At QCon London 2026, Jeff Smith discussed the growing mismatch between AI coding models and real-world software development. While AI tools are enabling developers to generate code faster than ever, S

InfoQ is a leading online platform for software developers, architects, and technical leaders, providing news, articles, presentations, and interviews on a wide range of topics, including agile practices, DevOps, microservices, and emerging technologies. With a focus on quality content and expert insights, InfoQ helps professionals stay informed about the latest trends, best practices, and industry developments. Developers can learn from real-world experiences, gain  knowledge, and connect with peers in the global software community through InfoQ's diverse and engaging content.

InfoQ

Jeff Smith's QCon London 2026 talk addresses the growing mismatch between AI coding models and real-world codebases. AI tools are trained on public repository snapshots and lack organization-specific knowledge, causing them to generate syntactically correct but architecturally non-compliant code. Data shows AI-assisted pull request volume has surged since 2022, but acceptance rates have dropped. Smith categorizes repository constraints into architectural rules (component patterns, dependency handling) and procedural rules (PR conventions, testing expectations), noting these are often enforced implicitly during code review. He proposes 'repository fingerprinting' to systematically extract and document these implicit rules, making them accessible to AI systems. The core argument is that the AI-code quality gap is a knowledge management problem, not a tooling problem, and teams that explicitly document their repository constraints will gain a competitive advantage.

QCon London 2026: Refreshing Stale Code Intelligence