The capacity of artificial intelligence (AI) models is growing exponentially, but the way in which companies will adopt this technology still generates significant uncertainty. Thinking about shaping this future, labs like Anthropic and OpenAI have created companies focused on sending AI engineers directly to their customers. This initiative represents a bet that supporting companies to effectively use AI models will be the next sector worth trillions of dollars, as indicated on Tuesday, July 15, 2026.
One of these new companies has already been named: Ode with Anthropic, valued at US$1.5 billion, is an AI implementation company that the artificial intelligence laboratory Anthropic launched in May. The joint venture has the support of investors such as Blackstone, Hellman & Friedman, Goldman Sachs and others. This move mirrors a similar initiative from OpenAI, called The Deployment Company, reinforcing the growing realization among cutting-edge AI labs that winning enterprise customers goes far beyond just developing improved models.
The idea for Ode initially came from Blackstone, which identified a gap in the market when trying to apply AI in its portfolio companies, even with the help of large consultancies and small AI services boutiques. The startup Fractional AI, specialized in AI engineering, stood out in this scenario, leading to its acquisition by the joint venture shortly after the announcement of the creation of Ode. Fractional, which previously maintained an eleven-month partnership with OpenAI, ended this relationship after the purchase.
Currently, Fractional has become the foundation of Ode, functioning as a kind of “scaled boutique” of AI services, with significant ambitions from its leaders.
In an exclusive interview, Chris Taylor, CEO of Ode and co-founder of Fractional, expressed optimism about the future: “It’s pretty easy to imagine this becoming a trillion-dollar company someday if we execute well.” He also pointed out the main challenge: “The central question for the business is how to go through this phase of hyper growth without losing focus on quality.”
Ode currently employs one hundred engineers and collaborates closely with Anthropic’s applied AI team. The objective is to identify where technology can have an impact on different companies, developing personalized systems for each organization’s operations.
Anthropic’s internal team will remain focused on strategic implementations aligned with its mission, as stated by a company spokesperson. The private equity firms backing Ode will direct their own portfolio companies to the joint venture as potential clients, although Ode will not restrict the sale of its services to just these companies.
For Ode, the ideal customer is one whose CEO truly believes in the promise of artificial intelligence, according to Chris Taylor.
Taylor explained that “a lot of the work we’re doing represents the first or second priority for the CEO of the company.” He added: “It’s the most crucial product feature the company will build in the next two years, or it’s the most critical business process restructuring they have.”
Ode will adopt the “Claude-first” principle, meaning it will implement Anthropic technology, including features like Claude Tag in Slack, whenever feasible. However, the company is not restricted to Anthropic solutions and will utilize competing AI products if necessary for customer demands.
Eddie Siegel, chief technologist at Ode and one of the co-founders of Fractional, highlighted that the joint venture’s difference lies in the high quality of its implementations and the ability to develop customized solutions for business challenges.
Siegel stated, “I believe model selection matters, but it’s not where most of the effort is spent.” He compared: “It’s an ingredient in a system that needs to be engineered. It’s like choosing a programming language when building software […] I wouldn’t define a business transformation in terms of choosing Python or Java.”
Chris Taylor added that Ode’s fundamental belief is that “companies not focused on AI will be among the big winners of this moment in artificial intelligence, as long as they adopt the technology in the right way.” However, to integrate AI, which he described as “this magical, mind-blowing ingredient,” and redefine core business processes or customer experiences requires considerable support, he said.
“This requires high-caliber applied AI talent, something most companies do not have,” said Taylor.
Ode executives describe their team as elite generalist software engineers, with more than half of them being former founders. According to Siegel, they are professionals capable of “balancing a really challenging technical problem and, at the same time, taking on something from start to finish.” A Blackstone executive defined them as “adult” engineers, “special forces” rather than an army of field engineers (FDEs).
As several sources linked to the joint venture reported, the demand for these teams of field engineers (FDE) far exceeds the available supply. Ode’s objective is to continue expanding, including internationally, while maintaining its positioning as a boutique company, which involves carrying out continuous assessments to measure the commercial impact of AI implementations.
In a global scenario where top engineering talent is already scarce, maintaining and expanding a team like this represents a considerable challenge. If becoming an elite applied AI engineer requires entrepreneurial experience, systems thinking, AI skills, and enterprise product insight, the question is whether Ode will be able to train enough people to meet demand.
These difficulties are compounded by the fact that Ode will compete not only with OpenAI’s The Deployment Company, but also with consulting giants like Deloitte and Accenture, which have already established their own teams of field engineers.
Eddie Siegel, however, did not show much concern about the possible shortage of “adult” generalist engineers.
“There has never been an easier time to become an entrepreneur,” he said. He explained: “You learn a lot by trying to solve problems from start to finish, looking for product-market fit, moving the needle in a business. You learn a lot there that you don’t learn just by solving a narrow problem. That’s the skill set that fits very well with Ode.”
The question of whether there will be enough engineers with this profile remains open. However, if Ode and its investors are right, the next big race in artificial intelligence will not be about the best models, but rather who can successfully apply these models within the largest companies in the world.
