The AI Bifurcation of Tech by Neevash Ramdial

The AI Bifurcation of Tech

It's unclear right now how AI is going to play out for most companies, and I don't think anyone has a clean answer yet, including me. But there's a pattern I keep coming back to, and it has less to do with what AI eventually becomes and more to do with what it can already do.

I don't think the capability curve breaks at some single moment we'd call AGI. It just keeps climbing. Each release adds capability somewhere, and we don't need to reach the top of the curve for the bottom of it to start reshaping things.

This past Tuesday at Google I/O, Antigravity 2.0 built a functioning operating system from scratch in twelve hours. It spun up 93 sub-agents, processed 2.6 billion tokens, ran roughly 15,000 model requests, and cost less than a thousand dollars in API credits. Then they ran Doom on it live. When the keyboard drivers were missing, they asked the agent to write them on stage, and it did.

Take the staging with whatever grain of salt you want. The point underneath is what "good enough" looks like in mid 2026. Many small agents, running in parallel, cheaply, reliably enough to compose into something that actually boots. That's the engine worth paying attention to. Not because of where it ends up, but because of what it can already do.

A capable agent loop, called many times in parallel, with reasonable cost and reasonable latency, is enough to recreate most of what the application layer of software currently sells. The curve keeps going from here. The question that follows is which kinds of companies sit downstream of that engine and which don't.

Who sits downstream<br>The companies pulling ahead right now share a property that has very little to do with their marketing and not much to do with strategy either. Their products are increasingly being consumed by software, not by people.

Turbopuffer crossed $100M in annual revenue this past March, nineteen months after hitting their first million. The company is profitable, has raised less than a million dollars total, and powers vector search for Cursor, Anthropic, Notion, Cognition, Harvey, and a dozen other names you'd recognise. Modal closed an $355M Series C at a $4.65 billion valuation this week. Months following their series B round in September of 2025. Mintlify just closed a $45M Series B from Andreessen Horowitz, and their own data tells the clearest version of this story I've seen. Across the documentation sites they power, AI agents now account for almost half of all traffic.

None of these companies pivoted into this. Most of them existed before the agent wave and were already well-regarded inside the developer tools world. They didn't bolt a chatbot onto a landing page or rebrand as AI-native. The product mostly looks the same as it did two years ago.

What changed is who their customer is becoming. The buyer is still a human writing the cheque, but the consumer of the API is increasingly an agent. And once buyers start choosing tools based on what their agents use well, the two collapse into the same thing. An agent reaches for the same APIs a human developer does, except it reaches faster, more often, and with less patience for anything that gets in the way. None of this required those companies to do anything new. They were already clean enough, well-documented enough, and API-first enough that a non-human caller could pick them up and use them without help.

The DX-first orientation, the obsession with making the developer's first ten minutes feel effortless, the API-first design, all of that predates agents by years. The agent wave didn't create them. What it did was add a second audience to the same product. One that never sleeps, never gets tired of reading docs, and calls the API like its life depends on it. The pre-existing quality is what made them ready. The agents are what made the growth look exponential.

Meanwhile most of the industry is having a much harder year. Layoffs, flat growth, long sales cycles, a general sense that the air has changed. The easy story is that these companies failed to "do AI." That's mostly wrong. Plenty of them have AI features. The harder truth is that their products were built for humans to look at and click on, and that audience isn't growing the way the agent audience is.

The line that matters isn't AI-native versus legacy. It's whether your product can be consumed by something that doesn't read landing pages.

Back to fundamentals<br>Fundamentals still Matter (Google IO 2026)

Strip away the agent framing for a second. What does a company need to do to be useful to an agent? Have a clean API. Have docs that explain it without marketing fluff. Be reliable. Be fast. Scale without falling over. Don't hide behaviour behind cute abstractions.

That list is identical to what made a developer tool great in 2010.

The agent wave isn't introducing new product requirements. It's enforcing the old ones, harder. A human developer will...