Nodeself
The behavioral mirror. Not a habit tracker.
What it does
Most habit apps count your streaks. Nexus models why they break. Nexus maps the causal structure of your behavior as a living, interactive graph. Each node - a habit, decision, attitude or state - is connected to others and decays over time when you stop reinforcing it. Silence is data too. Check in through an AI-Powered journal. Nexus analyzes you entires, detects patterns, updates your graph and simulates where you current trajectory leads in 30 or 90 days. No generic advice. No streaks.
Does the same job
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- AFA free minimalist daily habit tracker2024 · rdht.vercel.app · ▲158
Hello. I was looking for a simple and clean habit tracker. I went through a few apps but felt they were missing something. I also had some time on my hands, so decided to make my own and share it in case anyone else likes it. Some of the supported features: Streaks based, track and beat your longest streaks Fully useable offline Freezes (similar to Duolingo's streak freezes) Visual map for tracking consistency Pause the app when you need a break or will be away For anyone curious about the tech stack: - React for frontend - Dexie cloud for storage and syncing - Vercel for hosting Link:…
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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…
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Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
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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
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Dev tools · May 2026 · github.com