Some things just take time

Speed, Direction, and “Friction”

• Many argue that speed is only useful if you’re heading in the right direction; otherwise you just get lost faster.
• Others counter that speed makes it cheaper to be wrong: if course-correction is easy and judgment is good, moving fast lets you explore more options.
• Several people say old “friction” (time/effort to code or ship) forced better thinking; AI removes that friction and tempts people into shallow, poorly considered work.
• Metaphors about jars, rocks, sand, and even fish are debated; some see them as helpful reframing, others as empty “wise-sounding” talk.

LLMs, Coding, and “Vibe Slop”

• Strong concern that devs are accepting LLM code with little scrutiny: code “works” superficially but root causes and design are ignored.
• Multiple commenters report that AI can quickly generate PoCs, boilerplate, tests, and one-off scripts, but still can’t replace deep domain understanding, product vision, or fun/game design.
• Others share frustration: long prompts, broken code, and more debugging than writing it themselves. Model quality and usage mode (agent vs chat) matter a lot.
• Some say AI accelerates being wrong and getting stuck in “doom loops” of bad assumptions. Good results require tight scoping, specs in context, restarts, and strong human steering.
• There’s a recurring pattern: AI feels like a productivity high, but may not actually improve long-run output or quality.

Time, Value, and Status

• Disagreement over whether luxury goods are valued for “embedded time” or just as status symbols.
• Several distinguish between market value and personal/emotional value (e.g., a grandmother’s hand‑knit sweater).
• Some broaden the idea: value often reflects how many people, skills, and industries a thing passes through over time.

Work, Productivity, and Capitalism

• Commenters note that productivity gains historically haven’t translated into more leisure for workers; instead they fuel layoffs, quotas, and burnout.
• Tech workers describe coding becoming “sweatshop-like,” with AI used to justify higher expectations rather than better work.
• “Productivity” is seen by some as a weaponized, fuzzy concept used to rationalize squeezing labor.

Trees, Time, and Open Source

• The tree analogy (you can’t fake a 50‑year oak) sparks nitpicking but broadly resonates: trust, community, and mature OSS projects need years.
• Some open‑source maintainers describe decade‑long efforts, slow compounding improvements, and the difficulty of sustaining projects once they gain users.