![]() Fortunately, the industry has moved away from using lines of code as a measure of output. ![]() We discussed many modern tools and techniques for this Radar that take more nuanced approaches to measuring the creative process of building software yet still remain inadequate. Our chief scientist, Martin Fowler, wrote about this topic as long ago as 2003, but it hasn't gone away. Software development can sometimes seem like magic to non-technologists, which leads managers to strive to measure just how productive developers are at their mysterious tasks. At the same time, we hope developers use all of these tools responsibly and stay firmly in the driver's seat, with things like hallucinated dependencies being just one of the security and quality risks to be aware of. We're also excited about how open-source LLMs for coding might shake up the tooling landscape, and we see great promise in the explosion of tools and capabilities for assistance beyond coding as well, such as user story writeup assistance, user research, elevator pitches and other language-based chores. As part of the Radar, we therefore discussed many coding assistance tools, like GitHub Copilot, Tabnine and Codeium. As a software consultancy with a history of pioneering engineering practices like CI and CD, one of the categories of particular interest to us is using AI to assist in software development. For the first time ever, we needed a visual guide to untangle the different categories and capabilities (something we never had to resort to even in the heyday of chaos in the JavaScript ecosystem). ![]() To no one's surprise, AI-related topics dominated our conversation for this edition of the Radar.
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