All relatively simple problems can readily be [[solved, coded]] by LLMs.
All problems that are complex but verifiable in one systematic way [[have, will]] fall to LLMs.
Only the problems that are too [[small, niche, complex]] to be easily verified will be solved by humans (with the help from LLMs)
"Any fool can write code that a computer can understand. Good programmers **write code that humans can understand"
Martin Fowler
[[update: since summer 2026, agents needs way less hand-holding than described below]]
AGENTS.mdpreferences ("don't rebuild the project, as i'm already doing it")
have a clear mental model of what feature i want to build.
i know that the size / scope / complexity is manageable for the LLM
start dictating the new feature I want to work on. Dictating allows me to give more information and thus provide more context to the LLM. I've noticed that the LLMs are super good at sorting out my brain dump, and I get better results than typing it myself.
terminate my initial message with: "Before you do that, ask me clarifying questions. Number your questions (1, 2, 3) and label answer options (a, b, c, ...). Keywords are fine. " --> same as "Plan mode"
rinse and repeat until questions are trivial
type "go", let the LLM cook for a few minutes
review significant files (e.g. backend), skim medium important files (ts, html), skip a few (css)
run some tests
not using: - on stuff that i don't know about (LLM will run me in circles) - biggest models (latest Opus), unless nasty bug - Claude code: i like the concept, but prefer to be in an IDE where i can follow the process more - parallel agents (too much brute force to me) - vibe coding (:= not look at the code), unless for tiny 1-shot projects