15 Business Model Questions for OpenAI and Anthropic

0:00This podcast is supported by Google. Hey folks, Stephen Johnson here, co-founder of Notebook LM. As an author, I've always been obsessed with how software could help organize ideas and make connections. So we built Notebook LM as an AI-first tool for anyone trying to make sense of complex information. Upload your documents and Notebook LM instantly becomes your personal expert, uncovering insights and helping you brainstorm. Try it at notebooklm.google.com. 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.

0:43The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

0:52All right, friends, quick announcements before we dive in. Firstly, thank you to today's sponsors, Gemini, Notion, Blitzy, Superintelligent, 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 aidailybrief.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 Operators 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.

1:40Users 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 Marag, 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.

2:25The 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. Clawed 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.

3:02You 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 then 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 guidelines skill, a financial reporting skill, and a presentation formatting skill, coordinating all three without the need for manual intervention.

3:36People very quickly picked up that this is sneakily a big deal. Daniel Meisler wrote, Something I want to stress today, MCP changed everything, but not because of a model improvement. And today, skills change everything, but not because of a model improvement. AI systems are the thing to watch, not just the intelligence of the models. People are useful in jobs because they connect dots and can do many different things. That's what Anthropic has been doing here, building a unified system that connects dots. Simon Willison discussed in his blog how skills are awesome and maybe a bigger deal even than MCP, which is of course in bold words.

4:12First, he described what skills are. He said that conceptually they're extremely simple. They're a markdown file telling a model how to do something, optionally accompanied by extra documents and pre-written scripts that the model can use to help it. However, he writes, there's one extra detail that makes this a feature, not just a bunch of files on disk. At the start of a session, Claude's various harnesses can scan all available skill files and read a short explanation for each one. This is very token efficient. Each skill only takes up a few dozen extra tokens, with the full details only loaded in should the user request a task that the skill can help solve.

4:44He discussed how he would build a data journalism agent using the feature. The skills that he would build were things like how to access and parse census data, how to load data from SQL and DuckDB with associated Python code provided, how to publish data online, and how to figure out an interesting story to tell based on the data. Simon concluded, The core simplicity of the skills design is why I'm so excited about it. Skills are marked down with a tiny bit of YAML metadata and some optional scripts in whatever you can make executable in the environment. They feel a lot closer to the spirit of LLMs, throw in some text and let the model figure it out.

5:18They outsource the hard parts to the LLM harness and the associated computer environment. Given everything we have learned about LLM's ability to run tools over the last couple of years, I think that's a very sensible strategy. Put differently, I think skills are in some ways a different user experience pattern for getting at agent creation. That's really what this is about. On the one hand, you've got the NNN style agent workflow builder, but this is basically where you articulate component parts and then can use natural language to help the LLM itself figure out which of those parts it needs to put together.

5:51Again, in Simon's example, he's got a skill for parsing census data, a skill for loading data, a skill for publishing data online, and a skill for figuring out an interesting story. Instead of having to put them together in a step-by-step workflow schematic, he can just make sure that each individual piece has all of the context it needs, and then the LLM can figure out how to put it together, which strikes me if it works as a much more intuitive way to organize this than some of those other interfaces. There's going to be a ton of examples, I think, coming up. And like I said, I'm planning on maybe an Operator's Cut style episode where we get into some ways to actually use Claude Skills.

6:26But for now, we've got a lot to cover. So let's move on to Microsoft, who wants to make every PC an AI PC with a big new update to Windows 11. Now, on the surface, this is an update about bringing Copilot to all users and making it more central to the Windows experience. Users can now summon the AI assistant by saying, hey, Copilot. They're also rolling out Copilot Vision, which allows the AI model to see what's happening on the desktop and use it as input. In addition, agentic features will be introduced as early previews. Those agentic features will allow Copilot to tap into data from emails, calendars, and the office suite, as well as taking actions in the file system itself.

7:00The biggest difference from previous AI releases is that none of these features will be restricted to co-pilot plus hardware, they will just be a default part of the Windows 11 experience for all users. Executive VP and Consumer Chief Marketing Officer Yousef Mehdi explained, We think we're on the cusp of the next evolution, where AI happens not just in a chatbot and gets naturally integrated into the hundreds of millions of experiences that people use every day. The vision that we have is, let's rewrite the entire operating system around AI and build essentially what becomes truly the AI PC. The rewrite is built around two main features, agentics in voice.

