Harnesses, context, tools, and the systems that help agents work well.
5 articles
How we built a company-wide cloud Agents API: the agent loop runs in the cloud on DeepSeek Harness, its state is durably persisted, and tools run through an executor built on Codex exec-server.
A performance-optimization case study showing how prompt contracts, multi-agent research, trace tooling, experimental memory, and validation turn an agent harness into a working environment for capable models.
Token management in AI agents is not a single compression trick. It is a system design problem around admission control, compression, retrieval, cache protection, output shaping, and overflow recovery.
A comparative analysis of seven AI Agent projects, examining the Harness design space across loops, tools, sub-agents, context management, permissions, and enterprise adoption.
A deep dive into Claude Code's Tool Search mechanism — how it manages tool discovery and loading through a two-layer catalog-execution architecture.