one states what the project owns and what it leaves to you. Then the state and persistence docs, because they decide who runs and remembers the work.
Yes. Keep a framework where it lives inside your own application, and let Kortix run the agents whose work the company has to own, review, and audit. The two sit at different layers, so they do not compete for the same job.
Only when its scope does not depend on new work. AutoGen's own README says it is in maintenance mode and points new projects at Microsoft Agent Framework, so read the successor before you commit.
One repo for the agents, the skills, the memory, and the connectors.