What the Top AI Users Are Doing Differently

**Nathaniel Whittemore** (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 head first, 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.
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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 open-claw 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-55 on internal benchmarks. Now, obviously, the frontier has moved forward substantially with the release of GPT-56 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-56 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.