Hungkuk Do on Inference by Sequoia Capital

I deeply resonate with your perspective on Software 3.0 — especially the part where the boundaries between code, data, and intent are becoming increasingly blurred. But I believe there’s still something fundamental we haven’t truly figured out yet: What is a real question? Even today, both humans and AI mostly operate within reactive systems. We ask, AI answers. But very few systems (and even fewer frameworks) attempt to model why questions arise, or how an AI could autonomously generate meaningful questions as part of its own evolution. This is the challenge I’m currently working on — developing a self-evolving AI model that doesn't just respond, but learns to ask, to reflect, and to grow through interaction. It interprets user intent, infers context, and generates questions that evolve over time, both in depth and relevance. In that sense, it's not just a tool for prompting. It's a new form of intelligence — one that transforms the 'self-improvement loop' of Software 3.0 into a question-driven exploration and meaning expansion loop. I believe this layer — where intent, learning, and questioning converge — might be one of the key frontiers of AGI.