Blog

Articles on AI, agentic systems, and energy-efficient sovereign architectures.

Think Alien, Act Human: The AlphaGo Zero Lesson for Agentic Architectures

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We train agents to reason the way people reason, then wonder why they are only as good as people. AlphaGo Zero suggests the ceiling is one we built ourselves, and points at exactly where we should keep it.

Aug 22, 2026
Jan Scholtes

There Is No Data Like Strange Data: Rethinking AI Training for Agents

text-to-action

In 1993, the golden rule of AI was ‘there is no data like more data.’ Building agentic architectures today requires the opposite instinct: stop chasing volume, start chasing the unexpected.

Aug 15, 2026
Jan Scholtes

From Triple to Quintuple: Why the Best Training Data Includes the Worst Decision You Could Have Made

text-to-action
fundamentals

The observation-action-consequence record has been the backbone of agent training data for decades. Two missing dimensions, the reasoning behind the action and the worst alternative, are what turn a logbook entry into a model that can actually think.

Aug 8, 2026
Jan Scholtes

What It Takes to Build a Sovereign AI Agent for Your Organization

sovereignty-edge
enterprise-strategy

From a customer service agent to a caseworker assistant helping citizens navigate bureaucracy, a practical, step-by-step guide to building an agentic AI system your organization actually owns, on infrastructure it actually controls.

Aug 1, 2026
Jan Scholtes

Shrinking the Giant: How Pruning, Quantization, and Distillation Make LLMs Small, Cheap, and Safer

fundamentals
efficiency

Training a custom GPT-4-class model now costs an estimated 2-3 million dollars in compute alone. Here’s how pruning, quantization, and distillation take that same capability and put it on hardware you own, while incidentally closing off a whole class of attacks.

Jul 25, 2026
Jan Scholtes

From the Next Farmhand to the Next AI Agent: Turning Generational Knowledge Into Training Data

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For 150 years, farmers wrote logbooks so the next person on the job would know what to do. That same text, written for a human successor, turns out to be exactly what an AI agent needs to learn the job instead.

Jul 18, 2026
Jan Scholtes

Why NLP Finally Works: What Transformers Got Right That Fifty Years of Grammars, Statistics, and RNNs Didn’t

fundamentals

From hand-written grammars to statistical models to LSTMs, each generation of NLP solved one problem and hit a new wall. Transformers are the first architecture to take on every layer of language at once, and derive it all from data.

Jul 11, 2026
Jan Scholtes

David vs. Goliath: A Fine-Tuned 8B Model Nearly Matches a Trillion-Parameter Giant, On One Task

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Recent research shows a small, locally-run model can get within a few points of a frontier foundation model on a specific job. The reason isn’t magic, it’s specialization.

Jul 4, 2026
Jan Scholtes

How AI Will Revolutionize Education, And Where It Genuinely Shouldn’t

education

24/7 tutors, instant readers generated from slides, Socratic dialogues on demand, generative AI is already reshaping higher education. But the same technology has triggered a cheating arms race, and the honest picture is more nuanced than either the hype or the panic suggests.

Jun 27, 2026
Jan Scholtes

Governing the Autonomous Organization: Who’s Accountable When AI Decides?

governance

AI finally works. Now comes the harder question: how do you govern an organization where AI analyzes, advises, and acts, while final accountability stays with a human?

Jun 20, 2026
Jan Scholtes

The Institutional Moat: Why CTOs Can’t Stop at Prompts and Skill Files

enterprise-strategy

Prompts and Markdown skill files on top of Claude, GPT, or Gemini are a starting point, not a strategy. What CTOs and CIOs actually need to build, and why the EU has an extra reason not to wait.

Jun 13, 2026
Jan Scholtes

Why Europe Needs Its Own AI Models on Its Own AI Infrastructure

sovereignty-edge

What Stanford’s 2026 AI Index reveals about the five dimensions of AI sovereignty, and why running models on domestic, edge-capable infrastructure isn’t a luxury for Europe, it’s a competitive necessity.

Jun 6, 2026
Jan Scholtes

From Text to Action: Turning NLP Pipelines into Agentic Workflows

text-to-action

How raw, unstructured text becomes the training data behind an agent’s memory, tools, reasoning, and guardrails, and why that conversion is where the real competitive advantage lives.

May 30, 2026
Jan Scholtes

What Is an AI Agent? From Chatbot to Autonomous System

fundamentals

A grounded introduction to agentic AI: what changes when a language model gains memory, tools, and the ability to act, and why that shift matters.

May 23, 2026
Jan Scholtes

Adversarial Attacks: How a Few Invisible Pixels or One Swapped Word Can Fool an AI

fundamentals
efficiency

Adversarial examples exploit the exact mathematical boundaries a model draws to make decisions. Here’s what these attacks actually look like in images and text, and the concrete defenses that address each one.

May 16, 2026
Jan Scholtes

Why You Can’t Fine-Tune, Train, or Distill a Model Without XAI

fundamentals
governance

The moment you start fine-tuning, training, or distilling your own models, you inherit full responsibility for how they reason, not just what they output. Explainable AI is what lets you actually verify that.

May 9, 2026
Jan Scholtes

Bias Analysis in Practice: How Do You Actually Test an Algorithm for Discrimination?

governance

The Dutch government’s Algorithm Framework requires a bias analysis, a justification test, and an ethical desirability test for every algorithm that treats people. Here’s how to actually carry that out, with tools, real cases, and the underlying science.

May 2, 2026
Jan Scholtes
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