Charlie Stross – On the non-use of AI in my writing process

7 hours ago

The author does not use generative LLMs in their work or personal life, viewing them as toys sold by grifters rather than genuine tools.
The author has a long history of award-winning fiction published before OpenAI's founding, demonstrating no need for AI to write.
The author is a party to a class action lawsuit against Anthropic AI for pirating ebooks to train their LLMs.
LLMs are trained on stolen copyrighted material and their business model is compared to burglars reselling stolen goods.
The author argues LLMs are not sentient; they are stochastic word-association mechanisms lacking embodiment or self-model.
Some caveats: the author sees value in local, non-cloud AI tools for statistical analysis and editing support, but not as a substitute for human creativity.

The author chooses not to use LLMs for coding, not even tools like Claude Code or Cursor.
The author values the craft of programming, arguing that friction in code-writing encourages thoughtful design.
Using LLMs is seen as surrendering autonomy, creating dependency on corporate tools that may increase costs.

The author is highly enthusiastic about AI and its progress, including LLMs, self-driving cars, video generation models, and coding agents.
The author criticizes negative hype about AI creating a permanent underclass or a sudden transformative event, dismissing these as fear-mongering.
The author argues that AI's value will not be captured by frontier labs, as progress is driven by Moore's law and computing advancements, not specific companies.

The author uses a metaphor of a toaster falling in love to critique how we anthropomorphize AI tools like LLMs.
The software industry's insular bias leads to uncritical acceptance of AGI hype and the belief that algorithms can replace all human activities.
LLM vendors deliberately frame their products as human-like (e.g., 'personal assistant', 'Claude') to excuse errors and foster emotional bonds.

The author receives many LLM-generated emails pitching products and sees job applications with LLM-crafted resumes and portfolios.
While recognizing LLMs as useful tools, the author feels saddened by the impersonal nature of generated content, which obscures the individual behind it.
The author argues that sharing personal, imperfect work requires bravery, and that genuine human connection comes from revealing one's true self, not hiding behind polished, machine-generated outputs.

<antirez>5 days ago

The author loves writing software by hand but acknowledges that AI is irreversibly transforming programming, making manual coding no longer sensible for most projects.
In 2020, the author left their job to write a novel about AI and universal basic income, and opened a YouTube channel on AI in 2024, recognizing early the shift in programming.
Recent LLMs can complete large subtasks and medium projects alone with minimal guidance, as demonstrated by the author's examples: modding linenoise, fixing Redis tests, creating a BERT library in C, and reproducing Redis Streams changes.

The author chooses not to use LLMs for coding, not even tools like Claude Code or Cursor.
The author values the craft of programming, arguing that friction in code-writing encourages thoughtful design.
Using LLMs is seen as surrendering autonomy, creating dependency on corporate tools that may increase costs.

The author is highly enthusiastic about AI and its progress, including LLMs, self-driving cars, video generation models, and coding agents.
The author criticizes negative hype about AI creating a permanent underclass or a sudden transformative event, dismissing these as fear-mongering.
The author argues that AI's value will not be captured by frontier labs, as progress is driven by Moore's law and computing advancements, not specific companies.

The author uses a metaphor of a toaster falling in love to critique how we anthropomorphize AI tools like LLMs.
The software industry's insular bias leads to uncritical acceptance of AGI hype and the belief that algorithms can replace all human activities.
LLM vendors deliberately frame their products as human-like (e.g., 'personal assistant', 'Claude') to excuse errors and foster emotional bonds.

The author receives many LLM-generated emails pitching products and sees job applications with LLM-crafted resumes and portfolios.
While recognizing LLMs as useful tools, the author feels saddened by the impersonal nature of generated content, which obscures the individual behind it.
The author argues that sharing personal, imperfect work requires bravery, and that genuine human connection comes from revealing one's true self, not hiding behind polished, machine-generated outputs.

<antirez>5 days ago

The author loves writing software by hand but acknowledges that AI is irreversibly transforming programming, making manual coding no longer sensible for most projects.
In 2020, the author left their job to write a novel about AI and universal basic income, and opened a YouTube channel on AI in 2024, recognizing early the shift in programming.
Recent LLMs can complete large subtasks and medium projects alone with minimal guidance, as demonstrated by the author's examples: modding linenoise, fixing Redis tests, creating a BERT library in C, and reproducing Redis Streams changes.

Hasty Briefsbeta