
Noeth
The coding interview AI that lets you bring your own API key
What it does
Tired of $100–300/month coding interview AI subscriptions? Noeth is an invisible desktop overlay that gives you real-time help during technical interviews, LeetCode solutions, code review, voice Q&A, live transcription, flowcharts and much more. Bring your own Anthropic, Gemini, OpenAI, or Ollama key and pay at cost. No subscription ever. $12.90 one-time lifetime license for 3 devices. Works on Windows, macOS, and Linux. The alternative to Interview Coder, Cluely, Parakeet AI, and LockedIn AI.
Does the same job
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Hi HN, I built OpenHarness , an open-source terminal coding agent that works with any LLM: Ollama (free, local), OpenAI, Anthropic, Deepseek, Qwen or any OpenAI-compatible API. Install and run: npm install -g @zhijiewang/openharness oh # auto-detect local model oh --model ollama/qwen2.5:7b # specific model What it does: - 17 tools (file read/edit/write, bash, grep, glob, web search, task management, notebooks) - 16 slash commands (/diff, /undo, /commit, /cost, /compact, /plan, /review...) - Git integration: every AI edit auto-committed,…
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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, 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
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Dev tools · May 2026 · github.com