I read the YC RFS section on AI multiple times. Here's what they're asking for that the current market isn't delivering yet.

The RFS is aspirational, it describes what YC wants to see, not what's currently being built. The gap between the two is where the opportunity is. Reading the current RFS AI section carefully, here's what I see being asked for that the batch hasn't fully delivered: **Full autonomy in high-stakes workflows.** The RFS language suggests they want agents that take consequential actions without human review not just low-stakes tasks. The current market has lots of agents for low-stakes automation. High-stakes autonomous action (financial decisions, medical recommendations, legal actions) is almost universally still human-in-the-loop. The companies that figure out the trust infrastructure for high-stakes autonomy will be very interesting to YC. **Agents that learn from production usage.** Not fine-tuned once and deployed. Continuously improving from every action they take. The RFS language about AI that "gets better over time" implies a learning loop that most current agents don't have. The companies with genuine continuous learning in production are rare. **Cross-system orchestration.** Single-system agents are common. Agents that coordinate across 5-10 enterprise systems to complete a workflow end-to-end are still mostly aspirational. The integration complexity is the barrier. Also the moat. If you're building in AI agents and the current market looks crowded look at these three gaps. Not because the RFS tells you what to build. Because the gaps represent real technical and trust challenges that haven't been solved yet. Solving them is harder than building another wrapper. That's the point. What do you think, which Infrastructure for AI agents will boom in upcoming years...?