Writing content for AI: How to find topics that models pick up
AI models learn from billions of texts – but not all content gets picked up. Learn the mechanics behind 'AI discoverable content' and how to create content that lands in ChatGPT, Claude & Co.
Not all content is learned by AI
AI models like GPT-4, Claude or Gemini are fed with training data – from blogs, news, forums, Wikipedia, scientific papers and more.
But far from everything ends up in training. The question is:
- →Which content is preferred?
- →How does AI recognize 'good' content?
- →What can you do to increase the chances?
'Writing content for AI means: Write for humans, but think about machines.'
How AI models learn
To understand which content gets picked up, you need to understand how AI models are trained.
In simplified terms:
- 1.
Data collection (crawling)
AI companies collect texts from publicly accessible sources: blogs, news, Reddit, Wikipedia, industry publications.
- 2.
Filtering
Not everything is used. Spam, low-quality content, duplicate content are filtered out.
- 3.
Training
The model learns patterns, relationships and contexts from the remaining data.
- 4.
Inference
Later, when someone asks a question, the model generates answers based on what it learned.
Your goal: Ensure your content is collected in step 1 and not filtered out in step 2.
What AI models prefer
AI models have 'preferences' – not consciously, but through how training data is selected.
High authority
Content from trusted domains has a higher probability of making it into training.
Structured content
Texts with clear headings, lists, and paragraphs are easier to process.
Originality
Unique content is preferred. Copies or spam are filtered out.
Frequent updates
Sites that regularly publish new, relevant content are crawled more often.
Context & depth
Superficial content is ignored. AI learns from texts that provide real value.
The 7 principles of AI discoverable content
If you want your content to land in AI models, follow these principles:
1. Write for understanding, not for keywords
SEO-optimized content with keyword stuffing doesn't work for AI. Instead: explain concepts clearly and thoroughly.
Example: Instead of 'Best CRM Software CRM Tool CRM Solution' → 'A CRM (Customer Relationship Management) system helps companies manage customer relationships.'
2. Use semantic relevance
AI models understand context. Write about related topics, use synonyms, explain connections.
Example: When writing about 'remote work', also mention 'asynchronous communication', 'timezone management', 'virtual teams'.
3. Answer specific questions
AI models learn from question-answer pairs. Structure content to answer questions.
Example: 'How does X work?', 'What's the difference between Y and Z?', 'When should I use A?'
4. Offer depth, not breadth
A detailed article (2,000+ words) on a specific topic is more valuable than 10 superficial 300-word posts.
Example: 'Complete guide to API integration' > '5 tips for APIs'
5. Use structured formats
AI loves structure: H2/H3 headings, lists, tables, FAQs.
Tip: Create FAQ sections at the end of each article.
6. Be current and relevant
Newer data has higher chances of making it into new model updates. Update old articles regularly.
Example: 'Guide to X (Updated 2024)' signals freshness.
7. Build authority
Content from high-authority domains is preferred. Get backlinks, be cited by trusted sites.
Strategy: Guest posts on established blogs, PR in tech media.
Topics AI models prefer
Not all topics are equal. Some are included in training data more often than others.
Preferred topics:
- ✓Explanations & How-Tos
- ✓Comparisons & decision aids
- ✓Best practices & strategies
- ✓Case studies & examples
Less preferred:
- ✗Clickbait & sensationalism
- ✗Duplicate content (copy-paste)
- ✗Advertising without value
Content formats that work
Certain formats have higher chances of being picked up by AI:
Ultimate Guides
2,000+ words, in-depth, comprehensive
Comparison Articles
X vs. Y, feature tables, use case mapping
Case Studies
Problem → Solution → Result
FAQ Pages
Clear questions, clear answers
Tutorials & How-Tos
Step-by-step instructions
What you should NOT do
Some strategies that work for classic SEO harm your AI visibility:
- ✗
Keyword stuffing
AI detects unnatural repetitions and filters such content out.
- ✗
Thin content
300-word articles without real value are ignored.
- ✗
Duplicate content
Copy-paste from other sites gets filtered out.
- ✗
Clickbait headlines
'You won't believe what happened next' doesn't work for AI training.
How art8 Rise provides content ideas
art8 Rise analyzes your current AI visibility and gives you concrete content recommendations:
- →'Write about these topics to become visible in context X'
- →'Use these keywords for better semantic relevance'
- →'Position yourself as an expert in topic Y'
Instead of guessing what works, Rise shows you data-driven which content boosts your AI visibility.
Point of Truth
Writing content for AI isn't rocket science – but it requires a shift in thinking.
Instead of optimizing for search engine algorithms, you write for AI models that understand context, value depth and recognize quality.
The good news: Good content for humans is also good content for AI.
Check how visible your brand is in AI contexts
Use the tool for a reality check – and the methodology as reference.
Optional: Look up term in glossary