Think for Yourself (kevlinhenney.medium.com)

Think for Yourself is a practical manifesto for developers who commit LLM-generated code: don’t treat generated snippets as drop-in solutions. Before merging, verify the code with automated tests (unit/integration), ensure you can explain and reason about its behavior, compare it to how you would implement the same feature, and make at least one concrete improvement. The piece gives a short checklist—“Does it work? Do you understand it? What’s different? How can you improve it?”—emphasizing active code ownership: testing, comprehension, and iterative refinement rather than blind acceptance. For the AI/ML community this is a reminder that generative tools are augmentation, not replacement. Over-reliance can deskill teams, generate technical debt, and produce “pessimisation” or legacy code that increases long-term failure demand despite short-term throughput gains. Practically this means embedding LLM outputs into robust CI pipelines, rigorous code review, measurable value-oriented metrics (not just ticket velocity), and training developers to interrogate and learn from model suggestions. The core message: keep humans actively in the loop—use AI as a power tool to amplify craftsmanship, not to outsource understanding or responsibility.