Google assembles strike team to catch up with Anthropic in lucrative AI coding race

Google's Internal Politics Leave It Playing Catch-Up on AI Coding

At Google, leaders are anxious about falling behind in the race to offer AI coding tools, especially as rivals like Anthropic PBC offer more effective and popular tools to businesses, according to people familiar with the matter. The search giant is now working to unite some of its coding initiatives under one banner to speed progress and take advantage of a surge in customer interest. In some corners of Alphabet Inc.'s Google, particularly AI lab DeepMind, concerns about the company's position are mounting, according to current and former employees and executives, who declined to be named because they weren't authorized to speak publicly. Businesses are just starting to realize that AI coding tools can enable anyone to build products by prompting a chatbot. But Google doesn't have a clear solution for them. Its Gemini model's capabilities are sprinkled across half a dozen different coding products with different branding, indicating how the company's lack of focus and competing internal efforts have hampered success, the people said. Even internally, some Google engineers prefer to use Anthropic's Claude Code, they said. More concerning, the people said, are the engineers who are struggling to adopt AI coding at all. Google has made some effort to reduce the internal confusion over priorities. Chief AI Architect Koray Kavukcuoglu is working with Google's main engineering team to unite the company's internal artificial intelligence coding tools in the coming weeks under Antigravity, a platform released last year, according to a spokesperson. DeepMind is also devoting more resources to AI coding by forming a new team led by research engineer Sebastian Borgeaud, according to a former Google employee. That new team was earlier reported by The Information. John Jumper, who won the Nobel Prize in 2024 alongside Google DeepMind Chief Executive Officer Demis Hassabis, is also at work on AI coding, according to a person familiar with the matter. Google was widely viewed as ascendant in AI late last year with the release of Gemini 3, a model that appeared to outperform rival services across a range of benchmarks. In recent months, however, Anthropic and OpenAI have gained business momentum by focusing on the lucrative market for products that streamline the process of writing and debugging code to speed up software development. "Coding is the single easiest way to actually make money," said Keith Zhai, co-founder of startup TinyFish, which makes web agents. Many engineers in the valley toggle back and forth between Claude Code and OpenAI's Codex to see which program will give them the best results, but Google often isn't in the conversation, he added. Google still has plenty of reasons to feel confident about its position: the company has made big strides in the quality of its foundation models, which underlie coding tools, and it has deep pockets and substantial computing power. "We've seen tremendous adoption of our internal coding tools such as Antigravity and others since introducing them over recent years, and their use has been turbocharging our model and AI tooling development," a Google spokesperson said in a statement. Meanwhile, Google has been eager to tout the speed of its internal culture change. Alphabet said in February that roughly 50% of new code at the company is written by AI. But Silicon Valley engineers are embracing AI coding so quickly that even a momentary lag in the market could be consequential. There is a growing conviction in the industry that coding is not just a lucrative early application of AI, but the key to building software that matches human capabilities, said Raj Gajwani, a former Google executive who is now chief business officer of startup OpenArt AI. "From a computer science point of view, if you win at coding this year, you get the raw data you need to win at model capability next year," he said. Google's emphasis on its own technology has also complicated the push to catch up. Most employees are banned from using competing tools such as Claude Code or Codex due to security concerns, but Googlers can request exceptions if they can demonstrate they have a business case, one former employee said. Some teams at DeepMind, including those working on the Gemini model, internal applications, and open source models, use Claude Code, according to three former employees. "You want the best people to use the best tool, even inside Google," one of the former employees said. Anthropic cut off OpenAI's access to its models last year, Wired magazine reported. Google has invested billions of dollars in Anthropic. A spokesperson for Anthropic did not immediately reply to a request for comment. In recent years, DeepMind has tried to tighten control over how its AI breakthroughs are woven into Google products. Last year, Google appointed Kavukcuoglu to a new position as chief AI architect, a role in which he is charged with folding generative AI into Google products. Yet confusion about who is leading the charge on AI coding persists. Along with DeepMind, Google Cloud, Google Core, Google Labs and Android are all pushing AI coding in different ways, one of the people said. Google released its Antigravity platform last year following the acquisition of talent and technology from startup Windsurf in a $2.4 billion deal. It joined a cluttered lineup of Google AI coding tools that includes Gemini Code Assist, Gemini CLI, AI Studio, Firebase Studio and Jules. Kathy Korevec, who oversaw Jules, jumped from Google to OpenAI earlier this month, according to her LinkedIn profile. In a post on social network X, Korevec wrote that Google had an opportunity to build AI developer tools that "feel cohesive, intuitive, and truly great to use. What I saw more often was fragmentation. Parallel tools. Overlapping surfaces. Smart teams solving similar problems in slightly different ways. That's not a talent problem. It's a systems problem." Korevec didn't immediately reply to a request for comment. Get the Tech Newsletter bundle. Get the Tech Newsletter bundle. Get the Tech Newsletter bundle. Bloomberg's subscriber-only tech newsletters, and full access to all the articles they feature. Bloomberg's subscriber-only tech newsletters, and full access to all the articles they feature. Bloomberg's subscriber-only tech newsletters, and full access to all the articles they feature. Plus Signed UpPlus Sign UpPlus Sign Up By continuing, I agree to the Privacy Policy and Terms of Service. Within the Googleplex, there is a philosophical clash between AI researchers who want to move as quickly as possible and more traditional senior engineers who have exacting standards for code quality, former employees say. AI usage is factored into performance reviews, according to a former employee. But engineers who try to use internal AI coding tools often hit capacity constraints due to competition for computing power, the former employee said. One of the executives who oversaw efforts to promote AI coding within Google, Brian Saluzzo, recently departed. Saluzzo did not immediately reply to a request for comment. Companies are still figuring out how to best incorporate AI into their workflows, and having a variety of products on offer gives Google more chances to see what sticks. But incumbent players like Google have only so much of an edge, said Deepti Srivastava, a former Google executive who is founder and CEO of AI startup Snow Leopard. "The market is moving too fast for the larger companies to think about it and then move," Srivastava said. "Speed is your only moat."

