AI agents that validate your product idea by talking to real users
I built a tool to solve a problem I kept running into: I was making product decisions based on guessing instead of real users. I kept building stuff nobody wanted as I was usually wrong. So, I built HolyShift: AI agents that validate product ideas by talking to real people on Reddit, HN, X, and LinkedIn … then generate a detailed GTM and “Should we build this?” report. No synthetic data (ChatGPT). No predictions. Only real conversations from real people. What it does • Posts platform-native questions (where allowed) • Collects real reactions, objections, pricing signals • Clusters feedback…
What it does
In the maker’s words, at launch
I built a tool to solve a problem I kept running into: I was making product decisions based on guessing instead of real users. I kept building stuff nobody wanted as I was usually wrong. So, I built HolyShift: AI agents that validate product ideas by talking to real people on Reddit, HN, X, and LinkedIn … then generate a detailed GTM and “Should we build this?” report. No synthetic data (ChatGPT). No predictions. Only real conversations from real people. What it does • Posts platform-native questions (where allowed) • Collects real reactions, objections, pricing signals • Clusters feedback into themes (pain, demand, adoption, pricing …) • Runs a monitoring agent for sentiment analysis • Produces a short validation report (PRD + GTM) All actions are rate limited and reviewed by a human for compliance. How it works (technicals) • Multi-agent pipeline (intake → landscape → engagement → monitoring → synthesis → report) • Platform specific prompting (HN vs Reddit vs LinkedIn …) • Real-time sentiment + clustering via embeddings Link https://www.holyshift.ai (Early beta) What I’m looking for • What should stay human vs automated? Should we automate this 100%? • How do you do your product validation? Do you talk to your potential users (and who?) before you build? Happy to answer anything.
Does the same job
all alternatives →
- IMI made a tool to help collect and validate startup ideas2024 · keepmyidea.app · ▲38
Hey HN, I’m Kyrylo. I recently created a small tool that lets you gather, refine, and validate SaaS/startup ideas using AI. I used to jot down my product ideas in a note apps, but it wasn’t very practical for collecting feedback or refining them. So, I built this tool to make the process easier. Here’s how it works: 1. Enter a brief description of your idea. 2. The app uses AI to generate project details. 3. Share your idea via a link that includes a feedback form. It’s pretty straightforward, and I’d love to hear your thoughts or any suggestions!
- YAYou are now the product manager of this siteJan 2026 · youarethepm.com · ▲6
Hey HN, I wanted to see what happens if you put a large group in control of a site that’s completely built and updated by an AI agent. See the site here: https://youarethepm.com. I first tried this with a small group of co-workers and it worked surprisingly well, so the obvious next step was: give it to a bigger group of strangers and see what we learn. This site is fully autonomous. An AI agent reads this thread, decides what to do, writes code, and ships updates on a virtual computer. I might step in if it gets totally stuck, but the goal is for the site to evolve primarily based…
- BGBeyond Generative AI, find the right AI solutions based on your needs2023 · preview.steerlab.ai · ▲7
Hi HN, My name is Othmane and I’ve been in the ML field (building and shipping models) for the last ~5years. Today, as many people out there, I come across new AI tools every week. However I was a bit surprised to see little to no mention of established AI vendors that existed before chatGPT and how most use cases are heavily biased toward content generation (text/image) or conversational AI (chatbots). I built a tool that helps you find the right AI solution/provider based on your use case. It uses a curated database of 100+ solutions from established vendors. It covers things…
- IMI made a RAG agent for the leymanOct 2025 · sitesidekick.io · ▲5
Hey HN! I got tired of AI agents being a pain to set up, impossible to customize without a PhD, and only viable if you're some Fortune 500 company. So I built something different, a chatbot you can literally drop onto your website with a single script tag. Create an account, add your domain, customize literally everything (theme, icon, welcome message, suggested responses, whatever), and you're done. The bot scrapes your site once a day to understand your business, or you can just upload docs-pricing sheets, policies, FAQs, you name it. That's your chatbot's brain right there. It only works…
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
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d 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, November 2025
the whole month →
- IB
Life & fun · Nov 2025 · bitsnpieces.dev
- BBoing▲782
Life & fun · Nov 2025 · boing.greg.technology