GoKawiilWhy AI still struggles to replace skilled writers, even as it masters code
An opinion piece argues that while large language models have rapidly improved at generating code, their prose remains stuck in an 'uncanny valley' of clichéd, robotic language lacking real insight. The author contends AI labs have already pushed hard to improve writing quality but hit a wall, unlike image, voice, and video models that scaled quickly with more compute and parameters. The piece frames writing as a 'wicked problem' with no clear definition or objectively correct solution, making it resistant to the kind of brute-force scaling that worked for other AI capabilities.
GoKawiil's interpretation of the reporting above, not reported fact.
As companies push aggressive AI productivity mandates onto engineers, this argument suggests a meaningful skills divide may be forming: technical roles face rapid disruption while creative and interpretive writing may remain a durable human niche. It also raises a broader question about which cognitive tasks are fundamentally scalable through more compute versus those requiring irreducible human judgment and lived experience.
- Coding sees rapid AI-driven productivity gains, while AI-generated prose remains widely seen as formulaic and hollow.
- Image, voice, and video AI models scaled quickly with compute, but text quality for expressive writing has plateaued.
- Writing is framed as a 'wicked problem' lacking clear rules or solutions, making it harder for AI to fully automate.
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Published there as: “The safest job from AI may be writing”
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