NextGen AI: Pionierarbeit mit generativer KI
Neue Potenziale in der Technik erschließen: KI-Einblicke und Branchentrends
Why Prompting Hits a Wall
You can engineer around the composition problem. Until you can't. In Part 1, we explained the 0.95^10 problem — why ...
The Four Layers of Reliable Multi-Agent AI
What two years and 350,000 traces taught us about making agents actually work. In Part 1, we introduced the 0.95^10 ...
Why Multi-Agent AI Fails: The 0.95^10 Problem
The composition crisis nobody talks about — and why bigger models won't solve it. Every AI lab is racing to ...
From LLMs to SLMs: How Modular Agents Cut Cost, Latency and Risk
NVIDIA’s new paper validates a core CAA idea: use small, specialist models inside a deterministic controller. Here’s what that means for pilots, procurement, and ...
How Confluent’s Streaming Agents enables Real-Time Learning AI
Event streams as short-term memory, Flink as deterministic orchestrator — a pragmatic pattern that maps straight onto the CAA blueprint. Confluent’s Streaming Agents ...
MIT NANDA „GenAI Divide“ Validates Operational Knowledge Decay
MIT NANDA Project confirms in it's "The GenAI Divide - State of AI in Business 2025" report what enterprise teams have felt for months: ...
The Pragmatic Engineer Survey Exposes Failure of First Wave AI
The Pragmatic Engineer survey, their largest developer survey with ≈3,000 engineers, doesn’t just list tool likes and dislikes. It exposes the real failure of ...
Why AI Still Fails in Production: Our BSFZ-Certified Approach
After a decade managing technical relationships with BMW Group, Audi AG, and other German industrial giants, our founder witnessed the same costly pattern repeating ...
Trade Republic LLMOps Confirms the 10 Principles of CAA
Last week we published our 10 Principles of Cognitive Agentic Architecture (CAA), the rules we follow when turning AI demos into production systems. A ...









