The Rise of Whatever

LLMs for Coding: Crap or Useful Tool?

• One camp says the article attacks a straw‑man from “six months ago”: modern LLMs plus agents, type‑strict compilers, and tools (e.g. language‑server style systems) drastically reduce hallucinated APIs and can iterate until code compiles.
• Critics counter that “compiles” ≠ “correct”: LLMs still make subtle framework mistakes, invent wrong patterns, or produce fragile workarounds that tools can’t catch.
• Supporters report real productivity gains for boilerplate, serializers, refactors, CI YAML, and translations between tech stacks—provided a skilled developer reviews and guides them.
• Disagreement persists over trendlines: some argue recent models are dramatically better; others claim model quality is flat and only tooling improved.

AI, Learning, and the Death (or Not) of Craft

• Strong concern that beginners will skip the painful but necessary practice of coding, drawing, music, or language and instead lean on “Whatever” output—eroding deep skills and critical thinking.
• Counterpoint: every technology (tractors, cameras, spell‑checkers, IDEs) made tasks easier without eliminating serious practitioners; tools raise the floor, not necessarily lower the ceiling.
• Distinct worry: LLMs are opaque, inherently lossy, and trained on unconsented human work; some call this “theft” and argue AI should be treated as a shared asset. Others say it’s just mechanized cultural imitation in a capitalist system that already rewards owners over creators.

Jobs, Automation, and Economic Anxiety

• Many see LLMs as accelerating white‑collar automation after decades of blue‑collar offshoring, reviving fears of “bullshit jobs” or mass unemployability.
• Proposals range from “adapt or move” to basic income or stronger social safety nets; several examples (coal miners, rural decline, musicians) are used to argue current systems already fail displaced workers.

Crypto, Payments, and “Whatever Money”

• Some argue distributed ledgers have produced only speculation and crime, unlike smartphones, and remain a casino.
• Others insist there are real uses: DeFi, on‑chain liquidity, cross‑border remittances for the unbanked, censorship‑resistant transfers (e.g. in poor or sanctioned countries).
• Payment processors (PayPal, Stripe) are criticized for opaque bans, AI‑driven risk flags, and blanket hostility to adult content; debate over whether this is prudishness, chargeback economics, or both.

“Whatever” Culture and Content Slop

• The essay’s “Whatever” framing resonates: ad‑driven platforms rewarding engagement over quality, AI‑written emails and games, and “content creator” identity all feel like beige sludge optimized for metrics.
• Some commenters see this as a broader critique of capitalism and financialization: line‑go‑up incentives producing crypto hype, AI hype, and low‑grade content.
• Others think the author overgeneralizes, ignores real AI use cases, and indulges in curmudgeonly tone, yet they still value the call to “do things, make things” for their own sake.