Practical perspectives on enterprise AI - no hype, no fluff. What actually works in production environments.
CLV sits on slides and rarely shapes what happens on a Tuesday afternoon. Agentic AI is changing that - moving lifetime value from a lagging report to a live signal that autonomous systems consume and act on.
The three levels of CLV sophistication, what changes when predictions must serve in milliseconds, and the MLOps realities of always-on scoring.
Feeding CLV back into ad platforms, redesigning retention around the days-0-to-90 cliff, and the organisational shifts required.
The workflow-vs-agent choice is not binary. It is a dial - and most enterprises set it too far right. Cost, reliability, and EU AI Act oversight all favour the middle for most enterprise work.
One obligation is already active and most organisations missed it. A non-generic guide to AI inventory, classification, the Betriebsrat dimension, and what the August 2026 deadline means for your planning calendar.
The 6-layer framework, context rot, and the maturity curve that separates AI demos from production deployments.
Four architecture decisions separate agents that work in demos from agents that work reliably at scale. Memory layers, context compression, human oversight design, and multi-agent orchestration.
Understanding the framework is step one. We've deployed these architectures across DACH enterprises - from context layer design through to production-grade agentic systems. Let's talk about your specific environment.