Developer experience is one of the areas where AI applications are showing significant return on investment, but there are significant hurdles to overcome in both changing established development patterns, as well as integrating AI tooling. Analyst Jean Atelsek and AWS vice president for developer experience Deepak Singh join host Eric Hanselman to explore the current state of AI code assistance and look at where it’s headed. Auto-complete, where the next bit of a line of code is filled in for a programmer, has been evolving over a number of years, but the arrival of agents to augment code generation and task automation is being to revolutionize software development. Changing development patterns is hard, but the benefits offer strong incentives to change habits. Where early uses had AI engines generate smaller code snippets that developers integrated, that’s changing to having AI tackle full functions that are then reviewed and corrected. Tooling around AI implementations are tailoring they way in which they interact with individual developers, enhancing their experience.

Application modernization is an area where AI can shine, as it can assess a massive codebase whose authors are no longer available and provide not only documentation, but also prioritize recoding efforts. It’s a task where the hours required for manual assessment can be daunting and error prone. Leveraging AI code generation securely requires that organizations have sufficiently secure development pipelines. Mitigating risks from confabulation and errors in AI generated code is the same process as ought to be in place for human coders, an area where some less mature organizations may have some catching up to do.

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Credits:

• Host/Author: Eric Hanselman
• Guests: Jean Atelsek, Deepak Singh
• Producer/Editor: Adam Kovalsky
• Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith