Sherpa
Intelligent User Onboarding
What it does
Loom killed meetings. Sherpa killed emails. By the time you finish building a product tour, a new release makes it irrelevant. Sherpa keeps your product and your customers up to date in minutes. Record a product walkthrough as though you're recording a Loom, and Sherpa does the rest. Now, users can ask in-app, "How do I create a new customer record?" and Sherpa dynamically generates a guided overlay, showing them exactly where to click, from wherever they started.
Does the same job
all alternatives →- MUMost users won't report bugs unless you make it stupidly easy2025 · ▲335
Most feedback tools are built like people actually want to report bugs. They don’t. Unless you make it dead-simple, or better yet - a little fun. After shipping a few SaaS products, I noticed a pattern: Bugs? Yes. Bug reports? No. Not because users didn’t care but because reporting bugs is usually a terrible experience. Most tools want users to: * Fill out a long form * Enter their email * Describe a bug they barely understand * Maybe sign in or create an account * Then maybe submit it Let’s be real: no one’s doing that. Especially not someone just trying to use your product. So I built…
Quickhunt: Customer Feedback ManagementSep 2025 · ▲59AI-Powered Feedback, Roadmap & Changelog, All in One
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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, 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