As coding becomes increasingly AI-assisted, a backlash is emerging from programmers who value the craft of coding itself. This thoughtful counter-trend emphasizes the importance of cognitive struggle in programming skill development and advocates for intentional rather than reflexive AI use. The debate highlights a fundamental tension: whether coding is primarily about efficient output or a craft whose practice develops crucial problem-solving abilities that AI assistance might inadvertently diminish.
The big picture: A deliberate return to more manual coding methods challenges Shopify CEO Tobi Lütke’s assertion that “reflexive AI usage is now a baseline expectation” for developers.
- Switching back to vim (a text editor) reduces AI interference in the coding process, viewing programming not as a “boring part” to automate but as a craft to preserve and enjoy.
- This perspective creates a distinction between using AI to “automate the boring parts” versus preserving the core creative and intellectual work of programming.
The Rocky Balboa principle: The Rocky movies illustrate why manual coding remains valuable despite AI’s efficiency advantages.
- Just as Rocky returned to an “old gym” for fundamental training rather than using modern equipment, programmers benefit from occasionally foregoing AI assistance to maintain core skills.
- This approach prioritizes cognitive fitness and skill development over short-term productivity gains.
Why this matters: The debate reveals a tension between optimization-focused approaches to software development and the belief that coding’s challenges directly contribute to engineering skill development.
- If programming becomes predominantly AI-assisted, developers may risk atrophying problem-solving abilities that remain essential for tackling novel or complex challenges.
- The discussion extends beyond programming to broader questions about how technology shapes skill acquisition and expertise in knowledge work.
The value of cognitive struggle: Deliberately working through difficult problems builds neural pathways and expertise that can’t be developed through AI-assisted shortcuts.
- Overcoming coding challenges independently leads to deeper understanding and more robust mental models than accepting AI-generated solutions.
- This perspective frames struggle as valuable rather than inefficient, particularly for long-term skill development.
Finding the balance: Intentional AI collaboration beats reflexive dependence.
- AI tools are positioned as most valuable for automating genuinely tedious or repetitive aspects of coding while preserving human engagement with the creative, problem-solving components.
- The key distinction is between thoughtful AI integration versus defaulting to AI for all coding tasks regardless of their educational or craft value.
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