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Flyde – an open-source visual programming language

Hacker News

Flyde – an open-source visual programming language

Hi HN! I’m Gabriel, and I’m happy to share a project I’ve been working on for the last few years: Flyde, an open-source visual programming language. Check out the interactive examples and online playground on the website: https://www.flyde.dev . In my last role as an engineering manager for a B2B-oriented product, I authored and reviewed many diagrams for backend applications, mostly for integrations between 2 third-party services. Some of these diagrams were elaborate enough that I started dreaming of a way to simply run a diagram as is; I imagined a “run” button on the top-right corner of the screen that would execute the diagram without the need to translate it into code. That led me down a rabbit hole of exploration and experimentation, from tools like Zapier, Pipedream and Make, which are great for automating “backoffice” stuff, and up to NodeRED, NoFlo.js and the great work of J. Paul Morisson on Flow-Based Programming. I failed to find a tool that would answer my needs - a tool that balances a new level of abstraction, manages to stay powerful and flexible, and most importantly, integrates with the existing ecosystem, and doesn’t replace it. I built Flyde as an attempt to answer that need. Flyde is designed to complement and enhance traditional textual coding, not to replace it. It includes a VSCode extension, it seamlessly integrates with existing TypeScript/JavaScript code and can run on Node.js and in the browser. I believe that as we delegate more coding tasks to AI, we’ll assume the role of an architect rather than a programmer. This shift will require tools that focus more on orchestration and high-level troubleshooting and less on low-level functionality. I’d love to hear your thoughts and feedback on Flyde’s direction!

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, visual, tasks · Missing: mac, agents, macos
93%93% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, pipe · Missing: https docs, excited, just released
83%83% 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, personal
44%44% 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
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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