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Optimizing AI-Driven Code Generation in a 200k LOC C Codebase: Insights from Rsyslog

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Unlocking AI in Mature Software: The Rsyslog Case Study

Is AI truly overhyped? While some argue it’s just a money-burning fad, Rsyslog demonstrates otherwise. By treating AI as a serious engineering tool, we’ve fueled productivity and quality in a large, complex C codebase.

Key Insights:

  • Incremental Improvements: Early attempts (2023-2024) yielded little benefit; however, by 2025, asynchronous coding agents transformed our workflows.
  • Documentation Matters: Introducing agent-focused documentation (AGENTS.md) and enhancing inline comments significantly improved AI integration.
  • Fixing the Basics: Switching from tab to space indentation minimized noisy diffs, streamlining the code review process.
  • Continuous Process Evolution: AI support requires ongoing maintenance and adaptation to tackle real-world complexities.

Integrating AI into mature systems isn’t a set-it-and-forget-it strategy—ongoing refinement is crucial.

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