The LLM Critics Are Right. I Use LLMs Anyway.

Core View

The ‘dissonance’ of LLM usage: many senior engineers agree with critics regarding ‘AI slop’ and ethical concerns but continue to use tools like Claude Code to amplify their own thinking.
Risks to OSS: The flood of low-effort LLM PRs erodes trust, leading some projects (e.g., Zig, Gentoo) to refuse AI-generated contributions.
Impact on Junior Engineers: LLMs automate mundane tasks, potentially removing the incentive for seniors to teach juniors and making it harder to gauge a junior’s actual effort and growth.
Geopolitical and Corporate Risk: Dependence on frontier models (e.g., Anthropic) exposes users to abrupt export controls and corporate pricing shifts; local-weights models are the primary hedge.
The ‘Amplification’ Principle: LLMs do not replace thinking; they amplify existing opinions, structures, and frameworks. High-quality output requires a human to put thought behind the prompt.
Practical Workflow Patterns: Using the ‘/grill-me’ technique (relentless interviewing) and ‘Ralph Wiggum loops’ (sub-agents ripping apart plans) to force human rigor and eliminate hallucinations.

Intuition Probing: Letting an LLM hallucinate an expected API or UX before showing it the real design to test if the design matches common human expectations.
The 3-Sentence Problem Statement: Forcing a concise ‘Problem’, ‘Shipping’, and ‘Not Shipping’ statement to ensure human readability and factual accuracy.
Expertise Requirement: LLMs are most dangerous when used in fields where the user cannot distinguish ‘good’ from ‘dogshit’; they are best used as learning tools when a clear feedback loop (e.g., code compiling) exists.

LLMs should be used to make fewer things of higher quality, rather than more things of lower quality.
Trust is the primary currency in the AI era; credibility is maintained by only publishing work the author would be willing to read aloud in front of an audience.
Local models are essential for independence from geopolitical instability and corporate volatility.

Topics: Tech, Career, Design
Tags: tech llm software-engineering