Useful no-code tools that we used to build 35 startups

Hacker News

Hi! I'm leading a startup agency (I'm a dev turned CTO turned CMO). We're building products for 14 years and our core background is product engineering. We use lots of no-code (and full-code) tools to build startups for our clients + launch our own startups. I was surprised that many founders still don't know much about no-code tools. So I've collected all the useful tools that rather we, our clients or close network used to actually build startups. I'm curating this list manually and will regularly update it to show the current stable stack + few new fancy categories. The current categories include: Landing Page Builders, Forms & Databases, Blogs & Newsletters, Design & Creator Tools, Product Management, Automation, Low-Code App Builders, Analytics, Customer Chat, CRM and Sales, Payments, Marketing, SEO, SMM, DNS & Domains, Banking & Accounting, Formation & Legal, Capital & Growth, Startup Communities Hope you'll find something useful for your startup! Thanks

Visit product View on Hacker NewsOct 30, 2023

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

86%86% 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, code · Missing: mac, agents, macos

82%82% predicted probability of success on Product Hunt, 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

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

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

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

24%24% 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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