15 Business Model Questions for OpenAI and Anthropic
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Today on the AI Daily Brief, some monster revenue numbers bring up a slew of questions on the business model for OpenAI and Anthropic, before that in the headlines, why Claude's new skills feature is potentially a really big deal. 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. Firstly, thank you to today's sponsors, Gemini, Notion, Blitzy, Super Intelligent, and Robots and Pencils. 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 find out about sponsorship opportunities, or pretty much anything else, speaking, job opportunities, etc., visit the show at ai-dailybrief.ai.
Welcome back to another AI Daily Brief Headlines Edition, all the daily AI news you need in around five minutes, and we have a jam-packed edition today. We're kicking off today with a story that I think I will probably try to do a more operator's cut style episode as people dig in and figure out how to use these tools in the coming weeks. But for now, it's rolled out a new feature called Skills, which provides agents with instructions, scripts, and resources to help them with specific tasks. Users can fill a folder with these skills that might cover things like brand guidelines or instructions on carrying out a task in Excel. The feature also allows users to provide executable code for situations where traditional programming is more reliable.
Cloud agents can then draw from these skills when they become relevant to the task at hand. Essentially, skills are little barrels or buckets of context that Claude can draw on when it makes sense. They're in a standard format that can be used across Claude apps, Claude code and the API, meaning you only have to build them once. Said anthropic staffer Mahesh Murag, skills are based on our belief and vision that as model intelligence continues to improve, we'll continue moving towards general purpose agents that often have access to their own file system and computing environment. The agent is initially made aware only of the names and descriptions of each available skill and can choose to load more information about a particular skill when relevant to the task at hand.
Now, part of the benefit here is that this makes the method token efficient. Cloud agents can initially use very basic tools to figure out which skills they need for a given task and only spend significant tokens once it knows which ones to load. They also function sort of like custom agentic scaffolding, but in a much more modular and user-friendly package. A user doesn't need to know any programming language to create a custom skill that's fit for their purpose, which of course dramatically lowers the barrier to entry for advanced agent design. You can also prompt Claude to design its own skills with the example that they give, saying, help me create an image editor skill. Claude can also help them refine human design skills or monitor common failure points and then build skills to mitigate them.
Basically, Claude can be leveraged to collaborate on its own agentic design. skills are also stackable. So by way of example, Anthropic discussed an agentic workflow for building a quarterly investor deck where the agent would be able to tap into the company's brand guideline skill, a financial reporting skill, and a presentation formatting skill, coordinating all three without the need for manual intervention. People very quickly picked up that this is sneakily a big deal.
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