We ve just launched an innovative no-code platform called CodeFlow. Fully bootstrapped and built with care, it s a prototyping engine that turns natural language and Figma designs into working React apps - fast.
CodeFlow generates infrastructure-native, accessible code you can edit directly in the browser.
CodeFlow is a web-based platform that turns your ideas into working applications, fast.
Describing an app in plain English or uploading a Figma design, CodeFlow generates clean, semantic React/HTML/CSS code with built-in accessibility and styling.
Axiom's mission is to build a self-improving superintelligent reasoner, starting with an AI mathematician, and for that, Carina Hong has raised $65M in seed funding.
I keep seeing advice like use this model for the easy stuff and that one for complex problems. But it makes me wonder what really counts as a complex problem for an LLM?
For us, complex usually means lots of steps, deep reasoning, or tricky knowledge. But for AI, the definition might be different. Some things that feel easy for us can be surprisingly hard for models, while things that seem tough for us (like scanning huge datasets quickly) might be trivial for them.
Hey Makers I m exploring options for managing subscriptions, payments, and authentication in a super simple way. Ideally, something that s: 1. No-code / low-code friendly 2. Easy to integrate without a ton of setup 3. Handles the boring stuff like billing, invoicing, cancellations, and user access automatically
I ve looked at a few tools, but many feel too heavy for a small MVP. Curious to know: What are you using right now? Any lightweight tools that worked really well for your early-stage product? Bonus if it has a generous free tier or is affordable for indie founders. Would love to hear what s working for this community before I commit to something!