7:33Medi said, you should be able to talk to your PC, have it understand you, and then be able to have magic happen from that. With your permission, we want people to be able to share with their AI on Windows what they're doing and what they're seeing. The PC should be able to act on your behalf. He added, in our minds, voice will now become the third input mechanism to use with your PC. It doesn't replace the keyboard and mouse necessarily, but it's an added thing and it will be pretty profound and a new way to do it. They also have a new feature coming called Copilot Actions, which is sort of similar to OpenAI's Operator or Google's new Gemini Enterprise.

8:03The feature spins up a new window where the users can give directions and watch the agent complete tasks using local files. They can either monitor the agent and take over at any time, or click away to a different window and let the agent run in the background. Now, as I've said before, despite what seem like some stumbles and missteps, Microsoft has an incredible distribution network and serious benefits when it comes to consumer installs, and this is a great example of how owning the entire end-to-end experience could be a game-changer when it comes to how much value you can unlock for a particular user.

8:33Moving over to IP land, Spotify has reached a deal with the major music labels on how AI will intersect with the music industry. Spotify will collaborate with Sony, Universal, Warner, Merlin, and Believe to, quote, develop responsible AI products that empower the artists and songwriters they represent and connect them with the fans who support them. In a press release, Spotify wrote, Some voices in the tech industry believe copyright should be abolished. We don't. Musicians' rights matter. Copyright is essential. If the music industry doesn't lead in this moment, AI-powered innovation will happen elsewhere without rights, consent, or compensation.

9:05Now, the announcement didn't discuss any specific products, but it did reinforce that the introduction of AI features would fundamentally be the choice of rights holders and artists. They're also aiming to build AI products that create wholly new revenue streams and want to ensure that rights holders are properly compensated and credited appropriately. A lot of the coverage was extremely skeptical. Spotify has recently been criticized for allowing low-effort AI tracks to proliferate, leading to a purge of 75 million AI-generated tracks in September, but others are willing to give the benefit of the doubt.

9:33Ed Newton-Rex, the CEO of copyright advocacy group Fairly Trained, posted, In my opinion, it's a good thing that Spotify is working on AI music tools with the major labels. Lots of the AI industry is exploitative. AI built on people's work without permission served up to users who get no say in the matter. This sounds like it will be different. AI features built fairly with artist permission, presented to fans as a voluntary add-on, rather than an inescapable funnel of AI slop. To be clear, Spotify's general stance on AI music is not good. They seem happy to allow AI slop on the platform without labeling it, even featuring it in recommended playlists.

10:04This needs to change. But credit where it's due. Licensing music for training instead of taking it without permission is very welcome. The devil will be in the details, but in tone at least, this is a positive development. Now, that might not sound all that positive to you, but given how absolutely contentious the relationship is between the AI and anti-AI crowd, that is not just a fig leaf, that's a fig tree. Whether Oracle can actually pull off that line remains to be seen, but I think that they are in a good position to give it a shot. A couple quick product updates. General Purpose Agent Manus has been updated for version 1.5.

10:36The team wrote faster, better quality results, unlimited context, build full-stack web apps with real AI features, backends, user logins, custom domains, and analytics. Run your biz, start your side hustle, or just have fun. If you can dream it, Manus can build it. Manus claimed that tasks are now four times faster on average, and the performance boost should allow tasks that once failed to be completed successfully. Manus' internal benchmark showed a 15 % improvement in task quality and a 6 % increase in user satisfaction. The big new feature is the ability to build web apps end-to-end without leaving Manus, making the agent more useful as a vibe coding platform.

11:10Kind of seems like ultimately everything, even the general purpose agents, are a vibe coding platform in the end. Another small but potentially powerful feature announcement, agent orchestration startup Lindy has announced an AI chief marketing officer for your company. CEO Flo Crivello wrote, announcing Lindy AI CMO, a team of agents running entire marketing workflows end-to-end, handling market research, analysis, and creative at scale, so you can start thousands of ad experiments in minutes. As part of this, we're launching new integrations with Sora 2, VO 3.1, Nano Banana, and GPT Image Gen.

11:41Over the last few years, agents have grown tremendously in their scope and autonomy, going from handling simple tasks to assuming entire roles. This will be the first time that we see them take a chunk out of an entire org. I'm considering trying this out as CMO of AIDB, given that, as I've mentioned, I'm hiring for some growth roles. If that's an experiment that you would be interested in following along with, let me know and we'll see what can happen. Lastly, I am continuing to do our ROI corner, ROI shoutouts. ROI is going to be a major theme for next year. And so when we see companies reporting actual ROI from AI, you are going to get it here.

