Mastering aircraft manual LLM output is officially the best way to force generative AI models to produce highly readable, strictly controlled technical text.
Andrej Karpathy, a founding member of OpenAI and former Director of AI at Tesla, recently shared a framework for improving how we read model output. He advocates moving away from standard prose and forcing models into rigid constraints, likening the ideal text to an aircraft manual. Just as marketers are learning to mitigate AI decision making marketing risks in their pipelines, software developers must strictly control how their AI models generate code and technical explanations.
If you want to stop language models from generating fluffy, verbose text, here are 5 proven ways to achieve aircraft manual LLM output.
1. The Core of Aircraft Manual LLM Output
The foundation of this strictly controlled framework relies on a rigid standard known as ASD-STE100, commonly known as Simplified Technical English (STE).
Karpathy noted that massive language models already know this aerospace standard intimately. STE places heavy constraints on clean writing style, stripping away unnecessary adjectives and forcing single-meaning vocabulary. When you prompt a model to write using STE constraints, it produces text that is significantly more readable and easier to parse for complex engineering tasks.
2. Utilizing Simplified Technical English (STE)
ASD-STE100 is maintained by the Aerospace, Security and Defence Industries Association of Europe (ASD).
Because the standard is quite stringent—featuring a strict dictionary of about 900 approved words—Karpathy occasionally softens his prompt to ask for “80% of the way to ASD-STE100.” While standard marketing copy requires creative flair, generating aircraft manual LLM output is perfect for technical documentation. The core principles—short sentences, one topic per sentence, and active voice—remove the dangerous ambiguity that plagues standard AI summaries.
3. Rendering Interactive HTML Pages
Beyond generating aircraft manual LLM output via text, Karpathy heavily advocates for asking language models to output interactive web pages.
Instead of accepting standard Markdown formats, Karpathy recommends asking for output directly in HTML. This aligns with recent insights from Anthropic’s Claude Code team, who explicitly utilize HTML because it allows developers to interact with the data directly inside a browser. Interactive HTML turns a static text response into a highly functional software artifact. To understand standard markup languages, you can review documentation on HTML.
4. Using Diagrams for Cognitive Processing
Another powerful alternative to standard text is forcing the model to generate visual architectures.
Rather than reading through dense paragraphs, Karpathy suggests simply asking the model for a diagram. Generating diagrams makes complex systems “a lot easier to process, parse, and understand.” By combining strict aircraft manual LLM output with flowcharts and architectural diagrams, you drastically reduce the cognitive load required to verify if the AI’s underlying logic is actually correct.
5. Generating Custom Explainer Videos
The format Karpathy is “most bullish on” pushes far beyond simple text or HTML: custom explainer videos.
Karpathy’s current workflow involves prompting the AI for a “3b1b style” explainer (a direct reference to the popular 3Blue1Brown math visualization videos). He instructs the model to pair the visuals with an ElevenLabs API key for automated voice narration. If you do not have an API key, you can easily ask the model to find free alternatives that run locally on your own computer. As Karpathy enthusiastically noted, “This is actually starting to work!”
6. Moving from Writing to Human Oversight
As we generate more aircraft manual LLM output, the nature of our daily work is fundamentally changing.
Karpathy closed his insights by urging developers to aggressively ask models for “large, custom, discardable software artifacts” that would have never made financial sense to create manually before. Because the AI is doing the raw legwork, human responsibilities will rapidly rise up the abstraction ladder into pure oversight and understanding. You can explore the official standard documentation at the ASD-STE100 web portal.
Frequently Asked Questions
What is Simplified Technical English?
Simplified Technical English (ASD-STE100) is a strict set of writing rules originally designed for the aerospace industry to eliminate ambiguity. It uses short sentences and a limited dictionary of approximately 900 approved words.
Why did Andrej Karpathy suggest ASD-STE100?
Andrej Karpathy suggested this standard because its heavy constraints on vocabulary and sentence structure force language models to produce incredibly clean, highly readable text without unnecessary conversational fluff.
Can AI models generate videos and HTML?
Yes. Alongside controlled English, aircraft manual LLM output workflows prompt LLMs to generate interactive HTML pages, visual diagrams, and even custom 3Blue1Brown-style explainer videos with automated text-to-speech narration.
