February 3, 2026
Brain vs Bot: Round One
I miss thinking hard
Coders split: AI shortcuts vs the joy of hard thinking
TLDR: A developer says AI tools make coding faster but drain the satisfaction of deep problem‑solving. Comments split between warnings about hidden debt, a blunt “just don’t use it,” and a hybrid camp that plans first then lets AI assist—spotlighting a bigger craft‑versus‑convenience debate.
The post “I miss thinking hard” hit a nerve: a coder laments that AI-assisted vibe coding turns ideas into apps fast but starves the inner Thinker who loves wrestling with tough puzzles. The thread reads like group therapy with sparring gloves on—half confession, half courtroom drama.
Hardliners came swinging. Besibeta warned the “70% solution” from AI creates “massive hidden technical debt,” meaning you skip understanding the edges and pay later with bugs and rewrites. Bigstrat2003 went full tough love: just don’t use AI, it’s your choice. Meanwhile joshpicky mourned the simple joy of typing code, saying all this Agent stuff (AI helpers that write code) makes him feel left behind.
The counterpunch: topspin insisted they use LLMs (large language models—chatty AIs) and still think hard about design, risk, and trade-offs. R‑johnv pitched a clever twist—draft your plan first, then let the agent try, and compare. It’s like turning AI into your rival in a mental chess match.
Jokes and memes flew: the “70% solution” became “70% debt,” someone quipped “vibe coding, no vibes for bugs,” another asked if their brain installed “lazy mode.” Whatever side you pick, discussion is a debate about speed, craft, and joy of struggle.
Key Points
- •The author defines “thinking hard” as prolonged engagement with a difficult, specific problem over days.
- •They describe two personal traits: the Builder (shipping and utility) and the Thinker (deep problem-solving).
- •University physics experience is used to illustrate persistence in tackling very hard problems and different student approaches.
- •Software engineering previously balanced building and deep thinking, contributing to the author’s growth.
- •AI-driven “vibe coding” now reduces opportunities for deep thinking, leading to reliance on quick, “close enough” solutions and less perceived growth.