OpenAI Cuts Side Projects to Bet on Coding and the Enterprise Market

OpenAI is preparing a notable strategic turn: the company no longer wants to storm every possible AI market at once and plans to set priorities more strictly. The main goal is not to lose pace in the race against Anthropic and other competitors that turn AI products into clear businesses faster.

Why the course is changing

After ChatGPT's explosive success in autumn 2022, OpenAI could afford to do almost everything at once: launch new consumer use cases, test video, think about a browser, shopping tools and even hardware devices. That approach helped the company establish itself as the main symbol of generative AI, but as the market matured it began to backfire. When a team tries to cover too many directions, part of its resources goes not into strengthening the core but into experiments that are hard to monetize quickly and even harder to fit into a single strategy.

At an internal meeting, employees were given to understand that the era of broad expansion is ending. Leadership, headed by Sam Altman and Mark Chen, is reviewing its portfolio of initiatives and deciding which ones should no longer count as priorities. Inside the company the explanation is simple: OpenAI cannot miss this moment while the market is dividing up leadership in the most lucrative segments, developers and enterprise customers.

"We cannot miss this moment because we are being distracted by secondary tasks."

OpenAI's new bets

The two main directions now look obvious: software code generation and products for business. This is where competitors have started to press especially hard. Anthropic has grown noticeably stronger thanks to developer tools and enterprise deployment, segments where companies are more willing to pay large checks and stay customers longer. For OpenAI this is no longer a question of image but of revenue, market share and preparing for the next big stage of growth.

So OpenAI wants to win back the initiative with professional audiences faster. Fresh releases such as Codex and the GPT-5.4 model, which is more strongly tuned for work and engineering scenarios, are meant to help. According to the company's internal data, Codex is already used by more than two million people a week, roughly four times more than at the start of the year. In parallel, OpenAI is strengthening contact with customers and outside consultants, so it can develop models not only from lab logic but also for real business tasks.

There is a separate emphasis on productivity. The new strategy boils down not to an abstract "do more AI" but to helping users, especially corporate ones, write code faster, automate routine work and get measurable value. In this sense OpenAI is trying to reinvent itself from a company that launches many loud experiments into one that systematically turns its models into a working tool.

What will fade into the background

This does not mean OpenAI will shut down all additional products at once. But some initiatives will clearly get less attention, fewer resources or less independence. Last year the company managed to enter several disparate directions, and these are the first to come under review.

Sora is a telling example: after its standalone launch, interest in the product declined, and the plan now is to build the service deeper into the ChatGPT ecosystem instead of developing it as a separate app. Under pressure from the new strategy, the following may take a back seat:

• individual consumer experiments that do not deliver fast revenue growth;
• standalone apps outside the ChatGPT core;
• projects at the intersection of e-commerce and AI shopping;
• initiatives around the browser and hardware devices, if they do not directly strengthen the core business.

The shift is driven not only by competition but also by financial logic. OpenAI is reportedly considering an IPO before the end of the year, and in that situation companies usually need to show clear discipline: where exactly they make money, which areas are scaling and why it makes sense to invest even more in them. For OpenAI's leadership this means less dispersion and more focus on products that are easier to sell to large customers and simpler to explain to investors.

What this means

OpenAI is entering a more mature phase: the era of endless AI experiments is giving way to a fight for specific markets and stable monetization. For the industry, this is a signal that the main battle in the near term will play out not over the flashiest demos but over code, enterprise use cases and who is first to turn AI into a mandatory working layer for business.