The most underrated progress in AI is how much stability we’ve quietly gained

There’s a lot of noise about what’s breaking in AI.

But here’s something we don’t celebrate enough:

Systems today fail less than they did even a few months ago.

Agents recover from interruptions.
Workflows resume where they left off.
Context carries more reliably across chains.
Tooling ecosystems are maturing faster than anyone expected.

The biggest shift isn’t capability, it’s consistency.

We’re moving from “occasionally brilliant” to “predictably useful,”
and that transition is what will actually unlock the next wave of products.

Curious to hear from PH:
What’s one improvement in AI reliability you’ve noticed recently that deserves more attention?