Using personalized AI agents to speed up software development and improve code quality

AI code assistants are becoming an expected part of every developer’s toolchain. But not everyone sees real benefits from them, and concerns persist about the quality of what they generate.

Tabnine’s John Feeney reveals practical ways to make AI tools more relevant to your specific needs, significantly enhancing developer productivity and code quality. He explains the role of retrieval-augmented generation (RAG) and the importance of using your existing codebase as context and offers guidance on the best way to customize and fine-tune AI code agents.

Speaker

John Feeney, Principal Architect, Office of the CTO, Tabnine 

John Feeney is a Principal Architect within the CTO Office at Tabnine. Prior to helping Tabnine’s customers accelerate their software development cycles through the use of AI, he worked with various APM and DevOps tooling vendors to help drive development and operational efficiencies. He is based in Dublin, Ireland.