Nathaniel Whittemore

And importantly, their streaming model is the best at catching all the stuff that breaks on other voice agents, things like phone numbers, emails, names, and medical terms.

It's the leading agentic systems platform that is unified, agile, and enterprise-proven, allowing you to accelerate growth, reduce operational friction, and deliver real enterprise impact with AI.

OutSystems.

Welcome back to the AI Daily Brief.

Yesterday, we had two dueling events, both focused on enterprise AI.

One was from OpenAI and one was from Microsoft, and they each provided in their own way some indications of where enterprise AI is currently and where it's headed.

Now, the context for this, of course, is the broader shift we've been discussing on this show of moving from the subsidy era of AI to the scarcity era of AI or the token shortage era of AI.

The basic idea is that as we move from assisted to agentic workloads, the sheer quantity of the AI tokens we use goes up, and we're now running into the limits of what the available compute and physical infrastructure can produce, meaning that business models are realigning, costs are going up, and everyone's scrambling to figure out how to adapt to all of that.

In the meantime, though, part of what makes this challenging is that it's not at all clear to most organizations how to best use this new set of tools.

In other words, the question of enterprise AI adoption is not just a question of costs, but also one of tool and use case fluency.

And increasingly, enterprise users are living inside the power tools like Cloud Code and Cowork and OpenAI's Codex.

Interest in Codex has been surging for a while, with Google searches for Codex actually spiking past Claude Code for the first time in May.

The information wrote about how the, quote, vibe shift on Codex has been palpable.

And OpenAI's event yesterday centered on a set of new updates for Codex that are all about it moving out of the strict realm of the developer into the broader world of knowledge work.

Now, alongside the event, OpenAI released a report called the Next Era of Knowledge Work.

And the TLDR on the thing was not only that Codex was growing, hitting 5 million weekly active users, but that the biggest source of its growth was not developers, but non-technical knowledge workers, who are now adopting Codex at a three times faster pace than developers are.

And one of the things that's interesting about the report is that it's not just a bunch of reported stats, but actually shows quite a bit of the design philosophy and the first principles understanding that's going into how OpenAI is thinking about Codex.

One of the central themes is what OpenAI calls a strange abundance.

Modern workers, they write, can produce documents, messages, dashboards, models, and presentations faster than ever, yet they spend a remarkable share of their time looking for context, reconciling conflicting versions, waiting for responses, and moving information across systems.

They point to a McKinsey study that found that the average knowledge worker right now spends more than a quarter of their workweek managing email and almost a fifth of it looking for internal information or trying to find people who can help within their company around some specific task.