Getting Back to Basics by Abusing AI
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Many projects and addons exists to reduce the verbosity on standard bash / git /npm etc. Commands that agents pass regularly as tools to LLMs. (eg. rtk, headroom, lean-ctx). Tool output compression does yield good token savings. Though it can lead to increased turns - effectively nullifying the per turn token savings. This is the current topology. Are we going to see a class of products and libraries that structure o/p to what models want to see? Comments URL: https://news.ycombinator.com/item?i
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<blockquote cite="https://news.ycombinator.com/item?id=48592163#48593190"><p>The real valuable capability MCP offers over skills/CLI is isolating the auth flow outside of the agent’s context window, and potentially out of the harness completely. [...]</p> <p>Maybe the idealized form of MCP is just an auth gateway for the API and nothing else. That’d still be a win.</p></blockquote> <p class="cite">— <a href="https://news.ycombinator.com/item?id=48592163#48593190">Sean Lynch</a>, comment on Hacke
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Hey All, I built Konxios (spelled as Conscious) because I had a problem, AI tools were multiplying, but my workflow was getting more fragmented with no privacy first solution. One tool for chat. Another for coding. Another for automation. Another for creating UGC videos. Another for agents. And almost all of them required sending my data somewhere else. Konxios is my attempt at an AI operating system: Local-first AI with Ollama / LM Studio, Optionally connect cloud models if you prefer BYOK mode
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