Code Quality in the Age of AI ✅

How to create a process for quality throughout the whole SDLC.

Last month, the 2024 DORA report came out, and as always it was full of interesting insights. A good part of it explored the impact of AI on engineering teams, and reported a surprising finding: Despite AI’s potential benefits, our research revealed [that] AI adoption may negatively impact software delivery performance. As AI adoption increased, it was accompanied by an estimated decrease in delivery throughput by 1.5%, and an estimated reduction in delivery stability by 7.2%. So, in many cases, the gains in pure coding throughput do not translate into general software delivery…

related reading

• AI is removing the middle class of software engineeringblog.florianherrengt.com
• claude code is not making your product betterethanding.substack.com
• How AI assistance impacts the formation of coding skills \ Anthropicanthropic.com
• Code was our medium for thoughtwattenberger.com
• Software Engineering in the Age of AIadiamond.me
• Would you fly on an AI-coded plane | Hackle's bloghacklewayne.com
• Does Code Quality Still Matter? It Depends on This — Max Kanat-Alexander, Capital Oneyoutube.com
• The Case for Software Craftsmanship in the Era of Vibes — Zed's Blogzed.dev
• Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wildalphaxiv.org
• The 70% problem: Hard truths about AI-assisted codingaddyo.substack.com
• Coding Models Are Doing Too Much | whnrehiew.github.io
• When AI Writes the World's Software, Who Verifies It? — Leonardo de Mouraleodemoura.github.io