Google Puts Together A-Team to Build Better Coding Models Than Anthropic

Google co-founder Sergey Brin is said to be involved in the project Coding seems to be the flavour of the month for artificial intelligence (AI) companies. Recently, OpenAI increased its focus on its coding platform Codex, and now Google appears to be shifting its focus as well. As per a report, the Mountain View-based tech giant's DeepMind division has created a specialised team that has been tasked with building AI models focused on coding. The aim is, reportedly, to close the gap between the company and Anthropic and is likely to secure a larger share of the lucrative high-ticket enterprise revenue. Google's A-Team Targets Anthropic's AI Models According to The Information, Google DeepMind has created a new team of researchers and engineers to develop the coding capabilities of future Gemini models and to build coding-focused large language models (LLMs) from scratch. This team is reportedly being led by research engineer Sebastian Borgeaud, who previously looked after pre-training of AI models. Some of the areas the team is focused on are said to be complex coding work, long-horizon programming, writing an entire software from scratch, and enabling the models to read files to contextually understand the requirements of the user. It appears that the company is aiming to develop an AI model capable of handling end-to-end coding tasks. Google's Co-Founder, Sergey Brin, and DeepMind's CTO, Koray Kavukcuoglu, are reportedly directly involved with the team. In an internal memo seen by the publication, Brin reportedly highlighted the need to "urgently bridge the gap in agentic execution and turn our models into primary developers." The Co-Founder is also said to have asked engineers working on Gemini to use internal agents for complex tasks. Google is reportedly pushing to improve the coding capabilities of its models because the executives believe that Anthropic's models are better at such tasks, and the Gemini maker does not want to be left behind. With the enterprise adoption of AI coding tools increasing, major AI players have switched their focus to developing models that can handle complex tasks autonomously. Just last week, OpenAI upgraded Codex with Computer Use and image generation capabilities, allowing the desktop app to access files, apps, and interfaces to write code, run programs, test software, and iterate on existing builds. The image generation feature also bolsters the coding tool's ability to handle frontend tasks.

Google creates strike team to improve AI coding models, catch up with Anthropic: Report

The team is expected to focus on building AI systems that can handle complex, long-term coding tasks. Google has reportedly created a strike team to improve its AI coding models. According to a report by The Information, the move comes after growing belief within Google DeepMind that coding tools developed by Anthropic are currently ahead of Google's own Gemini models. AI-assisted coding has become one of the most competitive areas. Anthropic has been focusing heavily on this segment with its tool Claude Code. The company has even said that most of its code is now written with the help of AI. However, according to Google's CFO Anat Ashkenazi, AI currently writes around half of the company's code. The new strike team is expected to help improve that number while strengthening Google's AI coding capabilities overall. Also read: OpenAI releases Chronicle in Codex: What is it and how to use The strike team is led by Sebastian Borgeaud, who previously worked as the pre-training lead for Gemini at Google DeepMind. The group is expected to focus on building AI systems that can handle complex, long-term coding tasks. Also read: 'Legend': Sam Altman and other leaders react as Tim Cook steps down as Apple CEO Senior leadership is also said to be closely involved in the initiative, including Google co-founder Sergey Brin and DeepMind CTO Koray Kavukcuoglu. Google is also reportedly focusing on using AI internally. Until now, many of the company's AI models have primarily been designed for external developers and customers. Google is even tracking how often employees use these AI coding tools through an internal leaderboard. For those unaware, Claude Code is an AI-powered coding assistant by Anthropic that can read, modify and execute code on your computer via natural language commands.