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I created a tool that converts designs into responsive HTML email

Hacker News

I created a tool that converts designs into responsive HTML email

Hey HN! Like many of you, I absolutely hate writing HTML emails. Nested tables everywhere, client compatibility issues, and that feeling when you need to modify something in those deeply nested elements... pure pain. While there are plenty of drag-n-drop email builders out there, I still found myself diving into code for custom stuff. That's when I discovered MJML - it's amazing at handling all the tedious HTML email stuff and makes the code actually maintainable. Then I thought - what if I could combine MJML with AI to just... look at a design and write the code for me? After a few months of development, I built [paste2email.com]( http://paste2email.com ). How it works: 1. Paste your email design image (or just describe what you want in plain text) 2. The latest Claude-3.5-Sonnet(2024-10-22) model generates MJML code for you 3. Use the built-in variable system to easily swap content 4. See live preview(mobile & desktop) as MJML compiles to HTML 5. Export everything with Handlebars support - just plug in your variables and you're done 6. Connect it to your email service (like nodemailer) and ship it! \To get you started, you’ll get 10 free credits. That’s enough to generate 3 emails and tweak one of them, or go for 2 emails with 4 rounds of refinements. --- I built this specifically for developers who, like me, hate the tedious parts of HTML email development but need more control than drag-n-drop builders offer. Would love to hear your feedback! You can try logging in with email to check out an actual email I created using this tool.

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
96%96% 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: claude, model, email · Missing: mac, agents, macos
94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: builder · Missing: plus, platform, intuitive
50%50% 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
46%46% 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: month · Missing: mobile apps, ios, personal
42%42% 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
16%16% 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.

Correct prediction on native model

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