Nathaniel Whittemore

In the past, cyclicality in chip pricing has punished long-term investment, with new plants often missing the window of peak demand.

SK Hynix's new plan suggests that they now view AI-driven demand as a structural change, and they're deploying capital to take advantage of it.

Now, to be clear, they're talking about doubling capacity by the end of the decade, so this is unlikely to do much for the chip crunch in the short term.

Indeed, Chairman Shea Tewan told reporters that the shortage could last until 2030.

And yet still, the deeper investment is the right policy, with Chairman Shea arguing, the whole AI industry needs to be more sustainable.

We have to continue to grow, but sudden jumps in price can become a problem and actually hurt sustainability.

So lots of big movement today, but that is going to do it for the headlines.

Next up, the main episode.

One of the most important AI questions right now isn't who's using AI, it's who's using it well.

KPMG and the University of Texas at Austin just analyzed 1.4 million real workplace AI interactions and found something surprising.

The highest impact users aren't better prompt engineers, they treat AI like a reasoning partner.

They frame problems, guide thinking, iterate, and push for better answers.

And the good news?

These behaviors are teachable at scale.

If you're trying to move from AI access to real capability, KPMG's research on sophisticated AI collaboration is worth your time.

Learn more at kpmg.com slash us slash sophisticated.

The listening, the thinking, the speaking.

You just stream audio in and get your agent's voice response back.

We're talking about things like outbound sales calls that actually qualify leads.

customer support that handles complex requests without a script, scheduling agents that sound like a human assistant, and you can build one in five minutes with one API.