12:13The latest comes from Alibaba, who have announced that they've reached breakeven on AI in their e-commerce business. In February of this year, the Chinese tech giant announced they would spend$53 billion on AI over the next three years. They've since rolled out a string of features, including personalized AI search and virtual clothing try-ons. Now, a company official has announced that preliminary testing of their AI features has shown consistent results, including a 12 % increase in return on advertising spend. VP Kaifu Zhang said it's very rare to see double-digit changes. Zhang predicted that AI would have a quote, very significant positive impact on sales during this year's singles day shopping period, which centers around November 11th.

12:51Meanwhile, I would anticipate that in the US, we're going to see a bit of an AI-focused Black Friday as well, but it's not even Halloween yet. We still have a little time before that. And so with that, we will wrap today's headlines. Next up, the main episode.

13:31America, clients gain local expertise and global scale. As AI evolves, they ensure you keep peace with change. And that means faster results, measurable outcomes, and a partnership built to last. The right partner makes progress inevitable. Partner with Robots and Pencils at robotsandpencils.com slash AI Daily Brief. Chatbots are great, but they can only take you so far. I've recently been testing Notion's new AI agents, and they are a very different type of experience. These are agents that actually complete entire workflows for you in your style. And best of all, they work in a channel that you already know and love because they are purpose-built Notion super users.

14:10Notion's new AI agents completely expands the range of what Notion can do. It can now build documents from your entire company's knowledge base, organize scattered information into organized reports, basically do tasks that used to take days, and get them complete in minutes. These agents don't just help with work, they finish it. Getting started with building on Notion is easier than ever. Notion agents are now your very own superuser to help you onboard in minutes. Your AI teammates are ready to work. Try Notion AI for free at the link in our show notes. What if AI wasn't just a buzzword, but a business imperative?

14:42On You Can With AI, we take you inside the boardrooms and strategy sessions of the world's most forward-thinking enterprises. Hosted by me, Nathaniel Whittemore, and powered by KPMG, this seven-part series delivers real-world insights from leaders who are scaling AI with purpose. From aligning culture and leadership to building trust, data readiness, and deploying AI agents. Whether you're a C-suite executive, strategist, or innovator, this podcast is your front row seat to the future of enterprise AI. So go check it out at www.kpmg.us slash AI podcasts, or search You Can With AI on Spotify, Apple Podcasts, or wherever you get your podcasts.

15:21Today's episode is brought to you by Superintelligent. Now, for those of you who don't know who are new here, maybe Superintelligent is actually my company. We started it because every single company we talk to, all the enterprises out there are trying to figure out what AI can do for them. But most of the advice is super generic, not specific to your company. So what we do is we map your AI and agent opportunities by deploying voice agents to interview your teams about how work works now and how your people would like it to work in the future. The result is an AI action map with high potential ROI use cases and specific change management needs, basically everything you need to go actually deliver AI value.

16:00Go to bsuper.ai to learn more. Welcome back to the AI Daily Brief. At the core of all of the conversations around whether or not we are in an AI bubble is the question of the growth potential of the core model provider companies. Basically, we have a situation where there's this set of deals that are perceived as increasingly circular, that are all based on getting more compute and more electricity to power that compute, more data centers to deliver that compute, etc. But all of that is based on the assumption that that compute will turn into AI products that have enough demand to generate enough revenue to make all of that infrastructure build out make sense.

16:40So for that reason, people are paying extremely close attention to indications of how these businesses are growing? And the short answer seems to be like gangbusters. So we got two interesting reports this week, both of which dealt to some extent with revenue from these companies. The first was about Anthropic, and it showed just what an absolute tear this company has been on this year. Now, Anthropic started the year at around$1 billion in annualized revenue. That's where they were in the December-January timeframe. Over the summer, they nudged up to$5 billion in annualized revenue. And according to Reuters, they are now running at a$7 billion revenue run rate and are on track to meet a goal of$9 billion by the end of the year.

17:22900x growth from a billion dollar base in a single year is absolutely insane. And while they don't think that they're going to continue that unbelievably breakneck pace into 2026, they still do think that they can reach between$20 billion and$26 billion in annualized revenue by the end of next year. Okay, so that's the Anthropic story. OpenAI, meanwhile, began the year at around$5.5 billion and have now grown apparently to around$13 billion. Now, in any normal world,$0 to$13 billion in three years after the release of their core product would be seen as absolutely insane growth, and it is. The challenge is that they are projecting$100 billion in annual revenue by 2028.

18:05The Financial Times wrote a piece about the big obligations that OpenAI is putting on its back called OpenAI Makes Five-Year Business Plan to Meet$1 Trillion Spending Pledges. This, of course, they're referring to all these deals with NVIDIA, Oracle, etc. Now, it's very clear that OpenAI isn't planning on being able to finance all of this just with revenue. However, as I said, they are projecting$100 billion in three years, meaning they are going to need to see a big uptick in revenue from where they are. And alongside the Financial Times article, we also got some reported information around the state of the business.

