Misalignment: The hidden cost of AI coding agents isn't from AI at all

The primary cost of using AI coding agents lies in misalignment rather than the tools or tokens, leading to rework, inefficiencies, and slower team performance. Often, discussions around AI agents focus on model capabilities and benchmarks, but the real issue is the gap between AI-generated code and the intended outcome, which results in time-consuming rework and revisions. The fast execution of AI can exacerbate misalignment, creating a cycle of prompt tweaking and code correction. This problem highlights the importance of collaborative planning, which aligns team expectations and prevents costly misalignments by clarifying intent before AI agents generate code. CodeRabbit's Issue Planner addresses this by integrating with issue trackers to create detailed coding plans, ensuring that AI execution starts with clear directives, thus minimizing misunderstandings and aligning development processes around shared goals from the outset. Successful AI adoption focuses on reducing rework and enhancing alignment through effective planning, rather than simply chasing the best-performing model.