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Practical insights on AI, software, and digital transformation from Amsterdam.
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Alternatives to a fractional CTO: what Dutch companies can do instead
Interim CTO, full-time hire, technical advisor, a promoted tech lead or an outside team — what each option costs, what it owns, and when it beats a fractional CTO.
AI Application Development from Prototype to Production
A practical guide to AI application development covering design, prototyping, evaluation pipelines, deployment, and monitoring for engineering leaders.
MLOps Consulting Guide for Reliable ML Pipelines
Discover how MLOps consulting builds reproducible pipelines, robust monitoring, and delivers ROI. Learn why your enterprise needs expert MLOps consulting today.
Agentic AI Workflows: A Practical Guide for 2026
Learn how agentic AI workflows actually work in production, from core concepts and orchestration patterns to safety, governance, and integration.
Scaling with Low-Code: Where Dutch Companies Stumble
The question Dutch companies keep asking is the wrong one. “Can lowcode scale?” implies that scaling is mainly a technical limitation — that somewhere arou
Cloud vendor lock-in: when switching costs become a business risk
A practical guide to recognising cloud lock-in and reducing switching risk without giving up the benefits of managed infrastructure.
Post-Odido Hack: Building Secure Customer-Data Pipelines
The announcement from the Dutch Data Protection Authority on 16 April 2026 marks a turning point in how Dutch and European companies need to approach custo
Infrastructure integration challenges for Dutch supply chains
Why fragmented systems create operational drag in Dutch supply chains, and where focused integration work creates the most value.
Cost-benefit analysis: building AI workflow software in-house versus outsourcing
A practical framework for comparing internal teams, external partners, and hybrid approaches to AI workflow software.
Trade-offs in Scaling Machine-Learning Models: On-Premises vs. Hybrid Cloud Architectures
Machinelearning models that perform brilliantly during development often collapse under production load. The infrastructure decision you make today — onpre
Why most AI proof-of-concepts fail in production: lessons from 12 Dutch implementations
Why promising AI pilots fail to reach production, and the infrastructure, data, workflow, and monitoring checks that prevent it.