TITLE: Google Engineer Says AI Tool Replicates Year's Work in 1 Hour

Google Engineer Highlights AI's Speed in Replicating Complex Task

A principal engineer at Google has disclosed that an artificial intelligence coding tool from rival Anthropic completed a software design task in one hour that required nearly a year of effort from her team.

Jaana Dogan, who works on Google's Gemini API, shared the experience on X, formerly Twitter, on Jan. 2, 2026. She described providing Anthropic's Claude Code with a description of the problem — building distributed agent orchestrators to manage multiple AI agents collaboratively — and receiving an output that closely mirrored Google's eventual solution.

"I'm not joking and this isn't funny. We have been trying to build distributed agent orchestrators at Google since last year. There are various options, not everyone is aligned... I gave Claude Code a description of the problem, it generated what we built last year in an hour," Dogan posted.

The revelation quickly gained traction, amassing over 4 million views and igniting discussions among developers about AI's potential to streamline software development processes traditionally bogged down by meetings and internal disagreements.

Details of the Test and Limitations

Dogan clarified that her test was conducted fairly, without using any proprietary Google data. Instead, she crafted a simplified, toy version of the problem based on publicly available concepts. The prompt consisted of just three paragraphs, outlining the need for systems that coordinate AI agents, akin to managing traffic flow among autonomous bots.

"It wasn't a very detailed prompt and it contained no real details given I cannot share anything proprietary. I was building a toy version on top of some of the existing ideas to evaluate Claude Code. It was a three paragraph description," she explained in a follow-up post on Jan. 3, 2026.

While impressed, Dogan emphasized that Claude's output was not flawless. "It would still need refinement," she noted, advising skeptics to experiment with AI tools on challenges they know intimately to appreciate their capabilities.

Google permits the use of Claude Code internally only for open-source projects, not for proprietary work, according to Dogan. Regarding whether Google's own AI models, like Gemini, could soon match this performance, she responded: "We are working hard right now. The models and the harness."

Broader Implications for AI in Software Development

The incident underscores the accelerating pace of AI-assisted coding. Dogan reflected on the evolution: in 2022, such tools handled single lines of code; by 2025, they could reconstruct entire codebases. She expressed motivation rather than concern, stating, "Claude Code is impressive work. I'm excited and more motivated to push us all forward."

Developers responding to her posts highlighted how AI circumvents bureaucratic hurdles, fostering quicker innovation. One common theme was that while AI won't eliminate collaborative elements like whiteboards or team discussions, it could significantly reduce the time spent on initial planning and prototyping.

This event occurs amid intensifying competition in the AI sector. Anthropic, founded by former OpenAI executives, positions Claude as a safe and capable alternative to models like OpenAI's GPT series and Google's Gemini. Claude Code, a specialized tool for code generation and organization, has been praised for its ability to handle complex, multi-step programming tasks.

Google, a leader in AI research, has invested heavily in its own tools. The company's DeepMind unit and broader AI efforts aim to integrate advanced capabilities into products like Gemini, which powers features across Search, Workspace, and Android. However, Dogan's account suggests that external tools are setting a high bar for internal development speed.

Industry Reactions and Future Outlook

The tech community has reacted with a mix of awe and caution. Some developers shared similar anecdotes of AI tools outperforming human-led efforts on routine tasks, while others warned against over-reliance, citing risks like hallucinations — where AI generates incorrect but plausible code — or security vulnerabilities.

Analysts view this as evidence of AI's disruptive potential in software engineering, a field employing millions worldwide. A 2025 Gartner report projected that by 2027, AI could automate up to 80% of coding tasks, potentially reshaping job roles toward oversight and integration rather than from-scratch development.

Dogan's experience also highlights ethical considerations in AI benchmarking. By using public-domain ideas, she ensured transparency, but it raises questions about how companies evaluate competitors' tools without breaching confidentiality.

As AI coding assistants mature, experts anticipate a hybrid future where human expertise guides AI outputs. Dogan's call to action — for engineers to test these tools rigorously — may encourage broader adoption and innovation across the industry.

Google declined to comment on internal development timelines or specific comparisons with rival tools. Anthropic did not immediately respond to requests for comment on Claude Code's performance in this scenario.