I made an app so I'll never worry about prompting again

Hacker News

prompting chatGPT sometimes feels like I'm begging for handouts. - I assign it a role like "You're a programmer with 10 years of experience" or "You're a creative writer specializing in science fiction" - I give it the context - I ask it if it has any questions and try to answer them But it still gives me rubbish code or answers. The only times, I've gotten real gold are when I spend hours perfecting the prompt. I try and think through every scenario. I don't always have hours, I just want answers. That's why I built https://llmchef.com I call it a prompt enrichment engine. I've curated over 100 recipes from a project called Fabric by Daniel Meissler. You can enter the basic unimpressive prompt and the recipe is applied to your prompt to give you a masterpiece.

Visit product View on Hacker NewsJun 10, 2024

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

74%74% 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, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: answers, way · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

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.

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

14%14% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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