Practical perspectives on enterprise AI — no hype, no fluff. What actually works in production environments.
The model is the smallest part. New research identifies the agent runtime as the primary source of hidden technical debt — and the real reason enterprise AI fails quietly in production.
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.
Research and writing in progress — coming over the next quarter.
Every vendor has GPT-5. The real competitive advantage in enterprise AI isn't the model — it's your data quality, governance framework, and ability to deploy responsibly at scale.
The EU AI Act is in force. Most guidance you'll find is written by lawyers for lawyers. This is a ground-level walkthrough for technical leaders.
Last-click attribution is broken. It systematically rewards the wrong channels and misdirects marketing budgets.
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.