Google’s AI Coding Agent Jules Graduates from Beta, Introduces Structured Pricing

Google has officially transitioned its AI coding agent, Jules, out of beta, marking a significant step for AI-assisted software development. Launched just over two months after its public preview debut in May, Jules, powered by the robust Gemini 2.5 Pro model, is now available to a wider audience.

Jules operates as an asynchronous, agent-based coding tool designed to integrate seamlessly with platforms like GitHub. It functions by cloning codebases into Google Cloud virtual machines, where it intelligently fixes or updates code, allowing human developers to concentrate on higher-level tasks and strategic problem-solving.

Originally announced as a Google Labs project in December, Jules was made available to beta testers during Google’s I/O developer conference. Kathy Korevec, Director of Product at Google Labs, shared that the decision to exit beta was driven by the tool’s enhanced stability, a result of hundreds of UI and quality updates implemented during the beta phase. “The trajectory of where we’re going gives us a lot of confidence that Jules is around and going to be around for the long haul,” Korevec stated.

With its wider rollout, Google has introduced structured pricing tiers for Jules. An “introductory access” free plan is available, capped at 15 individual daily tasks and three concurrent tasks, a reduction from the 60-task limit during the beta. For more extensive use, paid tiers are integrated with Google AI Pro and Ultra plans, priced at $19.99 and $124.99 per month, respectively. These paid plans offer subscribers five times and twenty times higher task limits, catering to different user needs.

Korevec explained that the pricing structure is informed by “real usage” insights gathered during the beta period. “The 60-task cap helped us study how developers use Jules and gave us the information we needed to design the new packaging,” she said. “The 15/day is designed to give people a sense of whether Jules will work for them on real project tasks.”

Google has also refined its privacy policy for Jules to offer greater clarity on AI training practices. While data from public repositories may be used for training, Korevec assured that no data from private repositories is sent. “We got a little bit of feedback from users that it [the privacy policy] wasn’t as clear as we thought it was, and so most of it is just responding to that. We didn’t change anything about what we’re doing on the training side, but we changed the language,” Korevec added.

During its beta phase, thousands of developers utilized Jules to tackle tens of thousands of coding tasks, resulting in over 140,000 code improvements that were shared publicly. User feedback directly influenced the addition of new capabilities, including reusing previous setups for faster task execution, integrating with GitHub issues, and supporting multimodal input.

The primary users identified for Jules are AI enthusiasts and professional developers. A key differentiator for Jules is its asynchronous operation within a virtual machine, contrasting with synchronous tools like Cursor and Windsurf. “Jules operates like an extra set of hands… you can basically kick off tasks to it, and then you could close your computer and walk away from it if you want and then come back hours later,” Korevec explained, highlighting the flexibility it offers developers.

Recent updates have further enhanced Jules’ capabilities, including deeper integration with GitHub to automatically open pull requests and branches, as well as the introduction of “Environment Snapshots” for saving dependencies and install scripts, ensuring faster and more consistent task execution.

Beta Trials Informed Jules’ Development

During its public beta, Jules recorded 2.28 million visits globally, with 45% originating from mobile devices, according to data reviewed by TechCrunch from market intelligence provider SimilarWeb. India led in traffic, followed by the U.S. and Vietnam.

Observations from the beta phase revealed that users frequently employed Jules for bug fixing and enhancing projects to make them more production-ready. Initially requiring an existing codebase, Google expanded Jules’ functionality to work even with empty repositories, broadening its appeal and usage. The increasing mobile usage has prompted Google Labs to explore features specifically needed by users on mobile devices.

Internally, Google is already leveraging Jules for several projects and plans to expand its use across more projects within the company, underscoring its confidence in the AI coding agent’s capabilities.