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Author claims LLMs can't be worse than human-written code

By PulseAugur Editorial · [1 sources] ·

The author argues that expectations for Large Language Models (LLMs) to produce perfect code are unrealistic, given the history of poorly written codebases created by human teams. They point to examples like the Team Fortress 2 codebase and the general state of app stores as evidence of human coding deficiencies. The piece suggests that LLMs may not be worse than existing human-generated code, and that the prevalence of shoddy code is a self-inflicted problem. AI

IMPACT Suggests that current LLMs may not significantly worsen the quality of code compared to existing human-generated software.

RANK_REASON Opinion piece discussing the capabilities and limitations of LLMs in coding, drawing parallels to historical human coding practices.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Author claims LLMs can't be worse than human-written code

How we ranked this

Signal score
2 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Commentary
Opinion piece discussing the capabilities and limitations of LLMs in coding, drawing parallels to historical human coding practices.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
opinion
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    We probably just expected too much out of LLMs, entire teams of well-trained teams can be capable of writing entire code bases of slop, why would we expect much

    We probably just expected too much out of LLMs, entire teams of well-trained teams can be capable of writing entire code bases of slop, why would we expect much better from anything we train, even if was magically deterministic? Just ask anybody who has worked on the team fortres…

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