Orqen
Optimize, route, and safeguard your LLM agent context.
What it does
Stop paying the "input token tax." Orqen is a native AI proxy that sits between your app and LLM providers. It dynamically compresses chat histories, filters tool schemas, trims large tool outputs, and acts as a circuit breaker for agent loops.
Does the same job
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- IBI built an open-source AI data layer that connects any LLM to any dataOct 2025 · github.com · ▲18
Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
- MAMirror AI – LLM agent that takes action, not just chat2025 · themirrorai.com · ▲5
Hi HN, TL;DR Mirror AI is a cross-platform desktop action oriented LLM. Instead of just replying with text, it can run terminal commands, move files, hit APIs, send email/messages, schedule calendar events, query databases etc. - and chain those steps in one request. Why I built it Chatbots are great for answers but stop at the “OK, now go do it” moment. I was copy-pasting between ChatGPT and my shell/IDE/Gmail far too often, so on red-eye flights I hacked a bridge that lets an LLM execute tasks under a permission layer. Friends asked for it, feature-creep happened, and here…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, June 2026
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Today, I’m proud to announce Homebrew 6.0.0. The most significant changes since 5.1.0 are a new tap trust security mechanism, the new faster, smaller, default internal Homebrew JSON API, sandboxing on Linux, better defaults informed by our user survey, many brew bundle improvements, improved performance and initial support for macOS 27 (Golden Gate). Happy to discuss any questions here!
Dev tools · Jun 2026 · brew.sh
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Life & fun · Jun 2026 · vorpus.github.io
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