contxt.to
Share context with your team and their AI - in one link.
What it does
You spent an hour explaining your project to ChatGPT. Now your teammate needs the same context in Claude. Your client wants their AI briefed too. So everyone starts over from scratch. contxt.to fixes that. Paste your notes, briefs, or AI chat summaries, and get one clean link carrying the full context. Share it in Slack, email, or any AI tool. Humans and models get the same structured understanding instantly - no forwarded exports, no “let me summarize first,” no repeated onboarding.
Does the same job
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- DEDump – easily share context with AIMar 2026 · dump.page · ▲7
I wanted a very simple way to dump prompts, links, and todo lists into my claude code and codex agents. And to work outside of the context window. This works particularly well for sharing "Projects" between Claude/ChatGPT etc. It's open source here; https://github.com/Vochsel/dump.page Anything you dump on the board becomes an llms.txt - spatially sorted implicitly and explicity sorted via connection edges. Would love HN's thoughts!
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.
AI · 17d ago · simedw.com
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AI · 19d ago · company-app.joinastute.com
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, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com