<antirez>
5 hours ago
- The author feels a responsibility to help less experienced programmers adapt to AI-driven changes in programming, based on their own foresight and experience.
- The key shift is that programmers should focus on controlling the ideas and design of software rather than reading code line-by-line, because LLMs handle local optimization well and generate large amounts of code.
- Reasons to prioritize ideas: LLMs produce verbose code, humans have limited time, and it's more efficient to evaluate design through prompts instead of scanning functions.
- The author's work on DwarfStar and comparison with other implementations shows that AI can help catch errors in complex domains like local inference, where hand-written code is often flawed.
- Resistance to AI may be ideological; rigorous engineering and testing are more valuable than manual code review, especially for domains like GPU kernels.
- Even for codebases like Redis, detailed code review is becoming less useful; instead, documenting design ideas in a DESIGN.md file would be more valuable for future modification.
- Young programmers should learn fundamentals (e.g., writing a small interpreter) but not waste time reviewing LLM-generated code for mundane tasks.
- The software world was already 'rotten' before AI, and AI offers opportunities to improve it, though the change is painful.