What's going to happen to central buyers and platform teams and IT teams if agents are making the decision?

It's very clear that coding is pretty much dead, but engineering is very much not.

Every time you have a technical epoch, you have to redo everything,

and we forget that every time.

I don't think people even have a common definition of a bubble.

If AI demand is real and accelerating,

why does everything still feel constrained?

Why does a technology that's clearly delivering value

also feel harder to scale than expected?

We've seen this pattern before. In early technology shifts, it was easy to assume the hard problems

were solved. Infrastructure was treated as finished, then usage surged. Systems built for a smaller world

began to fail. Networks strained, power, physical footprint, and coordination became

first-order constraints again. Each new technical epoch forced a rebuilding of the stack.

AI is creating that moment now. The demand is not speculative. Companies are deploying models,

budgets are moving. Real productivity gains are already showing up, and yet nearly every

part of the system feels tight. Computer is scarce. Data centers take years to permanent build.

Power is difficult to secure. Regulation moves far more slowly than the technology itself.

This has led to two dominant stories. One says we're in an AI bubble. The other assumes

scale will smooth everything

out. Neither fully explains what's happening. Demand continues to outpace supply and the biggest

bottlenecks increasingly sit outside the models themselves. This is especially visible in

enterprise software. AI is often framed as a threat to SaaS, but SaaS was never hard because of the interface.

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