The Business Engineer

The Business Engineer

The Map of AI Redrawn

Gennaro Cuofano's avatar
Gennaro Cuofano
May 24, 2026
∙ Paid

A decade ago, I started covering the intricacies of the AI ecosystem. As early as 2016–17, I described AI as a multi-layered stack, almost like a layered cake of interconnected technologies and infrastructure.

A few years later, right after the launch of ChatGPT, I began mapping the AI landscape in a far more granular way. The reason was simple: the ecosystem was finally crystallizing around a few critical building blocks.

More importantly, however, something I had emphasized for years became impossible to ignore. This entire ecosystem has been shaped by constraints, bottlenecks, chokepoints, and scarcity at every layer.

In an era where AI represents the next computing paradigm, this cascading ecosystem revealed how unprepared we actually were to make it work at scale.

From that realization, I developed the idea of the AI Supercycle: the notion that the AI industry resembles the semiconductor wave that began in the 1940s and 1950s, matured in the 1970s, and ultimately enabled the first great computing wave.

That wave gave us the Internet, the cloud, mobile computing, and all the sub-waves attached to it, from browser wars and search engines to social media and now AI super apps.

Interestingly, until just a couple of years ago, I believed it was sufficient to update the AI map once a year. Then reasoning models started to emerge, alongside additional scaling laws converging with pre-training. At that point, it became clear to me that the landscape needed quarterly updates instead.

Yet another shift is happening now. We are entering a phase where four scaling laws are simultaneously shaping the AI ecosystem, while several converging forces are radically transforming the physical layers underpinning AI itself.

And to be clear: while the physical infrastructure supporting the AI revolution will likely take more than a decade to fully mature, entirely new paradigms will continue to emerge on top of it in parallel.

For that reason, don’t be surprised if this map evolves rapidly. The AI paradigm caught most of us by surprise, and understanding it requires a high degree of mental flexibility as the landscape keeps shifting beneath us.

The May map described the geography — seven parallel competitive layers, each with its own clock. Seven weeks later, the architecture has revealed itself. The layers are still there, but the unit of analysis has changed. Companies stopped competing layer-by-layer and started binding multiple layers together through three distinct geometric strategies.

Three spines now cross the map. Two new buyer poles have emerged inside it. And one cascade is now flowing downward through four layers, changing the strategic logic at each level.

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