YepCode Recipes. Connect Services and APIs with a Zapier for Developers

Hacker News

Hey HN! YepCode is the swiss-army-knife for development teams that allow to connect any service and API in an agile way just writing source code and using a serverless environment. It allows to build complex integrations forgetting about any devops hassle, and it's the perfect alternative when no-code tools may not fit: open data streams, huge amounts of information, complex implementation logics,... or when you don't want to have vendor lock-in with any platform. YepCode Recipes are the best way to get started. They provide both source and target snippets to move information between services and APIs and they may be cloned in your YepCode account with just a click. Some references: [1] YepCode PH launch some months ago - https://www.producthunt.com/products/yepcode#yepcode [2] Explore our docs - https://docs.yepcode.io/ [3] Sample video with full integration implementation: https://www.youtube.com/watch?v=zAMlFrVnD_c Having a quite mature product, our main focus right now is the go-to-market strategy, and we are trying both product-led-growth approach (any user may start with a FREE account) and also building an outbound sales strategy for enterprise companies with development teams. Any suggestion with the go-to-market or feedback about the product will be highly appreaciated!

Visit product View on Hacker NewsAug 11, 2022

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

93%93% 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: user, using, code · Missing: mac, agents, macos

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

70%70% 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: video, month, way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

18%18% 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, crypto

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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