DeepSeek Harness Opens the Agent Framework It Used to Benchmark Its Own Models
DeepSeek open-sources its agent harness framework under MIT, where every component from models to UI is a hot-swappable plugin
- DeepSeek Harness v0.1 is now in public developer preview, fully open-source under the MIT license: github.com/deepseek-ai/deepseek-harness
- Built on the Cordis meta-framework: every agent component (models, tools, loops, sandboxes, UI) is a hot-swappable plugin requiring no source changes.
- Ships with four runtime modes: Standard (full agent), Code (TypeScript tool orchestration), Minimal (benchmarking), and Creator (custom preset authoring).
- Model-agnostic: supports DeepSeek, Anthropic, OpenAI, Bedrock, Vertex, Azure, and any OpenAI-compatible endpoint out of the box.
- Every run is fully traceable via an append-only session log; sessions can be resumed, forked, and replayed.
- Still in developer preview with breaking changes expected; a community plugin ecosystem is already forming on GitHub.
DeepSeek Harness (dsh) just dropped into public developer preview, and it's fully open-source under the MIT license. This is the same framework DeepSeek used internally to run its own coding-agent benchmarks for DeepSeek-V4-Flash, and now anyone can build on top of it. The core philosophy is simple but radical: everything is a plugin.
What problem does this solve?
Building a production-ready AI agent today means stitching together a model, a tool-calling loop, memory, sandboxes, file systems, and a UI, and then hardcoding the seams between them. Swap your model provider, and you're rewriting glue code. Add a new tool, and you're patching the orchestration layer. DeepSeek Harness is designed to eliminate that problem entirely by treating every one of those components as an interchangeable plugin.
A harness lets an agent understand its environment, use tools, and keep working in real-world settings. The framing here is deliberate: the team's mission is explicit: Model + Harness = Agent. Everything except the model itself, including tooling, memory, agent loop, desktop integration, and feedback systems, belongs to the Harness.
The Cordis kernel: the engine underneath
DeepSeek Harness is an open-source agent harness developed by DeepSeek AI. It uses an architecture where everything is a plugin, and is powered by Cordis, whose design is described in A Programming Paradigm for Spatiotemporal Composability.
Cordis is a TypeScript meta-framework built around the idea that software components should be composable both in space (which plugins are active) and in time (when they are mounted or unmounted). Think of it like a dependency-injection container, but one where plugins can be hot-swapped at runtime without restarting the process. The Cordis kernel manages plugin mounting, unmounting, and dependencies. Agent capabilities live in the plugins.