CookWing, an AI chef that doesn't hallucinate quantities

Hacker News

Hey HN! I just released Cookwing. This is an AI app that solves the biggest problem I had when I was cooking with ChatGPT : The quantities are often hallucinated. I was curious, so I even built my own cooking quantity benchmark while development, and here are the results. We're using my system, which is anchoring tables that are searched in the original country of the recipe. For example, when cooking carbonara, it's going to check for the Italian web for the anchoring table, not the English web. Benchmark results : https://cook.redwi.ng/static/blog/cookbench-v1-cooking-quant... The results were quite stunning, We reached 90% correct runs in average with correct quantities, and I'm saying that because I actually cooked myself these and I know the exact quantities Required for these recipes. Feel free to try it and give me your thoughts!

Visit product View on Hacker NewsAug 25, 2026

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, using · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, 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, exist

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% 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, cryptocurrency

1%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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