Where This Is Heading Videos

Lightly edited for clarity.

Demis Hassabis, who’s the CEO of Google DeepMind, recently stated that we are in the foothills of the Singularity. Jensen Huang, who’s the CEO of Nvidia, has stated that he thinks they’ve already achieved AGI. And AGI, if you’re not aware, is artificial general intelligence. People love to talk about AGI. It’s simple to understand. It’s the benchmark which we have: an AI that’s just as good as a person is at doing whatever.

But I think the reason that most people really like to talk about AGI is because it’s kind of scary. It’s once we have AGI, then what? Right, if I have an AI that’s as good as a person at doing a job well, then why would you hire the person for 100 times the price when you could have AI do it? And so it’s terrifying, the idea that we’ll have AGI that is as good as us at doing effectively anything. So that’s scary.

I just don’t think it matters. Like, what we have with the current technology with AI is already so powerful and transformative that whether or not we have AGI is almost beside the point.

I haven’t made videos for a month because I’ve been busy, and most of what I’m doing at work is business process consulting, business process automation, and modernization. So we are talking to companies about how to reorganize their business processes within their organization to effectively take advantage of AI. It’s what do we need to do to change the way we do work to take advantage of this technology, to be able to do more work faster and cheaper?

And this is the change that most large organizations are going through now. These are the things that they are working on. The scope and scale is massive. It’s effectively every business process in every organization can be affected by AI.

And so whether or not we get to AGI, whether or not we already have AGI, if you’re waiting for AGI to figure out the then what moment, you’re too late. We’re already at the then what moment.

Lightly edited for clarity.

The more I work with AI, the less convinced I am that the intelligence of the model is currently the bottleneck.

The models have improved incredibly quickly, right? A few years ago, it felt kind of like a high school student, and today they feel more like pretty capable professionals. And we can debate how smart the models are, but it’s obvious how quickly they’ve improved. And it makes me wonder how much additional intelligence will actually change the equation.

If I think about why experienced people are valuable, it’s easy to say experience, but what does that really mean? Some of it lives in people’s heads. A lot of it lives in people’s heads. But a surprising amount of it actually gets written down, like architecture decisions and design documents, emails, meeting notes, code, project plans, lessons learned, and retros.

People naturally accumulate knowledge by doing the work, and AI doesn’t. But that doesn’t mean that AI has to learn it the same way that we do.

If every design decision, trade-off, meeting, project success story, and failure, if all those things become searchable and referenceable, how much smarter do the models actually need to be?

The work we’re gonna be doing over the next decade, the integration of AI into business processes and into people’s lives, is taking decades of accumulated organizational knowledge and making it available to models, not just making the models smarter and smarter.

Lightly edited for clarity.

I spend all day, like all day, working with AI, and I still haven’t seen an AI that could replace any of my team members.

What I’ve instead seen is people becoming dramatically more capable because of AI. Not replaced, but amplified.

And the conversation around AI often gets framed as humans versus AI, but there’s a much more reasonable possibility, which is AI and humans integrating and working together.

I haven’t seen AI replace developers or architects or project managers, or business analysts, marketers, any role that I work with regularly.

But what I have seen is people becoming more productive, more capable, taking on larger problems, expanding their skill sets.

The future isn’t AI taking over everything that people do. The future is people becoming much more capable because they use AI effectively.

Lightly edited for clarity.

So I started this week talking about how quickly AI is getting smarter, and I’m ending the week with how intelligent people really are.

I spent a lot of time this past week with my team on multiple client projects and software delivery challenges. And it’s not about how much AI can do, but it’s about how much judgment people apply subtly without even really thinking about it.

AI is incredible at generating code and content and synthesizing information and finding patterns in things. But this week, as I watched people recognize incomplete requirements, spot contradictions before they became problems, balance competing priorities, navigate organizational politics, and ask questions that completely changed the direction of a conversation, I noticed that none of those things looked particularly remarkable while they were happening.

The more experienced someone is, the more invisible their expertise becomes.

At the beginning of this week, I wondered whether AI was approaching the capability of a mid-career professional. And by the end of this week, I wasn’t thinking nearly as much about AI. I was thinking about how much of professional expertise is really judgment.

The more I work with AI, the less impressed I am with memorized knowledge, and the more impressed I am with human judgment and nuance and understanding. And those things are a lot harder to automate than people think.