Formula8.ai – A formula-based approach to AI prompts

Hacker News

We just launched our new product, which we developed ourselves out of the need to have a better abstraction layer for ChatGPT. Yes, we know; another AI content tool. As a marketing agency, we produce different types of content such as newsletters for large public companies. We found ourselves typing the same prompts over and over again, even though the structure was often very similar or identical, except for the actual content or topic. Formula8 offers us an easy way to develop parameter-based prompts for this and combine them in templates and make them smarter with helper functions, such as automatically crawling the content of an external URL for article teaser excerpts. Frankly, we didn't really plan to turn it into a real product originally, but since our team adapted it super fast and we can certainly give those who have the same problem a useful tool with it, we're introducing it today. Happy if it seems to be helpful to anybody and to collect your input or ideas.

Visit product View on Hacker NewsJul 30, 2023

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

82%82% 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: new, chatgpt · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% 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 released

41%41% 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, para · Missing: mobile apps, ios, personal

40%40% 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, smart · Missing: web3, crypto, cryptocurrency

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

Incorrect prediction on native model

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