In this conversation, Robert Ta and Jonathan dissect the recent enterprise‑focused joint ventures launched by Anthropic and OpenAI. Anthropic’s venture is valued at roughly $1.5 billion, with $300 million each from Anthropic, Blackstone, and Hellman‑Friedman, $150 million from Goldman Sachs, and additional backing from General Atlantic, Sequoia Capital and others. OpenAI’s development company is raising $4 billion from 19 investors—including TPG, Brookfield, and Bain Capital—at a $10 billion valuation, with no overlap in investors between the two deals, indicating two distinct financial ecosystems. Both labs are adopting a Palantir‑style model that embeds forward‑deployed engineers inside client organizations to solve the “last‑mile” problem of turning powerful models into concrete enterprise ROI. Robert cites Anthropic CFO Krishna Rao’s comment that enterprise demand for Claude outpaces any single delivery model and that system‑integrator partnerships are essential. The discussion references Fortune’s thesis that for every dollar spent on software, companies spend six on services, highlighting the lucrative consulting‑services market the labs are targeting. Jonathan expands on how forward‑deployed engineers address friction in model integration, the risk of delivering ROI, and whether smaller players can find a role alongside the giants. Robert also notes OpenAI’s strategic shift away from consumer products like Sora to focus resources on enterprise knowledge‑work automation. The overall narrative frames enterprise AI deals as critical to the financial futures of these companies and as a catalyst for a new service‑oriented ecosystem.
Chapters
Anthropic and OpenAI are both launching joint ventures for enterprise AI services. Here's what happened, what they got right, and what nobody's talking about. So Anthropic's joint venture is valued at about $1.5 billion, and the breakdown in capital is Anthropic, Blackstone, Hellman Friedman each contributing about $300 million, Goldman Sachs contributing about $150 million, with additional backing from General Atlantic, Sequoia Capital, and more. OpenAI's venture, the development company, is raising $4 billion from 19 investors against a $10 billion valuation, including TPG, Brookfield, and Bain Capital. There's zero investor overlap between the two ventures, indicating two distinct financial ecosystems forming around services. And both labs are adopting the Palantir model for forward deployed engineers, embedding very skilled engineers who understand product. And engineering directly inside client organizations to accelerate enterprise adoption. From Anthropic's own CFO, Krishna Rao, exact quote, "Enterprise demand for Claude is significantly outpacing any single delivery model. Our partnerships with the world's leading systems integrators are central to how Claude reaches large enterprises." And Fortune reports the consulting industry disruption thesis: for every dollar companies are spending on software, they spend 6 on services. That's the market both labs are targeting strategically. Jonathan, as a 12-time founder and our CTO, what are some of your thoughts on this play from both OpenAI and Anthropic?
Yeah, it's an interesting story, right? Anthropic and OpenAI both had announced various ways of, you know, having forward deployed engineers in these larger enterprises. And this is kind of like maybe the longer tail of the companies that they couldn't address through the first round of strategies. And I think OpenAI's first strategy was partnering with big consulting firms like McKinsey and PwC and those, the likes of those. So this is kind of like the longer tail effort of that. A lot of interesting things. I mean, one is how does the value of AI get realized in enterprise? The need for a forward deployed engineer shows that some of the frictions of, say, applying a model in the actual context of work and getting return out of it. And what Anthropic's been doing with these forward deployed engineers is going in, understanding the domain, creating software services that are specific to like how the forward deployed engineer is configuring the model to be used and trained. And I think that sort of like last mile of delivery is an opportunity to like take these powerful models and apply them to like specific business problem with ROI. It's interesting. This is the form factor that it's coming in. I think from one standpoint, you could say, well, they have to do this because it's not a proven thing yet. And this is actually like a business risk to actually get that last mile of value and get the applications working in enterprise. And we see a lot of stories about enterprise dysfunction, the lack of ROI. On that front line. And I think the other thing for us, like, you know, our company is like, what role do we play in this world if we're trying to work with enterprise customers? And like, do we need to like engage with these partnerships? Do we need to, you know, work with these companies? Or is there going to be room for smaller players to engage in, you know, on top of OpenAI and Anthropic and deliver for deployed engineering services?
Yeah, that makes a lot of sense. I like what you said about the last mile, which is they're racing for enterprise adoption as a story circling around their IPOs impending, both Anthropic and OpenAI. And they both, both raised a shitload of money to go win in enterprise. And it also intersects with OpenAI's move of dropping Sora and the consumer angle there to just focus their resources to capture enterprise market. But all the strategic moves that we could see from the outside from these labs show that they see the money is in capturing value in enterprise for knowledge work. It makes a lot of sense. They're building intelligence layers. They want those things last mile sort of installed in enterprises so that they could accelerate the value these companies are getting in automating a lot of knowledge work.