18:37$13 billion in revenue includes about 70 % of that from consumer subscriptions and around 30 % of that from the API. Of their 800 million users, about 5 % are paying monthly or$40 million. They're also at a$20 billion burn rate. So let's talk about some of the interesting questions that I think this brings up that are more slanted towards the strategy of these companies going forward. So one question is, does the radical breakout success of Anthropic push OpenAI to be more aggressive about enterprise? In that Reuters piece, we also learned that 80 % of Anthropic's revenue comes from the enterprise.

19:10They have more than 300 ,000 business and enterprise customers. They've recently announced big deals like the one with Deloitte, where they have hundreds of thousands of users coming from a single company. And given their 9x growth, the fact that they have gone from 1 20th or less of OpenAI's revenue to more than half of OpenAI's revenue in just 10 months has got to be pushing the question of whether there should be more emphasis on the enterprise from OpenAI. Now, of course, it's not like OpenAI has no enterprise focus. The company has even recently added a forward deployed engineer team that will go in and actually help companies build out solutions if apparently they are a$10 million or more customer.

19:47And interestingly, at DevDay, Altman and Brockman did speak a little bit about enterprise. Brockman talked about how there were a lot of really boring enterprise problems that were some of the juiciest things to solve. And Altman talked about how they didn't just want FTEs to be bungling around, but now they feel like they really have a good idea of how to help enterprises, and so they want to scale that. All of that suggests to me that we might see at least a bit more enterprise focus heading into 2026. Now, of course, one of the interesting questions, which has a big stake in this strategy as well, is how much of this enterprise success is strictly anchored in Anthropik's coding prowess.

20:19For most of this year, really up until GPT-5, Anthropic were the preferred coding models by far and away, with Gemini models a distant second, and OpenAI models not really in the conversation. We've covered a lot about how that shifted, and it was very clear that a huge goal of GPT-5, if not the primary goal of GPT-5, was to redress this balance. And I wonder to what extent OpenAI sees coding as the Trojan horse for absolutely everything in enterprise and as the thing they need to focus on, even if their broader goal is more general enterprise revenue as well. Still, I don't think it's a foregone conclusion that OpenAI's only play is to double down on enterprise.

20:54The numbers that Anthropic is putting up certainly suggest how valuable that segment is, but at the same time, OpenAI really does have a unique position vis-a-vis consumer. For a huge number of people, AI and ChatGPT are completely inextricable from one another. In fact, ChatGPT is the term more than AI that they know. Aside from a few dips and blips, they've been the number one app for a huge part of their life since ChatGPT was launched, And every week that goes on, ChatGPT gets more and more deeply woven into the consumer experience. Now, one of the questions for a lot of people is how much more there is to be gained from those 800 million users.

21:28Max Sparrow, for example, tweeted, is it just me or is 40 million paying ChatGPT users kind of low? Spotify, for example, has 276 million paid subscribers. Just kind of surprised that there are 760 million people who don't feel like they derive an additional$20 of value from a more capable model. This, to me, I think is a really important question. It certainly feels like there is a lot more to be gained from these users. And my guess is that OpenAI is betting that the more valuable that these models get over time, the higher the percentage of users they'll be able to unlock and convert to a higher tier.

22:00But it also seems like they're not taking that for granted. And so another question that comes up is, does this make ads inevitable? My read, having watched all of these discussions, is that OpenAI really doesn't want to have to do ads, at least not in the traditional way. I think that they genuinely don't really want to be strictly speaking in the attention business in the way that Meta or TikTok or Instagram are. But I also think that they feel like it is to some extent inevitable and a huge source of revenue. And certainly if you're trying to go from 13 billion where we are at the end of 2025 to 100 billion by the end of 2028, it seems like there are going to have to be new revenue streams unlocked that aren't just converting more paid subscribers.

22:41Certainly, I think that that brings up the question of how much revenue is possible from ads and what they need it to do as part of the overall mix if they were to go into this area. Now, one thing that hasn't been discussed as much is that it is possible that OpenAI finds some slight variation on the traditional ad unit experience that better befits the user experience patterns of interacting with ChatGPT and that make it less annoying and more palatable for users than, for example, big chunky display ads. Indeed, it feels like that's kind of what they're thinking about with their checkout with ChatGPT business and in general, taking a cut of referrals from the part of the ChatGPT experience that's all about discovery.