Inside DeepSeek Harness and Its Plugin-Based Agent Runtime
DeepSeek Harness separates models, tools, sessions, permissions, and interfaces into plugins that builders can replace and combine.
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面向使用 Codex、Claude Code、Cursor 和各类 Agent 的开发者,分享实测过的 AI 编程工作流、编程 Agent 现场笔记和真实的大模型评测。
DeepSeek Harness separates models, tools, sessions, permissions, and interfaces into plugins that builders can replace and combine.
阅读文章A hands-on look at DeepSeek V4 Flash 0731, its vendor-reported agent benchmarks, and the coding tasks where I would use it.
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阅读文章LoopX keeps goals, evidence, ownership, quotas, and handoffs stable across long-running agent sessions without replacing the agent runtime.
阅读文章Practical Claude Code habits that reduce context noise, protect prompt cache reuse, and keep recurring work in smaller sessions.
阅读文章Use ModLens to route screenshots and image files through a configured vision engine, then return structured evidence to a text-only coding agent.
阅读文章Install an Unsloth GGUF build of Qwen3.8-27B with Ollama or llama.cpp, then choose a quant that leaves enough unified memory for the runtime.
阅读文章Same model, different inference stack, wildly different latency and cost. Modular's handbook covers VRAM math, KV cache, batching, and serving.
阅读文章A practical look at ChatGPT Voice and multi-folder projects in Codex, including their workflow benefits, limits, and setup details.
阅读文章A hands-on Kimi K3 backend audit across 68K lines of FastAPI code, including query fixes, measured results, and the full task cost.
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