I'm going back to writing code by hand

Scope of AI in Coding: Features vs. Architecture

• Many agree with the article’s core claim: current LLMs are good at implementing features but poor at making or evolving sound architecture.
• Common pattern: if you let agents “vibe-code” without strong constraints, you get god objects, tangled state, and hidden dependencies.
• Several argue architecture must be designed by a human first (interfaces, ownership, message types), then given to AI as a spec; AI should mostly fill in functions and boilerplate.

Code Quality, Testing, and Refactoring

• Strong emphasis that AI-generated code must be reviewed like a junior’s work; failure to read the output is seen as the real problem.
• Others counter that reviewing all AI output at scale is unrealistic, so test coverage (unit, integration, e2e) becomes the main safety net.
• Multiple comments report AI being particularly bad at large refactors: it tends to add code, miss nuances, and create subtle inconsistencies even under lint rules.
• Desire for a “verification layer” or better tooling to automatically check AI’s work beyond conventional tests.

Workflows and “Comprehension Debt”

• Many propose rules: only let AI write code you could write yourself, and don’t ship AI code you don’t understand; otherwise you accrue “comprehension/cognitive debt” that later becomes unmanageable.
• Some find AI most useful for: scaffolding, codemods, tests, exploratory design, or boring boilerplate (CRUD, forms), while keeping humans in charge of core logic and abstractions.
• Others experiment with strict modularization, small-scoped tasks, plan-first modes, and detailed skills/spec files to keep agents from derailing.

Productivity, Enjoyment, and Management Pressure

• Mixed experiences on productivity: some claim 50–100% coding time savings; others say perceived speed hides slower real progress and massive tech debt.
• A recurring concern: managers now expect “AI-speed” delivery and may push vibe-coded features, offloading cleanup onto developers.
• Several devs say they’re scaling back agentic coding for personal projects because it’s less enjoyable and produces sloppier code long-term.

Meta: Title, Authenticity, and Hype

• Many criticize the post title as clickbait, noting the author still uses AI for implementation while only “doing design by hand.”
• Some suspect the blog post itself might be LLM-written, and more broadly see the article as part of a broader, overhyped AI-marketing narrative.