Ethan Mollick

speaker

673 appearances 1 recordings 1 series first heard Jul 2026 last heard 9 Jul

Ethan Mollick’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

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Strange Loop Podcast · Ethan Mollick | The long way is the shortcut: experiments over AI playbooks · 9 Jul 2026 podcast

Like it had to be closely watched.

It made lots of mistakes.

There were lots of errors.

It couldn't take action in the world.

Now hallucination rates have dropped.

They're not zero, but they've dropped.

Models can do multiple hours of work independently.

That work is judged by independent people to be as high quality as experts work often.

And that changes how you do things.

So I think there have been a couple of inflection points that you couldn't predict exactly when they happened that have occurred.

I think a lot of us knew who were close in the space knew the agentic moment was going to happen.

I think it was somewhat of a surprise that happened as quickly as it did and that the impact was as large as it was, right?

So it went from AI as toy to, oh my God, cloud code is here and now we have to change how we do all coding and all work.

And

I think that has been a relatively rapid change.

I've also been somewhat surprised in the last year about how much there was a pivot in early fall, even before that, with companies going from a conversation about, is AI worth doing, to that being answered and being like, how do we use AI?

I also think that just in a general purpose, I think the continued acceleration has been a little surprising.

I think that we were all expecting AI to keep getting better, but there really has not been a lot of slowdown of exponential growth, which I think is interesting.

So everything is downstream of AI abilities, right?

The jaggedness of those abilities, the fact that it's good at some stuff and bad at some stuff, is a, I think, it tells us what humans do, what our work should look like, where AI might fail, why it's problematic to integrate in.

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