Problem Miner.
Find real problems people complain about before you build
What it does
Problem Miner helps founders stop guessing what to build. It scans real online conversations where people complain or get stuck and turns that raw frustration into clean, builder-ready problem briefs. Instead of one-off ideas, you see repeatable pain patterns with context, severity, and willingness-to-pay signals. Pro users can run the pipeline on specific subreddits using Listening Channels. Built for indie hackers and product builders who want evidence before shipping.
Does the same job
all alternatives →
- BABacklog – a public repository of real work problemsDec 2025 · worldsbacklog.com · ▲112
AI has made building fast and cheap, but finding the right problems still feels hard. I built World’s Backlog (https://worldsbacklog.com ) to collect real problems directly from people working inside different industries. Contributors post workflow pain, others validate it, and builders can study severity, frequency, and willingness to pay before building anything. Would love feedback from builders and people who feel real pain at work.
- PAProblemHunt – A place to collect real problems before building startupsJan 2026 · problemhunt.pro · ▲5
Hi HN, I’m a solo founder. I built ProblemHunt after noticing a common pattern: many founders start with ideas and solutions, but don’t spend enough time understanding real problems. ProblemHunt is a simple place where people share problems they actually face in work or life. Developers and founders can browse these problems and use them as a starting point for building products. So far: – ~5,000 users – 150+ real problems submitted – 100% organic growth This is still early, and I’m trying to understand if this is genuinely useful. I’d really appreciate feedback: – Would you use something…
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
