Framer 3.0
Product HuntFramer gives you an AI design agent and a freeform canvas for turning ideas into polished, interactive sites. Start with a prompt and the agent can create pages, layouts, copy, visuals, interactions, components, responsive breakpoints, and code directly in your project. Everything stays editable, so you can keep prompting or refine the work yourself. Framer also includes CMS, collaboration, analytics, SEO, performance tools, and hosting to help you publish and improve your work.
Share cardActual performance
898upvotes
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Made the leaderboard
Traction signals
Makers1
Screenshots2
Launch Intel predictions
Analyze your own launch →Product HuntOn track for Day 1 leaderboard · Strong signals: agent, visual, code · Missing: mac, agents, macos88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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