The API Economy is Coming and I'm Still Wrapping My Head Around It

I'm not a software engineer. I want to be upfront about that.

But I've spent the last couple of years building SaaS products, implementing AI into real workflows, and watching this landscape evolve at a pace that is genuinely hard to keep up with. And some things are becoming clear to me, even from where I'm standing.

The companies treating AI like a product are already behind. The real shift is happening underneath all the chat interfaces and demo videos, and it's a lot more interesting than the headlines suggest.

The Thing I Keep Coming Back To

As I've gotten deeper into building with AI, one thing keeps standing out. The tools that are going to matter aren't the ones with the best interface. They're the ones that can talk to everything else.

APIs. The plumbing. The part nobody puts in a marketing video.

When AI is embedded in every tool you use, the question stops being "does this tool have AI" and starts being "can this tool's AI actually know what's happening everywhere else." A model that only sees what lives inside one platform is working with blinders on. The real power shows up when your AI can pull context from across your entire stack and actually understand the full picture.

I find this genuinely exciting in a way that's hard to explain to people who aren't in it. We're in this weird window where the rules haven't been written yet and the companies paying attention are going to have a real advantage over the ones waiting for it to settle.

The Fragmentation Problem

Here's something I see happening and it's a little uncomfortable to think about.

Right now most teams are using AI in completely independent ways. Someone on CS is using ChatGPT for customer emails. Sales has their own tool. Product is summarizing feedback in something else. Nobody made a decision about this, it just happened organically because the tools are cheap and accessible and everyone found their own way in.

On the surface that seems fine. People are being productive. But zoom out and the picture gets messier. Your customers are interacting with different voices, different tones, different levels of context depending on who they're talking to and what that person's AI happened to generate that day. Nobody signed off on that customer experience. It just emerged.

That's a CX problem wearing a technology costume.

This Is Where RAG Gets Interesting

I'll be honest, a year ago I didn't know what RAG stood for. Retrieval Augmented Generation. It's the architecture that lets AI pull from your actual data before generating a response instead of just relying on what it was trained on.

So instead of asking an AI a question and getting a generic answer, a RAG-powered system goes and finds the relevant context first. Your customer's history, your internal playbooks, your documented processes. Then it answers based on that.

The difference in output quality is significant. And once you see it working well you can't really go back to thinking a generic chat tool is good enough for anything that touches a real customer relationship.

But RAG only works if the underlying data is clean, organized, and in one place. Which means fragmented teams using fragmented tools are actually moving backwards on this even as they feel like they're moving forward.

Where I Think This Is All Going

(TL:DR I have no idea). This space is moving fast enough that anyone claiming certainty is probably wrong. But my working theory is that the software tools that win the next five years are going to be the ones that treat their API as seriously as their UI. The ones that are designed to share context, not hoard it.

And the companies that win are going to be the ones that get intentional about how their teams use AI, not as a technology decision but as an operational one. Who owns the context? Where does the customer knowledge live? What does our AI actually know about our business?

These feel like CX questions to me as much as they feel like IT questions. Maybe more so.

I'm still figuring a lot of this out. But that's kind of what makes it the most interesting time I've ever had doing this work.