Source URL: https://simonwillison.net/2025/May/19/jules/#atom-everything
Source: Simon Willison’s Weblog
Title: Jules
Feedly Summary: Jules
It seems like everyone is rolling out AI coding assistants that attach to your GitHub account and submit PRs for you right now. We had OpenAI Codex last week, today Microsoft announced GitHub Copilot coding agent (confusingly not the same thing as Copilot Workspace) and I found out just now that Google’s Jules, announced in December, is now in a beta preview.
I’m flying home from PyCon but I managed to try out Jules from my phone. I took this GitHub issue thread, converted it to copy-pasteable Markdown with this tool and pasted it into Jules, with no further instructions.
Here’s the resulting PR created from its branch. I haven’t fully reviewed it yet and the tests aren’t passing, so it’s hard to evaluate from my phone how well it did. In a cursory first glance it looks like it’s covered most of the requirements from the issue thread.
My habit of creating long issue threads where I talk to myself about the features I’m planning is proving to be a good fit for outsourcing implementation work to this new generation of coding assistants.
Tags: gemini, ai-assisted-programming, google, llms, ai, generative-ai, github
AI Summary and Description: Yes
Summary: The text discusses the emergence of AI coding assistants, specifically highlighting Google’s Jules, which has entered beta. This aligns with the growing trend of AI tools in software development that can streamline the coding process by handling tasks such as creating Pull Requests (PRs) for GitHub issues.
Detailed Description: The provided text reflects the current advancements in AI-assisted programming tools that are increasingly being integrated into platforms like GitHub. Here are the key points:
– **Emergence of AI Coding Assistants**: The text mentions several AI coding assistants released recently, including OpenAI Codex and Microsoft’s GitHub Copilot, indicating a surge in AI applications in the software development domain.
– **Google’s Jules**: Specifically, Jules, which is now in a beta preview, is noted for converting GitHub issue threads into actionable code contributions without requiring extensive input from the user. This showcases how generative AI can facilitate programming tasks by interpreting issue threads and generating code.
– **User Experience with Jules**: The author’s firsthand experience with Jules is described, emphasizing its ability to create a Pull Request (PR) based on a GitHub issue. Although the initial evaluation indicates some test failures, the response to Jules illustrates the potential for efficiency improvements in software development.
– **Trends in Automated Code Generation**:
– Increasing reliance on AI tools for coding tasks.
– Opportunities for developers to outsource implementation work through these technologies.
– The evolving nature of programming where AI can take over repetitive tasks, allowing developers to focus on higher-level planning and architecture.
– **Tags and Relevance**: The use of tags like “ai-assisted-programming” and “generative-ai” reinforces the relevance of this text in the context of AI and software security, as these tools must also adhere to security and regulatory standards to ensure safe coding practices.
In conclusion, the emergence of tools like Jules signals a transformative period in software development where AI plays a substantial role in enhancing productivity while adhering to best practices in security and compliance, particularly as these tools integrate deeper into development workflows. This represents a significant intersection of AI and software security that professionals should monitor.