AI Coding Hype Is Starting to Crack

• Intro
  • “AI skepticism might be one of the most valuable developer skills right now, but only if it does not turn into stubbornness.”
• Section 1: The bad version of skepticism
  • Developers who refuse to try the tools.
  • Developers who dismiss everything as hype.
  • Why this makes you look rigid when companies are clearly moving toward AI-assisted workflows.
• Section 2: The bad version of AI optimism
  • Developers who accept massive AI-generated diffs without understanding them.
  • Teams that mistake more code for more progress.
  • Managers who only measure output volume, not quality.
• Section 3: The useful middle
  • Use AI for speed.
  • Use your own knowledge for judgment.
  • Ask: “Where would this fail in production?”
• Section 4: Where developers should focus
  • Security
  • Architecture
  • Performance
  • Data correctness
  • Maintainability
  • Product-specific context
• Section 5: The moving target
  • AI strengths will keep changing.
  • Your job is to keep re-evaluating what to trust, what to verify, and what to delegate.

Links

• Exclusive: Meta to start capturing employee mouse movements, keystrokes for AI training data | Reuters

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