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Streaming AI powered prompt/image to process
Hacker NewsStreaming AI powered prompt/image to process
We just released AI backed text to process and image to process. Training ChatGPT to understand our process notation and structured format was the easy part of this. Isolating our editor and make it work with streaming was what took time. Let us know what you think! We belive it will be a great way to quickly test our product and to import processes made in other tools or drawn on the whiteboard.
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3points
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt · Missing: mac, agents, macos66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: just released, io · Missing: https docs, excited, exist48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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