OpenAI’s chief revenue officer, Denise Dresser, sent a four-page memo to employees on Sunday about the company’s strategic direction, emphasizing the need to lock in users and grow its enterprise business.

Read OpenAI’s latest internal memo about beating the competition — including Anthropic

“The market is as competitive as I have ever seen it,” wrote Denise Dresser, OpenAI’s chief revenue officer.

The memo, which was viewed by The Verge, repeatedly underlines the importance of building a moat around its AI products, to combat how easy it is for users to switch between whichever model is topping the charts on any given day or week. Dresser, who recently took over much of former COO Brad Lightcap’s duties as he transitions to a new role focused on special projects, also emphasizes the importance of focusing on enterprise clients. It’s part of the company’s recent strategy to avoid focusing on “side quests” and go all-in on its biggest revenue drivers. CNBC earlier reported on the memo.

“Multi-product adoption makes us harder to replace,” Dresser wrote, later adding, “We should stop thinking like a company with separate product lines. We should think like a platform company with multiple entry points and one integrated enterprise offering.”

Dresser also addressed the intensifying competition between OpenAI and its longtime rival Anthropic, writing that “the market is as competitive as I have ever seen it” and that though Anthropic’s “coding focus gave them an early wedge,” “you do not want to be a single-product company in a platform war.” The memo also accuses Anthropic of inflating its stated run rate and says it was a “strategic misstep” for the company to not acquire enough compute. Both OpenAI and Anthropic reportedly plan to go public this year.

“Their story is built on fear, restriction, and the idea that a small group of elites should control AI,” Dresser wrote of Anthropic.

OpenAI has long marketed itself as “democratic AI” allowing more access to the people, often implying that Anthropic and its enterprise focus do the opposite. In February, OpenAI CEO Sam Altman wrote, “Anthropic serves an expensive product to rich people.”

The System That Will Win Enterprise AI

As we start Q2, I want to begin where we always should: with our customers. I have been spending time with leaders across our largest enterprises, most influential startups, and key venture firms. The message is clear. People are excited about what we are building, and they want a deeper view into our roadmap so they can plan with confidence and stay ahead of the market.

Enterprise AI is entering a more mature phase. Raw capability still matters, but it is no longer enough. Customers want fit: how well AI plugs into their workflows, knowledge, controls, and day-to-day operations, and how effectively it can be deployed, trusted, and improved over time. They want a system they can trust and build on.

We are building that system: the best models for work, a platform for agents, deep integration with business context, and the ability to deploy and improve at scale. And customers are validating that direction in the clearest possible way. Multi-year, multi-product, nine-figure deals are rising, and existing customers are expanding as they standardize on our capabilities across more of their organizations.

Here are the customer-backed priorities I want us to focus on:

1. Win the model layer for work: Enterprises pay for models that help employees write faster, analyze better, and code more productively. Our new model, codenamed 'Spud', is a step toward the next generation of work with stronger reasoning and reliable output.
2. Win the agent platform layer: The market has moved from prompts to agents. We need to position 'Frontier' as the default platform for enterprise agents – the core intelligence layer enterprises use to build and scale systems.
3. Expand the market through Amazon: Our partnership with Amazon Bedrock expands access for AWS-native customers. The Amazon Stateful Runtime Environment moves beyond stateless model access toward systems that operate reliably over time.
4. Leverage Compute Advantage: Our compute advantage sets us up to deliver continuous leaps in capability, higher token limits, and lower latency.