From fragmented code to consistent output with AI rules (www.stromcapital.fi)

In a recent discussion, Roni Ström, the founder of a tech startup, highlights the transformative potential of implementing structured, capability-specific rules in AI-assisted development. Many developers currently rely on generic prompts to interact with AI, leading to fragmented code and inconsistent outputs. Ström argues that by adopting persistent instructions—termed differently across platforms, such as Cursor Rules or Copilot Instructions—developers can significantly enhance productivity and code consistency. Ström outlines a four-level maturity model for AI interaction: starting from no rules at all, to the advanced use of capability-specific rules. The highest level emphasizes focused guidance tailored for specific architecture capabilities, complete with explicit instructions and code samples. These rules prevent the AI from making assumptions about code structure, enabling it to produce more reliable, coherent code output. As developers refine these rules in response to AI mistakes, they create a feedback loop that allows the AI to learn and improve, resulting in less time spent debugging and a more efficient development process overall. This structured approach could revolutionize AI integration in software development, paving the way for more sophisticated and precise AI tools.