As 2025 came to a close, conversations about AI swung between excitement and anxiety. Markets debated bubbles, capital cycles, and constraints, while researchers quietly shipped systems that worked.

In this audio essay, Nathan Benaich takes stock of what AI actually delivered in 2025 — drawing on recent writing by Tim Dettmers, Dan Fu, and Andrej Karpathy, alongside conversations with Sebastian Borgeaud at Google DeepMind.

Rather than speculating about distant futures, this episode focuses on what changed in practice: why AI crossed a usability threshold, how constraints reshaped progress rather than stopping it, and why the shift from models to systems matters more than any single benchmark.

The result is a grounded look at AI progress as it enters 2026 — not as hype or prediction, but as an evolving system that continues to compound.

Read the full essay at press.airstreet.com