I started as a dancer. And like every dancer, I was always hunting for something that actually fit the moment, not just whatever was free and legally safe enough.
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
We recently discussed the changes that took place on the platform in 2025, so it s clear that the approach to Product Hunt will need to evolve as well.
Some features were removed, others were added, but there are still opportunities to gain visibility.
My journey in startups began 10 years ago, and I've launched 18 startups, most of which failed. Briefly on why they failed: 1. Contract Online my first startup in 2015, which was supposed to be an online service for remote signing of contracts for any transactions between individuals. A kind of analogue of a secure transaction. For this startup, I even managed to attract a business angel who invested $16,500.
Reason for failure: I had two lawyers on my team who discovered in the process that the legal framework at the time could not provide reliable grounds for protecting our users in remote transactions. The contracts would not have been considered legally signed. 2. Natural Products In 2015-2018, I became very passionate about healthy eating, but in the process, I discovered that products in all chain stores are full of chemicals, and stores with truly natural products are inaccessible to the majority. Hence, the idea emerged to create my own online platform where you could order natural products directly from farmers at affordable prices.
Reason for failure: For several years, I tried to launch this project, even trained as a baker of natural bread and tried to create my own farm, but in the process, I found that few people are willing to pay for truly natural products, even if these products were only 20-30% more expensive than market prices, and not 2-3 times more, as in premium stores. Hence, the market was so small that all my attempts were doomed.
Yesterday Google published a paper on a new model called MusicLM, which generates high-fidelity music from rich text descriptions. I haven't seen as much discourse about AI-generated music as I've seen for images and artworks. Are we too early on when it comes to music, or what do you think is causing that? What do you see the biggest litigation challenges to be?
