Nugget AI

Hey Product Hunt 👋 I'm Brodie — PM by day, builder by night. Nugget is my answer to a problem I've lived with for 6+ years of doing customer discovery: great interviews generate incredible signal, then it dies in transcripts no one reads. Every PM I know has the same broken workflow: run 5 great interviews → take messy notes → forget half of it → write a PRD from gut feeling → pretend it was data-driven. Engineers then ship from your gut, not your customers. Nugget closes that loop: 🎙️ Real-time transcription (or drop in Zoom, support tickets, Slack threads) 🤖 AI extracts "Nuggets" — pain points, feature requests, sentiment 🧩 Cross-interview synthesis surfaces themes ranked by frequency + severity 📄 Auto-generated PRDs with real customer quotes attached 🔌 NEW: MCP server so Claude, ChatGPT, Cursor, and Codex can query your interviews directly The MCP piece is the one I'm most excited about. Your AI agent stops hallucinating users and starts citing real ones. 🎁 Alpha Day offer: 66% off the first year of Pro for anyone who comments here — DM me your handle. Would love honest feedback — especially from PMs and founders doing discovery. What's broken in your workflow that I haven't solved yet?

<p>Interview graveyard vibes here. Notes in Notion, gut in the PRD. If it really pulls themes and spits PRDs with quotes, that's useful. The MCP angle is neat grounding chatgpt on real calls. Keen to try on my next batch. Solo PM here, time savers matter.</p>

<p>Indie iOS founder here, doing a lot of customer discovery ahead of an App Store launch, so the "interviews die in transcripts no one reads" line hits home. The MCP server is the smart unlock; an agent citing real users instead of hallucinating them is the whole game.</p><p>Answering your q: the gap I'd flag is upstream of synthesis: interview <em>quality</em> varies wildly, and a confident-but-shallow interview produces clean-looking Nuggets that are actually just the customer agreeing with my leading questions. Does Nugget do anything to flag low-signal interviews (interviewer talked 70% of the time, all closed questions, sentiment too uniformly positive), or does it treat every transcript as equally trustworthy evidence?</p>

<p>I’ve personally been in situations where we did multiple customer calls, captured tons of feedback, and still ended up writing PRDs mostly from memory because nobody had time to go back through long transcripts. A lot of valuable insights just get lost in docs and scattered notes.</p><p>Really like how Nugget focuses on connecting customer conversations directly to product decisions instead of letting that context disappear. The MCP integration is especially interesting because AI tools become much more useful when they can reference actual user feedback instead of assumptions.</p><p>Congrats on the launch, Brodie!</p>