business engineer's manifesto!

OpenAI announced its new model, GPT-4o, how would a business engineer look at this event? And how is Google counteracting? This is a war on who gets the Apple's deal!

Just yesterday, as OpenAI announced its new model, GPT-4o, the response was twofold: people were either ecstatic about it or underwhelmed by that launch.

Now, the perspective I want to give is how a business engineer would think about it.

Before going there, what was the launch about?

I loved the definition that former Tesla and OpenAI engineer Andrej Karpathy gave about it on X, referring to GPT-4o, he said, that is: “a combined text-audio-vision model that processes all three modalities in one single neural network, which can then do real-time voice translation as a special case afterthought, if you ask it to.”

In other words, this is the Siri or Alexa we always dreamed about!

So, in a way, we’re back to the 2018 vibes (when voice search was all the rage), but this time, this isn’t anymore about search; it’s a whole different market!

A market ready to cross a billion users in the next 2-3 years…

Why?

Here comes the business engineer’s perspective!

The major mistake that both ecstatic and underwhelmed people made by looking at the launch of GPT-4o is to guess its technical capabilities.

Whereas a business engineer would have a different perspective, where not only technology and the technical part is not all that is.

But instead, technology is a means to an end. That end is the potential for technology to bridge the gap between value and distribution at scale, thus moving toward mass adoption!

In market expansion theory, I’ve explained how new markets are created on top of existing ones, yet they expand many times over these to create a whole new beast!

The major mistake (especially for technical people) is to look at the new market as if it’s simply a projection of the old market when it might seem so, but it’s not!

The new market initially resembles the old one, but that’s the only appearance that can fool those who don’t look at the big picture (like a business engineer would do instead).

In fact, going back to the example of GPT-4o, outside arguments about its really technical improvements compared to other models (it doesn’t matter) or the fact that this is only a UX change (it matters even less).

What matters is that this is a new interface, combined with some important technical tweaks, that has been developed with one thing in mind (if I have to think for a moment like Sam Altman would): scale to a billion users as soon as possible!

To do that, OpenAI is redefining the whole market, creating what apparently seems a revival of voice search (2018 vibe) but with a whole new twist, where these real-time assistants are able to perform any task at hand.

In short, this has the scaling potential of mobile search (billions of users) but the stickiness of social media (increased usage by many times over).

Those two things combined might create a whole new market, which for now (especially practitioners used to see this as “search”) we’ll call an extension of search.

But that in a few years it’ll be something completely different!

Let’s remember that where search connected users to tools they could use for their productivity.

This new set of tools, like GPT-4o, not only helps you find what you need, but they execute on it!

That’s a much, much larger opportunity….

Last but not least, Apple is ramping up its AI operations by trying to close a deal with both OpenAI and Google to integrate their generative AI into the iPhone (the new AI Siri that finally does what it promised, transforming the iPhone into an everything real-time assistant), we’ll see things spreading up on that front.

Indeed, today, Google I/O (its yearly developer conference) will introduce something similar, and for the first time, we’ll have Demis Hassabis, CEO of DeepMind (now merged into Google Brain), on the stage!

And guess what they might announce?

Something very similar to GPT-4o, also recalling the fact that Google was the first to introduce something similar in 2018 (Google Duplex, whose underlying infrastructure was slightly different from transformer-based).

What’s the point here?

This is a fight to see who will take the new deal with Apple, a deal that redefines the digital landscape and scaled distribution pipelines for millions of businesses worldwide.

Indeed, where for the last 30 years, most of the digital distribution went through search, now, with the capabilities of these real-time assistants, this might go toward new pipelines (like Siri) with a massive restructuring of the whole landscape, based on this new market!

Are you ready for it?

Now, back to the basic rules of the Business Engineer, in what I defined the business engineer’s manifesto!

With a short premise:

In the last decade, I've been looking at thousands of companies, building from scratch a few tech business models, and, in the process, developing my own way of looking at the business world.

I named Business Engineering (this is an entirely different view from the classic definition of it) to mean it is an intersection between three core disciplines:

Business engineering is a way of thinking that combines various disciplines.

Among these disciplines, there is business modeling, which helps business people test the underlying assumptions of a business quickly.

The business engineering manifesto moves along a few fundamental principles, which I outline below: