Let's talk about LLMs

· ai coding · Source ↗

TLDR

  • Blog post applies Brooks’ No Silver Bullet framework to LLM coding, arguing code generation speed is a minor bottleneck compared to specification, design, review, and coordination.

Key Takeaways

  • Brooks’ math: unless accidental difficulty exceeds 90% of total effort, eliminating it entirely cannot yield a 10x productivity gain.
  • Brooks estimated 5/6 of software time is non-coding work; LLMs speeding up code generation leaves that majority untouched.
  • Rails scaffolding could auto-generate CRUD skeletons 20 years ago; the author sees LLM code generation as incremental, not revolutionary, for mature web app domains.
  • The real bottleneck is the review queue, stakeholder alignment, and iteration cycles, none of which LLMs currently accelerate proportionally.
  • The Tailscale CEO framing: Claude coding in 3 minutes vs. 30 still leaves reviewers spending 5 hours, and now they’re also annoyed at unreviewed output.

Hacker News Comment Review

  • Strongest pushback: commenters argued the article understates LLM scope, citing research, debugging, code review, and documentation as high-value offloads beyond raw code generation.
  • Commenters noted the article reads as academic and possibly confirmation-biased, with one pointing out the author apparently never described hands-on LLM coding experience to ground the claims.
  • A counter-thread suggested the essential/accidental difficulty ratio itself may have flipped for solo and small-team projects, where abundant libraries have largely solved inherent difficulty, making accidental difficulty the dominant remaining cost.

Notable Comments

  • @marcus_holmes: Flags absence of first-hand LLM coding experience in the post; calls it a meta-study that leans on 50-year-old frameworks without empirical grounding.
  • @furyofantares: Argues that for many solo-dev projects today, libraries have resolved inherent difficulty, inverting Brooks’ ratio and making the article’s core premise inapplicable.
  • @ilia-a: Points out LLMs accelerate analysis, review, and documentation without writing a line of code, a use case the article largely ignores.

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