Promptlyzer
The fastest way to test, version, and deploy your prompts.
What it does
A simple DevOps-inspired tool to test, version, and manage prompts for AI teams. Build better prompts faster.
Does a similar job
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- PPPromptly – Prompt Management Platform for LLM Apps2023 · trypromptly.com · ▲15
We are excited to show Promptly (https://trypromptly.com), a prompt management platform for LLM apps that makes it easy to experiment, share and manage prompts in production. With Promptly, users can: - Try out different prompts and model parameters for various providers - Quickly share prompt snippets together with parameters and generated output. Think of it as CodePen or JSFiddle for prompts - Create high level endpoints on top of provider APIs (Open AI, DreamStudio etc) with templated and versioned prompts - Use built-in caching for endpoints that will help save on Open AI…
- IMI made a tool that helps you find and create better AI prompts faster2025 · searchpromptly.com · ▲15
Hi Everyone!! Our team is made up of passionate AI enthusiasts with backgrounds in marketing, and engineering. We’re united by a shared belief that the future of AI should be collaborative, accessible, and community-driven. With experience building consumer products and scaling platforms, we’re focused on creating a space where anyone from hobbyists to professionals can discover, organize, and share the best AI prompts and workflows. Promptly is built with a community-first mindset, where user contributions, creativity, and learning are at the heart of the experience.
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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…
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