A user experienced an AI agent making extensive, undesirable changes across multiple files, "messing up the whole code." While the agent eventually could undo the changes, it took the user three hours to realize this capability. This indicates a need for more intuitive, robust, and easily discoverable undo or change management features specifically for modifications made by AI agents, to prevent significant time loss and frustration when agents make errors.
I’m excited to share my latest video: “How to Master Agentic AI Development: Best Practices for Developers”. In this session, I explore how developers can leverage agentic AI tools—like GitHub Copilot and Cursor—to accelerate and streamline their workflow. Key takeaways include: • Why version control (Git) is essential when using AI-generated code • Why and how break down tasks into small, manageable increments • The role of PRD templates and clear, precise prompts • Best practices for debugging, testing, and maintaining code quality • Leveraging MCP (Model Context Protocol) servers to 10x the development speed. By applying these strategies, developers can reduce iteration cycles, save on token usage, and ultimately build more reliable solutions with AI assistance. If you're looking to integrate AI into your development process—or simply want to code more efficiently—this video is for you. I’d love to hear your thoughts and answer your questions in the comments. Watch the full video on my YouTube channel, and feel free to share if you find it valuable! - https://lnkd.in/ghK_iafr #AgenticAI #AIDevelopment #Copilot #VersionControl #MCP #DeveloperProductivity #SoftwareEngineering #AIinCode #FullStackDevelopment