“Japan was our first or second most popular country in terms of user engagement overall,” said Russell Kaplan, president of Cognition AI, the San Francisco startup behind AI coding tool Devin, in early June. 

The East Asian country has the world’s oldest population, with almost 30% of its residents over the age of 65. Japan’s working-age population is projected to decline by over 30% between now and 2060. The decline leads to a shortage of programming talent: In 2023, Japan’s Ministry of Economy, Trade, and Industry (METI) estimated that the country would face a shortage of 789,000 software engineers by 2030. 

Cognition AI is making Japan the first step in its Asian expansion, opening a Tokyo office in April; it will follow with making Singapore its Asia-Pacific headquarters later this year.

The firm is betting that Japan will be the ideal proving ground for AI-powered software engineering. “The needs are real, especially in critical infrastructure and government,” Kaplan said. “The country is running on aging infrastructure with a declining workforce.” 

The efficiency gains could be immense. Faced with a national IT compliance mandate, Sapporo’s city government needed to modernize over one million lines of legacy code, which Kaplan estimated would have normally taken 200 engineering months of work. Using Devin, Sapporo’s engineers completed it in roughly a quarter of that time.

Even before Cognition officially launched in Japan, Devin was already going “viral” in Japan. “There was a debate of what the correct honorific for Devin was,” Kaplan said, referring to the suffixes attached to names to designate social hierarchy. 

“What the community settled on was Devin-kun.”

Japan’s bet on U.S. AI

Japan has become the preferred beachhead for U.S. AI companies eyeing global expansion. OpenAI and Anthropic both opened their first international offices in Tokyo. Microsoft, Alphabet, and other hyperscalers have committed billions to Japanese data centers. Japan was also the second country to secure access to Anthropic’s powerful Mythos model, with three of its largest banks—MUFG, Mizuho, and Sumitomo Mitsui—among those granted entry through Project Glasswing, a program to help key companies and critical institutions fix security vulnerabilities. (This access was quickly shut off after the U.S. barred all foreigners from using the model in mid-June.)

While South Korea, Singapore, and other regional economies have made sovereign AI a priority, Japan seems to be more comfortable sticking with U.S. AI, due to the country’s investment and close relationships with American AI labs.

Courtesy of Cognition AI

“Japan has disproportionately invested in working closely with U.S. companies to influence the roadmaps of those companies to meet local domestic needs,” Kaplan said. One of OpenAI’s biggest investors is Softbank, the massive Japanese telecoms company run by tech booster Masayoshi Son.

AI could present an opportunity for Japan to integrate its digital systems with the rest of the world. Kaplan suggested that low English proficiency “has led to a bit more isolation for some businesses in Japan.” Yet AI’s native multilingualism chips away at that barrier. Japanese engineers can work with Devin entirely in Japanese while collaborating through the agent with teams on the other side of the world. 

AI coding reaches Asia

Cognition AI, founded in 2023, is best known for its AI coding tool Devin. The tool operates as a full AI software engineering teammate: Give it a task, and it codes, debugs, and deploys code autonomously inside the tools an engineering team already uses. 

Devin was one of the earliest instances of “AI employees,” or agents that are fully integrated into workplace tools like Slack that employees can assign tasks to without resorting to constant prompting.

In late May, Cognition raised more than $1 billion in a new funding round that valued the startup at $26 billion, more than doubling its valuation from a September 2025 round. The company’s annualized run rate reached $492 million at the time of the raise, up from just $37 million a year earlier.

Cognition AI’s coding tools, to some investors, pose an existential threat to existing programmers and software engineers, particularly in countries like India, a traditional hub for back-office work. The prospect of AI agents performing that same work at a fraction of the cost has rattled investors. Shares in Infosys, Wipro, Tata Consultancy Services, and HCLTech have all fallen between 30% and 40% over the past 12 months. 

But Kaplan isn’t worried about India’s ability to adapt to AI. “On the ground in India, the job of an engineer can become more fun and impactful. Suddenly you have someone who has been working by themselves on a specific part of a project, and they’re getting a promotion where they have a whole team of AI agents working for them.” Kaplan said. “The companies we work with are using productivity gains to become more ambitious.”

One of Cognition’s more unexpected growth markets is Malaysia. The country’s capital, Kuala Lumpur, has become a regional software engineering hub, driven by a large English-speaking talent pool, lower operating costs, and proximity to the rest of Southeast Asia. Kaplan described the engineers his team encountered there as among the most skilled in the world at managing AI agents.

Cognition has launched what it calls an Applied AI Engineering program in Malaysia, which identifies top engineers who excel at directing agents and training them to be able to teach entire teams on how to work effectively with AI.

Kaplan is also looking closely at South Korea and Australia as possible Asia-Pacific expansion markets. 

Cognition’s expanding presence is uncovering another benefit. Compute, the processing power that AI systems run on, is a finite resource; Kaplan says demand at Cognition is doubling roughly every seven weeks. But geographically diverse teams allow compute to be used during off-peak hours on Wall Street and Silicon Valley. “When people are at work in Japan, people in New York are asleep,” Kaplan said. “There’s a lot of efficiency you get as an AI company working that way.”