Spend Your Compute on Correctness (juanreyero.com)

Recent developments in AI programming have shifted the focus from merely increasing code output to ensuring the correctness of the code generated by AI agents. With tools like Claude Code and Codex significantly enhancing productivity, the challenge now lies in validating that the code not only functions as intended but is also architecturally sound and aligns with user needs. This change signifies a pivotal moment for the AI/ML community, emphasizing the importance of investing computational resources in validation processes—including rigorous testing, continuous code review, and architectural assessments—rather than just production throughput. The transition to prioritizing correctness requires a strategic allocation of resources toward different validation layers. This includes human judgment at the product layer, architectural reviews to maintain code structure over time, and oversight to ensure implementation accuracy. Proposed solutions range from integrating code-reviewing subagents to employing specialized reviewer agents alongside coding bots, fostering a collaborative environment that enhances the quality of software development. By embracing this model, developers can produce not only more code but correct code, thereby redefining the objectives of agentic programming and the future dynamics of AI-assisted development workflows.