Published Articles
AI Workflows vs AI Agents: Where to Set the Dial
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.
5 Workflow Patterns That Solve 95% of Enterprise AI Problems
Prompt chains, routing, parallelisation, orchestrator-subagent and evaluator loops. The gap between one LLM call and a full agent is where 95% of production value lives - and most teams jump straight past it.
When You Genuinely Need an Agent: A Production Readiness Checklist
The 12 questions to answer before granting autonomous decision-making to any system.
The Agentic CLV, Part 1: From Metric to Live Signal
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 Modelling Stack - Real-Time CLV in Production
The three levels of CLV sophistication, what changes when predictions must serve in milliseconds, and the MLOps realities of always-on scoring.
The Operating Model - Structuring Around Customer Trajectories
Feeding CLV back into ad platforms, redesigning retention around the days-0-to-90 cliff, and the organisational shifts required.
Beyond last click: how to measure every marketing channel in 2026
Where each touchpoint sits in the customer journey, why no channel wins alone, the traps that make naive analysis mislead, and how online, offline and AI touchpoints can be measured together.
EU AI Act: A Practical Implementation Guide for CTOs
One obligation is already active and most organisations missed it. A non-generic guide to AI inventory, classification, the Betriebsrat dimension, and what December 2027 means for your planning calendar.
Context Engineering: The Missing Piece in Enterprise Agentic AI
The 6-layer framework, context rot, and the maturity curve that separates AI demos from production deployments.
Building Production-Ready Enterprise AI Agents
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 - each a distinct discipline, together the difference between Level 2 and Level 3.