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What I've Been Thinking, Between Opportunity and Crisis

An ordinary software developer shares a personal meditation on AI's growing role in code production. The author describes an instance where an AI agent wrote a feature, built the data layer, generated tests, and fixed failures with minimal human input, then notes that the emotional satisfaction of wrestling with a hard problem diminished as automation took over. This experience prompts a broader reflection: AI can dramatically reduce friction and enable faster prototyping, but the benefit is not evenly distributed. Those who can recognize when the AI errs, understand architecture, and judge trade-offs still wield the most leverage, while beginners may become overly reliant on automation. The piece argues that ‘muscles’—deep coding fundamentals, mental models, and problem framing—must be kept active, even as autocomplete and code-generation tools become commonplace. The author suggests deliberate practice, occasionally writing from scratch, and learning to push back against over-reliance on AI to maintain capability. Ultimately, the craft is not typing code but solving problems with software, and accountability for outcomes remains human. The piece closes with four guiding ideas: view AI as a partner, preserve fundamental skills, ask the right questions, and recognize that the tool is a change in craft, not a replacement for human responsibility.