Amodei’s ‘exponential’ claims about AI are proving true: Here’s what has already changed

After that early (relatively easy) success, I grew more ambitious and started building increasingly complex applications—from a custom-built feed reader app to a minimal teleprompter that sits next to my laptop camera. I even made a few iOS games that are now available on the App Store.

As my confidence grew, so did the ambition of the code I produced; the more I understood what AI was capable of, the more full-featured and well-designed my apps became. To the point where I now have three-four apps in various stages of development on my computer, and a GitHub page that is dark green with activity.

I am a lawyer who does not know how to code. I should not have been able to build an app, let alone the half-dozen apps I have so far. That I did is not because some latent programming talent has been unlocked within me, but because frontier AI models can now translate a plain-English description into working software.

Dario Amodei calls the current phase of AI progress “The Exponential.” Until I used AI to prompt an app into existence, I don’t think I fully understood what he meant. Having now immersed myself in AI-assisted coding for the better part of a month, I have a better appreciation for how dramatically things are about to change.

The purpose of technology has always been to improve efficiency and enhance productivity. Most new technologies do this linearly, automating steps that would otherwise have to be performed manually or short-circuiting sequences that were previously unavoidable.

Frontier AI doesn’t eliminate steps; it democratizes capabilities. It allows those who once relied on the skills of others to do things they were not previously capable of doing themselves. And by doing so, it unleashes exponential opportunity.

What does a world with exponential capabilities look like? Personally speaking, it will free me up to do things I never thought I could. I have, for instance, always felt that the legal software we use was not designed with my needs in mind and lacks features that I need. With my newfound coding capabilities, I can simply program those frustrations away, prompting little snippets of custom code into existence to address the deficiencies in my current set-up.

What is good for the goose will likely be good for the gander. Software companies that once relied on lawyers to draft privacy policies and terms of service for their applications will likely get them drafted by AI. As much as my fellow lawyers may not like to hear it, AI is already more than capable of producing documents for this purpose. I should know. I allowed AI to draft the terms of use of the apps that I’ve launched on the App Store.

As frontier AI improves, we will see similar exponentials unlock in various other sectors. Traditional capacity constraints that forced costly interdependencies will melt away, freeing entrepreneurs to build new offerings and deliver new forms of service.

While this will affect traditional professions, it will also enable new ways of working, and policymakers around the world will need to balance the need to protect those disrupted by this technology with the opportunities it opens up for a new ‘exponentially capable’ workforce.

As a country with a young and adaptable workforce, India should lean into this opportunity rather than attempt to preserve traditional professions that, in their current form, are sure to be disrupted.

So how should we prepare ourselves for what’s coming?

In the first place, I believe we must be willing to redesign the systems that have served us well so far. What might have worked in the past is unlikely to be necessary in a world where skills can be invoked with a prompt.

Take, for example, the traditional hierarchies of software deployment—developers, system integrators, hyperscalers—that have underpinned large-scale software services over the past few decades. In a world of exponential capabilities, the boundaries between different categories of service providers are likely to blur.

Of all countries, India is uniquely positioned to adapt to this new reality. After all, this is precisely what we did when we took the digital public infrastructure (DPI) approach. Instead of leveraging the vertically integrated software stack that was at the time widely believed to be the only way to achieve population-scale deployment, we built reusable, interoperable building blocks that dramatically reduced deployment costs. We need to apply that same iconoclastic approach to shape our AI future.

Cutting-edge AI does not just improve efficiency; it expands human capacity. By lowering entry barriers across disciplines, it gives individuals access to skills that were once scarce and expensive.

The exponential is not about machines becoming more intelligent as much as it is about people becoming more capable. And if we play our cards right, the exponential will not merely change industries. It will change who gets to build them.

The author is a partner at Trilegal and the author of ‘The Third Way: India’s Revolutionary Approach to Data Governance’. His X handle is @matthan.