@rohanpaul_ai: DeepSeek Harness reached 122K+ GitHub stars in 3 days, one of the fastest to rise in GitHub's history. It makes models,…

DeepSeek Harness reached 122K+ GitHub stars in 3 days, one of the fastest to rise in GitHub's history. It makes models, tools, loops, storage, scheduling and even the UI swappable plugins. its an orchestration layer for coding agent, runs as a local web app on a configurable port, and exposes every component as a swappable plug-in: shell access, file editing, web search, skills, sessions, model choice, reasoning effort, and permission scope, all editable in a YAML config. sub-agent support is the really special part. You can wire Claude Code or Codex in as plug-ins and let Harness route subtasks to whichever agent suits each step. It's MIT licensed, so you can add other providers or point it at a self-hosted model and never touch DeepSeek's API. However, their release timing for this is strange. They raised the price of cache-hit input by 6-fold to 12-fold in the same week it shipped an agent framework, and cached input is exactly what agent loops consume, since every step replays the same system prompt and accumulated history. Whoever set the API pricing either didn't coordinate with the harness group or deliberately priced the new workload higher. My read is the 2nd, because caching subsidies made sense when agents were rare and become the largest unpriced cost once a framework makes them routine.