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AI360: Large Language Model Optimization (LLMO) for Websites NEW
Training - Artificial Intelligence
The training shows web developers, technical product managers and IT managers how to structure websites so that AI-based search systems can capture content and use it in summaries. It covers macro context, multi-vector retrieval, knowledge graphs, structured data, semantic HTML and navigation concepts for AI- and SEO-compatible implementations. In addition, it demonstrates how modern frontends and API architectures remain indexable and usable for large language models.
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Agenda:
- Introduction to AI-powered search and AI Overviews
- Changes in search behavior due to AI answers
- Fundamentals of large language model optimization
- SEO techniques compared to AI search
- Macro context and macro semantics
- Entities, knowledge graphs and vector-based search
- Structuring content: question-and-answer blocks
- Alt texts, hidden gems signals and experience-based content
- Recommendations for AI-ready websites
- Practical project: optimizing a website section according to LLMO principles
Objectives:
Participants receive a practical introduction to optimizing websites for AI-based search systems. The AI360 Large Language Model Optimization (LLMO) for Websites training teaches key concepts such as macro context, semantic structuring and vector-based search. Participants learn how to prepare content so that it can be reliably captured, understood and cited by language models such as those from Google™ or OpenAI.Target audience:
The AI360 Large Language Model Optimization (LLMO) for Websites training is aimed at marketing and SEO teams, content managers, web editorial teams, product managers, as well as professionals who want to optimize content for search engines and AI-powered systems.Prerequisites:
To be able to follow the content and pace of the AI360 Large Language Model Optimization (LLMO) for Websites course well, basic knowledge of website content, SEO fundamentals or related topics is helpful. No technical prior knowledge in AI or programming is required.Description:
In the AI360 Large Language Model Optimization (LLMO) for Websites training, participants learn to design and implement websites so that they are optimally understood and utilized by modern AI-based search systems. The growing importance of AI-based search systems is fundamentally changing the visibility of websites: AI Overviews, ChatGPT responses and other automated systems no longer extract content solely via keywords, but via semantic relationships, entities and vector-based semantic spaces. This training shows how to structure content so that language models reliably recognize it and surface it in AI-generated summaries.Traditional SEO approaches that rely primarily on keywords and ranking factors are increasingly reaching their limits. This is precisely where the AI360 Large Language Model Optimization (LLMO) for Websites course comes in: it translates these new requirements into clearly understandable, technically traceable concepts and measures for web developers, technical product managers and IT managers. In addition to concepts such as macro context, multi-vector retrieval and knowledge graphs, it teaches practical methods for preparing content in a clear, concise and AI-oriented way.
For participants in the AI360 Large Language Model Optimization (LLMO) for Websites course, the key question is how to implement these requirements technically. The course explains the role of structured data, semantic HTML markup, and consistent URL and navigation concepts in enabling crawlers and LLM-based systems to capture content efficiently. It discusses how server-side rendering, frameworks, single-page applications and API-based websites affect indexability and semantic interpretability – and which patterns have proven effective in practice for ensuring AI and SEO compatibility despite modern frontend stacks.
Guaranteed implementation:
from 2 Attendees
Booking information:
Duration:
1 Day
Price:
550,00 € plus VAT.
(including lunch & drinks for in-person participation on-site)
Appointment selection:
No appointment available
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