Cal Newport

They don't actually get the thing done.

But they said, oh, what LLMs are good at is producing code that compiles and we can actually like check that it works.

And so this is where this whole vision has changed is that all applications and internet websites should have a code accessible API that you can expose and that an LLM can write a program that will then

access that API.

So we don't need to teach the LLM how to use Excel.

It'll write a Python program that'll call hooks into Excel.

The problem with this is no one wants to open up their application to just agents in general.

If I'm Microsoft, I was like, I don't want, I want to write a custom tool

For my program, why would I expose my program for anyone else to use it?

But your original question is a big one.

To what end?

I've been writing about this recently, especially with work and AI.

You've got to find the real bottlenecks, right?

Yeah.

It's the drunk looking for the keys under the streetlight.

There's a lot of this going on where this is what we can do with AI right now.

then this now becomes like the key to productivity.

But the real bottlenecks in people's work is often not the things that we're trying to aim AI at.

Like, I don't know people are super frustrated at booking a plane ticket online.

How often do you book plane tickets?