The LLM Critics Are Right. I Use LLMs Anyway
theocharis.dev
July 16, 2026
18 min read
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53/100
Summary
Many users acknowledge the criticisms of large language models (LLMs) yet continue to utilize them extensively. The Local-First Conf in Berlin showcased discussions on the complexities and dissonance surrounding LLM usage, with notable speakers like Armin Ronacher contributing to the conversation.
Key Takeaways
- Many engineers, including those building tools for LLMs, are overwhelmed by the influx of low-quality contributions from LLMs, leading them to auto-close most pull requests and issues.
- The author acknowledges the valid criticisms of LLMs, including concerns about copyright, environmental impact, and ethical issues, while still choosing to use them.
- There is a prevalent sense of dissonance among users and critics of LLMs, where individuals express skepticism about LLMs while simultaneously utilizing them in their work.
- Trust in contributions to open-source projects has diminished due to the ease with which LLMs can generate submissions, making it harder to filter out low-quality inputs.
Community Sentiment
Positives
- LLMs are undeniably speeding up learning and familiarization with new concepts, making users feel more informed and capable in their fields.
- There's a genuine excitement around how LLMs can enrich thinking — the potential for sharper ideas and faster output is hard to ignore.
- Some users find LLMs not just a crutch, but a way to train and strengthen their skills, turning them into better developers in the long run.
Concerns
- Critics worry that heavy reliance on LLMs might lead to intellectual atrophy, questioning if our critical thinking will suffer in the long run.
- There's skepticism about the actual productivity gains from using LLMs, with some arguing that developers overestimate their benefits.
- Concerns are raised about the environmental and financial costs of AI, especially when users spend exorbitant amounts on tokens without clear necessity.
