I wanted to take a moment to thank each and every one of you for the incredible support during our launch week. Seeing VolumeHub climb the rankings and reading all your thoughtful comments has been absolutely amazing. The fact that 200+ people upvoted and believed in this project means the world to me!
As usual, Y Combinator came up with segments that are worth investing:
1. Cursor for Product Managers
2. AI-Native Hedge Funds
3. AI-Native Agencies
4. Stablecoin Financial Services
5. AI for Government
6. Modern Metal Mills
7. AI Guidance for Physical Work 8. Large Spatial Models 9. Infra for Government Fraud Hunters 10. Make LLMs Easy to Train
I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market. That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.
In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.
For those of you building AI or compute-intensive tools:
New AI models pop up every week. Some developer tools like @Cursor, @Zed, and @Kilo Code let you choose between different models, while more opinionated products like @Amp and @Tonkotsu default to 1 model.
Curious what the community recommends for coding tasks? Any preferences?
Yesterday, I had an unpleasant experience. For a few minutes, I lost my LinkedIn community of several thousand people (TL;DR: I was falsely accused of using suspicious software).
Fortunately, I got my account back but it was a strong reminder that we don t own platforms, nor our profiles on them.
On Product Hunt, I can see many people launching their products using "vibe-coding tools" like @Lovable , @bolt.new , or@Replit
I reckon many people who created something with them are usually developers who didn't have enough time for building a side idea before, but with AI, they could make it happen.
