What the Top AI Users Are Doing Differently

The AI Daily Brief: Artificial Intelligence News and Analysis

This episode explores the growing divide between average AI users and top-tier AI adopters, driven by the rise of agentic workflows. It highlights how

Key takeaways

• The gap between top AI users and average users has widened dramatically—from 2.6x to 8.3x in just six months—due to agentic workflows.
• Agentic use cases enable deeper system integration, maintenance, and coordination, shifting work from writing and knowledge retrieval to automation, classification, and application building.

Main topics

• The growing gap between average and advanced AI users
• Agentic workflows and system maintenance

Notable quotes

"The most advanced users of AI were using eight times as much AI as their average counterparts."

Conclusion

The shift toward agentic systems marks a pivotal moment in AI adoption—where top users are redefining productivity

Transcript preview

Speaker 1 (0:00) There's always been a gap between an average AI user and the most advanced AI users, but my goodness, has that gap grown. In recently released research, OpenAI showed that the gap between the most advanced users and the average AI user had grown from 2.6x back in January to 8.3x by the end of June. In other words, the most advanced users of AI were using eight times as much AI as were their average counterparts. The reason, of course, is agents. At the beginning of the year, agentic use cases became viable and significantly upgraded the difficulty, complexity, and importance of the work that AI could take on. The top users have jumped in headfirst, figuring out how to significantly increase the value they get from their AI usage. The average users, on the other hand, just haven't. But as the power users use agents to take on increasingly valuable work, that gap is just poised to grow. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Blitzy, Harbor, and HyperAgent. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe on Apple Podcasts. And to learn more about sponsoring the show, send us a note at sponsors at ai-dailybrief.ai. You can also find information on the ai-dailybrief.ai site. While you're there, you can also find a link to our free webinar and hands-on lab, Agentic Loops for Knowledge Workers. That is happening on Wednesday. And even if you can't make it, if you register, we will send you the recording after. And of course, if you are looking for a little bit more hands-on support, our next executive catch-up and executive agent leadership program is starting in a couple of weeks. And you can find a link to that program from the top of ai.dailybrief.ai. According to roadmap documents viewed by The Information, Meta is putting the finishing touches on their consumer agent ahead of release in the coming weeks. Now, this is something we've been hearing about for a while, but we're getting more details as the product becomes imminent. Internally, the product is known as Hatch and sounds like it could be sort of in the Grokbot family of delivering a more streamlined version of an OpenClaw-style agent experience. The company is reportedly looking at using Hatch as part of a new AI agent subscription, which could justify a $200 a month price tag for high usage accounts. Meta also plans to launch a new platform on WhatsApp to allow better integration for third-party agents. The platform will reportedly allow multiple agents to coordinate with each other using WhatsApp messages, again, which is a mirroring some of the functionality, like I said, of Grokbot. For what it's worth, this doesn't strike me at all as Meta cribbing off of Grokbot. I think these are just interaction patterns that we're likely to see more of. The rollout could begin as soon as this week, as a preview to a smaller group of customers. Finally, in Meta model news, a larger model known as Watermelon is being prepared for an October launch. Back in July, Meta's AI CEO Alexander Wang told staff that Watermelon had already caught up with GPT-5.5 on internal benchmarks. Now, obviously, the frontier has moved forward substantially with the release of GPT-5.6. and will likely move again by the time October arrives. So we'll see whether Watermelon can actually keep pace or continues to fall in the column of Meta getting closer to the frontier without actually reaching it. Speaking of Grokbot, one of the barriers for a lot of you guys testing it has been its extreme premium pricing. In fact, it wasn't just high pricing, it was kind of confusing pricing. Initially, users weren't sure if they had to subscribe to both Cursor Ultra and Super Grok Heavy, which would be a total of $500 a month to access the service. But then many, myself included, were able to get it just through Super Grok, which is itself not a cheap subscription. But it was very clear that this was an intentionally rate-limiting launch to make sure that things didn't go down with the hopeful anticipation. that prices would be reduced later. As of this week, Grokbot is included in the $60 a month Cursor Pro subscription, as well as the $100 a month Super Grok subscription. Speaking of dropping prices, OpenAI is also dropping prices for GPT-5.6 Sol. Accessing Sol over the API will now cost $4 per million input tokens and $20 per million output tokens, down from $5 and $30 respectively. Costs for Luna and Terra were already cut late last month. Many are speculating that this is OpenAI trying to put pressure on Anthropic ahead of their IPO. My guess is that for whatever ancillary benefit that might have, OpenAI is more likely to just be realizing that they've got a new set of challenges based on what we talk about every week here on this show, that especially business customers are not just going to use the most expensive state-of-the-art model for everything anymore and have to think in more sophisticated ways about their complete model stack. To the extent that OpenAI has the compute to deliver their frontier models cheaper, it seems like they've decided it makes sense to do so. Now, following up on news from yesterday, Business Insider reported that Hugging Face was courting an acquisition at a $13 billion valuation. And according to sources speaking with the information, part of what might justify their high asking price is that the company is now generating more than $150 million in annualized revenue, which is up 50 % from two months ago. Now, that number may seem low relative to, for example, the coding agent startups, but Hugging Face is a company that has specifically not been focused on generating revenue. 97 % of users access the platform entirely for free, including downloading the latest model weights. The primary revenue drivers for Hugging Face are premium and enterprise-grade accounts, serving inference in partnerships with hyperscale clouds. Essentially, up until now, the profit-seeking segments of the platform have existed to subsidize the free hosting and distribution of open models. In June, CEO Clem DeLange said that the number of premium accounts had doubled in the first half of the year, and based on that, the platform was approaching profitability. For acquirers, this is very likely not a strict revenue multiple type of conversation. Subbing up the logic, Jess Fields writes, Hugging Face should be worth as much as Cursor is, way more than $13 billion, maybe three to four times that. Considering that Hugging Face is the backbone of the open weights challenging frontier gatekeeping, it occupies a uniquely powerful position in the entire economy. Now, one of the companies that people are speculating on might be an interesting fit for Hugging Face is, of course, NVIDIA. if for no other reason than they seem to be in the conversation for every acquisition right now. In fact, with a flurry of reporting around NVIDIA's dealmaking in recent days, some are wondering just what Jensen is building. Over the past week, we've heard that NVIDIA signed a deal to license technology and acquire talent from Poolside, buy a stake in data labeling company Mercore, and potentially invest in Perplexity at a potentially perplexing $30 billion valuation. That's to say nothing of other equity investments in neoclouds, land and power deals, and data center backstops. Some have started to conceptualize NVIDIA as the central bank of compute, standing behind the AI economy, as well as setting the price of the key resource. Martin Peers of The Information compared Jensen's approach to that of John Malone, who built up