How Headless Agents Will Change Work
episode
The AI Daily Brief: Artificial Intelligence News and Analysis
30 min
2 speakers
3 chapters
transcribed 4 months ago
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Transcript generated automatically by AI and may contain errors.
What major shifts are happening in the software industry towards headless agents?
Today on the AI Daily Brief, how headless agents will change software and work. Before that in the headlines, the compute competition heats up.
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, Zencoder, and Granola. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe on Apple Podcasts. If you're interested in learning more about the show, head on over to ai-dailybrief.ai. You can find out about our newsletter, learn more about sponsorship opportunities, or see really anything else that's going on in the ecosystem. OpenAI has accelerated their ambitious roadmap for scaling inference. In an X post, they said they plan to deploy 30 gigawatts of compute by 2030. Now, during the Stargate announcement at the beginning of 2025, OpenAI announced their massive 10 gigawatt target by the end of the decade.
Meaning, for those of you who are sitting there doing the math, they are tripling their medium-term compute goals. To give a sense of the scale, Epic AI estimated that total global AI data center capacity reached 30 gigawatts at the end of last year. That figure includes both the power use for chips and ancillary systems like cooling and networking, so it's not entirely clear this is an apples-to-apples comparison. 30 gigawatts also happens to be roughly peak power demand for the entirety of New York State. OpenAI, meanwhile, says that they are already well on their way. They said that they tripled their compute supply last year, going from 0.6 gigawatts to around 1.9 gigawatts. OpenAI also said that they've identified, whatever that means, more than 8 gigawatts already.
Now for those of you who feel like, sure I know why this is important, but it's not really the part of AI that impacts me, this year has shown exactly why it actually does affect all of us. The rise of agentic work this year has brought a huge inference crunch. Most observers believe that Anthropic is straining under a wave of new demand, though they've yet to discuss that issue in public. Instead, we're seeing a bunch of weird things that end up feeling like missteps that could all be attributed to just simply not having enough compute and power to serve as much of their AI as people want. Hader writes, Right now, compute is everything. Anthropic does not have enough of it, which is why Opus performance is degrading.
OpenAI felt the pressure in 2025, especially after the Ghibli wave, which pushed SAM to lock in long-term compute. Until there is a breakthrough in model architecture or chip design, this cycle will continue. Now, whether or not that's true, it is certainly the case that OpenAI is positioning themselves as the startup with ample compute. During the rollout of ChatGPT images on Tuesday, President Greg Brockman remarked, really incredible what you're now able to do with a little bit of compute. At the moment, it might be a few subtle jabs, but OpenAI pretty clearly wants customers to know that they have ample capacity to accommodate any clawed refugees out there. At the same time, Semi Analysis is calling out another crucial bottleneck in energy supply.
In a classic vague post on X, they wrote, 100 gigawatts under contract, 10 gigawatts of capacity left through 2030, pricing up double digits, competitor literally stopped taking orders, and they generated more free cash flow in 90 days than the prior 365. This market is the tightest it's been in decades and nobody's talking about it. Most believe this referred to GE Vernova, one of the few suppliers of gas turbines required for co-located power generation. GE Vernova stock was up 13.7% on Wednesday after they delivered a blowout earnings beat. They reported $17.44 in earnings per share, smashing the consensus forecast of $1.67. Below the headline, they also discussed a massive increase in their backlog, with new orders rising 71% last quarter to bring that backlog to $163 billion.
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