This article dissects DeepSeek Harness, an MIT-licensed agent framework where everything is a plugin, explaining its Cordis-based spatiotemporal composability, internal execution loop, and trade-offs against Claude Code's integrated approach.
DeepSeek Harness (DSH) introduces a plugin‑centric AI Agent architecture that treats the Agent as the emergent result of configurable plugins, leverages the Cordis spatiotemporal composability framework, offers four distinct runtime modes, and is compared against Claude Code, Codex, LangGraph and AutoGen, highlighting its strengths, practical usage, and current limitations.
DeepSeek Harness has been open‑sourced together with a newly released Cordis paper that lifts the effect‑coeffect concepts to runtime, defines spatiotemporal composability, details a TypeScript implementation, and validates the approach with the Koishi chatbot framework.
The DeepSeek Harness SDK, now open‑source, offers a completely pluggable architecture for building AI agents, provides four preset modes, multiple entry points, a fail‑closed security model, and is underpinned by a rigorous academic paper on spatiotemporal composability that formalizes reversible effects and reactive coeffects.
