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The Operating System Manual for AI-First Companies

Frameworks, guides, and research for modern AI automation. From practitioners for practitioners.

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Knowledge Graphs vs. Vector RAG: The Fundamental Difference

When graph methods beat classic RAG, when they do not, and what the benchmarks actually measure.

The 8 Fundamental Weaknesses of LLMs

Why ChatGPT, Claude and Co. are not production-ready on their own - and what you can do about it.

The Aprixity Thesis: 2026-2030

Our scientific forecast for the future of AI-First transformation. Why determinism and transaction velocity determine success.

MECE for LLMs: Structuring Principle for Precise AI Prompts

Learn how the MECE principle from consulting structures your LLM prompts and improves AI outputs.

The 5 Dimensions of a Complete AI System

A MECE framework for evaluating and planning AI architectures. What capabilities does a system need to be truly intelligent?

From Gut Feeling to Graph: How to Automate High-Touch Processes Without Losing the Human Element

A case study from Premium Real Estate. Why traditional automation fails with complex, relationship-intensive processes – and how a semantic Intelligence Layer solves this.

What is GraphRAG? The Hybrid Approach Explained

How GraphRAG connects knowledge graphs with RAG, where the advantage is measurable and where it is not.

MCP Explained: The Model Context Protocol for LLM Integration

MCP is the open standard for LLM-to-tool communication. How it works and why it matters.

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The Operating System Manual for AI-First Companies

Knowledge becomes valuable inside a process.