2 posts tagged with "agents"

The way most people build software with LLMs today is: write something, look at it, ask an LLM to make it better, look at it again. Vibecoding. It's fast, it's surprisingly effective, and it's still fundamentally local search guided by human intuition.

Human intuition is a bad guide for knowing if something actually got better. You can feel like an iteration was good without having moved the metric that matters. You can iterate eight times and end up with a more sophisticated-looking solution that scores lower than what you started with. I know this because I ran the experiment.

I've lived and breathed AI and agents for 365 days of 2025 (and 2026 won't be any different). The AI boom of the last few years has been incredible to watch, but I keep coming back to the same few issues:

1. Energy is not scaling with demand.
2. When we say want autonomous AI agents, we don't really want autonomous AI agents.
3. Data is not scaling with demand and synthetic data will never be the whole story.