GitHub published new research on 23 September 2026 based on feedback from more than 1,000 GitHub users, looking at what developers want from modern software tools.
One theme highlighted by GitHub is software efficiency. Developers are looking for ways to reduce wasted compute while still shipping useful software.
Why this matters in the AI era
AI coding tools can make it easier to generate and modify code, but generating more code is not automatically the same as building better software. Compute costs, build times, test cycles and infrastructure usage still matter.
For developers, that means the fundamentals remain valuable:
- write smaller, focused changes;
- run targeted tests when possible;
- measure slow builds and expensive workloads;
- remove unused dependencies and services;
- understand the infrastructure behind AI-powered features.
A useful lesson for students
If you are learning programming with AI tools, do not stop at getting code that works. Learn to explain why the code works, how much it costs to run, how it behaves under load and how you would maintain it six months later.
AI can speed up development, but engineering judgment still matters.
Source
- <a href="https://github.blog/news-insights/" target="_blank" rel="noopener">GitHub Blog: latest developer news and insights</a>
<p><em>Published 23 September 2026. The research summary and findings are attributed to GitHub and Yale's study as described by GitHub.</em></p>