So the board goes to the CEO, and what does the board say?

We need more AI.

And what does the CEO said? Oh, okay, I'll get like a consultant to do more AI. And then they have some centralized project that nobody knows how it works. They haven't aligned their operations and those things will fail. The funniest concept that the more code we write, the less we would need engineers, it would be the opposite because now your systems are even more complex than before, which means that you're going to be running into even more challenges of when you need to do a system upgrade

or when there's downtime and you have to figure out like, well, how do I fix that problem

or when there's a security incident? So yeah, we're just getting started with the jobs on this front.

They're going to hit a wall at integration.

The thing that's not different about AI

and that agents don't fix that nothing fix

is that any enterprise of a thousand people or more

or that's older than 10 years

is just a massive stuff that's sitting there waiting

to be integrated.

And you can't just say it's gonna integrate. AI actually doesn't help to integrate anything.

AI feels like it's moving fast.

And for many companies, the real transformation is just getting started.

There's a growing gap between what's possible in Silicon Valley and what's being deployed inside large organizations.

Engineers are already shipping with agents and new workflows,

while enterprises are beginning to adapt those capabilities to more complex systems and real-world use cases.

That creates a moment of opportunity.

The tools are getting more powerful,

and companies are learning how to integrate them into existing workflows, data systems, and decision-making processes.

At the same time, there's a deeper shift underway.

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