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The 10 Most Common Mistakes in an AI Rollout

Krisztian Eyssen, Krisztian Eyssen

The 10 Most Common Mistakes in an AI Rollout

Every one of the ten comes with either a documented case or a survey number — and every one of them with a concrete countermove. The point is not naming the problem, it is what you do differently on Monday morning.

Beginner Business owner Explainer Business, Law & Security

Sep 13, 2026

Do Not Swap the Tool, Redesign the Workflow

Krisztian Eyssen, Krisztian Eyssen

Do Not Swap the Tool, Redesign the Workflow

Three quarters of the high-performing companies fundamentally redesigned their workflows; among the rest it was one quarter. A threefold gap — but that is self-reporting, not causal proof. The experimental measurements, on the other hand, all point the same way: the effect of AI comes through the way work is organised, not through the properties of the tool.

Intermediate Business owner Explainer Business, Law & Security

Sep 13, 2026

Measuring AI ROI – and Why Most Companies Cannot See It

Krisztian Eyssen, Krisztian Eyssen

Measuring AI ROI – and Why Most Companies Cannot See It

In the same quarter, one survey found that 95% of companies see zero return, another that three quarters of them see a positive one. Both are executives reporting on themselves. And one rigorous measurement showed that the feeling and the reality are **40 percentage points** apart. Once you know that, you already know what you have to do differently.

Intermediate Business owner Explainer Business, Law & Security

Sep 13, 2026

AI Strategy for a Small Company: Where Do You Start?

Krisztian Eyssen, Krisztian Eyssen

AI Strategy for a Small Company: Where Do You Start?

Across the EU, 17.0% of companies with 10–49 employees use AI; in Denmark the figure is 37.5%. If you are starting now, three months is enough — and in the first month you buy nothing. The plan asks one hard decision of you: which single process.

Beginner Business owner How-To Business, Law & Security

Sep 13, 2026

Private AI: Keeping Data Inside Your Company

Krisztian Eyssen, Krisztian Eyssen

Private AI: Keeping Data Inside Your Company

One large provider's zero data retention agreement lists item by item which endpoints it covers — and which it does not. On the does-not list: **file upload** and the **vector store**: **exactly the two features you would use to build RAG on that platform.** And on the other side, the assumption that "local means safe": a 293-day survey found **175,108 publicly reachable local model servers** in 130 countries.

Advanced Business owner How-To Data, RAG & Self-Hosted AI

Sep 13, 2026

Why Run AI on Your Own Machine?

Krisztian Eyssen, Krisztian Eyssen

Why Run AI on Your Own Machine?

Of the four usual reasons, two hold up and two do not. `[Own calculation]` Against the cheapest API tier, a $3,500 machine breaks even at **2.6 billion tokens a year** — 133 days of continuous generation. And here is the twist that holds the whole article together: **the volume at which local running pays off is exactly the volume at which the local model is no longer good enough.** There is a fifth reason, though, that nobody states out loud, and measurably it is the strongest of the lot.

Beginner Business owner Explainer Data, RAG & Self-Hosted AI

Sep 13, 2026

Keeping the Knowledge Base Fresh

Krisztian Eyssen, Krisztian Eyssen

Keeping the Knowledge Base Fresh

A measurement built on 96 thousand question-answer pairs and 219 thousand documents found that the mere presence of outdated content causes, according to the study, **at least a 20% drop in performance**, with some models doing worse than chance. But the most important finding is not the number: **models stay appropriately uncertain when they find nothing — and are confidently wrong when they find something stale.** An empty knowledge base is less dangerous than an old one.

Intermediate Business owner How-To Data, RAG & Self-Hosted AI

Sep 13, 2026

A Company Knowledge Chatbot: A Realistic Plan

Krisztian Eyssen, Krisztian Eyssen

A Company Knowledge Chatbot: A Realistic Plan

An airline's chatbot gave the wrong rules for its bereavement fare. The company's defence was that it is not responsible for "information provided by its agents, including a chatbot" — and it floated the idea that **the chatbot is a separate legal entity**. The court's answer is one sentence worth printing out: **"It makes no difference whether the information comes from a static page or from a chatbot."** The damages came to $812. The precedent is not so cheap.

Intermediate Business owner Recipe Data, RAG & Self-Hosted AI

Sep 13, 2026

How Do You Know Your RAG System Is Right?

Krisztian Eyssen, Krisztian Eyssen

How Do You Know Your RAG System Is Right?

At a public evaluation campaign a judge model was measured against a human assessor. Their agreement, corrected for chance, came out at **0.29**. On the very same task, **two humans agreed at −0.03** — worse than chance. So this is not a story of "the machine is bad, the human is good". The task itself is ill-defined at the edge cases. This article is about what can still be measured reliably.

Advanced Business owner How-To Data, RAG & Self-Hosted AI

Sep 13, 2026

Preparing and Chunking Your Documents

Krisztian Eyssen, Krisztian Eyssen

Preparing and Chunking Your Documents

In one measurement, simply cutting a long document into chunks lifts retrieval from **28.2 to 45.7** — **17.5 points for free**. The same measurement also shows that **bigger chunks are monotonically worse**. The awkward part: the most widely used tools ship with defaults of 800 and 1,024 tokens, or 4,000 characters — and in an independent test the 800-token setting finished **near the bottom of the field**.

Advanced Business owner How-To Data, RAG & Self-Hosted AI

Sep 13, 2026

Teaching AI Your Own Documents: RAG Explained

Krisztian Eyssen, Krisztian Eyssen

Teaching AI Your Own Documents: RAG Explained

Start with a 910-question benchmark: the same model scored **48.1%** out of the box, **50.4%** after fine-tuning, and **87.5%** with RAG. On another model fine-tuning did not help but **hurt** — from 35.3% down to 21.9%. So RAG is not one option among several: for new knowledge it is an order of magnitude better. It just happens **not to be teaching** — and most of the disappointment comes from believing that it is.

Intermediate Business owner Explainer Data, RAG & Self-Hosted AI

Sep 13, 2026

Vibe Coding: What It Is Good For and Where It Stops

Krisztian Eyssen, Krisztian Eyssen

Vibe Coding: What It Is Good For and Where It Stops

By the original definition, the point of vibe coding is that you "**forget that the code even exists**". So the question is not how good the model is — it is whether **you can afford to forget that this particular code exists**. In nine documented cases the answer was no.

Beginner Business owner Explainer Coding & Development

Sep 13, 2026

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