Lauren Crichton

speaker

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

Lauren Crichton’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

And you've described wizards as being, like you said, almost unverifiable, impressive and opaque.

Do you think that those characteristics are a temporary feature of the current architectures or are they a permanent one?

And how does that make you feel personally that we would be developing technology that we don't fully understand?

And of course, AI is now increasingly writing code for itself to improve itself.

And so we might end up in a situation where we've created AI that is creating new AI in maybe even languages that we wouldn't understand.

It's interesting you talking about how opaque humans are.

And it's interesting thinking about that in the context of enterprise AI as well.

Obviously, we're trying to get to a stage where agents are doing work.

And in order for them to do work, they need to actually understand how work gets done.

Unless you're in some kind of perfectly documented organization, there's still a lot of contextual information that lives in people's heads.

So how might that be a limiting factor to what AI agents would actually be able to do inside organizations?

And have you seen any good examples of organizations that are quite advanced in AI or AI agent implementation figuring out how to get those loops and those handoffs between humans, agents, and systems?

I think there's an interesting bridge there to talking about wizardry again and the paradox that you've identified, which is that every time we cede a task or hand over a task to an agent and

We're not doing that task ourselves.

We are then losing the opportunity to actually build the expertise that we would need in order to form the judgment that is required to effectively assess the AI's output.

So I'd be curious to know, how do we resolve that paradox?

There's lots to unpack there.

I think your comment about agency reminds me of something that you had actually said to Joel when the two of you met last year, which was that we as humans, we get to make choices.

We have agency over what we're doing.

And it sounds to me like you're still very bullish on the idea that we do.

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