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Where Is AI Heading? What Is Worth Preparing For

Krisztian Eyssen, Krisztian Eyssen

Where Is AI Heading? What Is Worth Preparing For

In the spring of 2025 an industry leader said that within six months AI would be writing 90% of the code. Eighteen months later the most favourable measurement, based on self-reporting, stands at **51.9%**. The direction was right, the timetable was not — and that is the rule for this whole article. There is no forecasting here: four trends, each with a measurement and a date behind it, then four claims with no evidence — among them AGI, where GPT-6 Astra substantively rearranged the argument in September.

Beginner Everyone Explainer Business, Law & Security

Sep 13, 2026

Deepfake Fraud: Verify Before You Pay

Krisztian Eyssen, Krisztian Eyssen

Deepfake Fraud: Verify Before You Pay

In the 25.6-million-dollar Hong Kong case it was not the video call that started the fraud but a phishing message — the deepfake was only there to remove the doubt. And according to the latest UK figures, losses to CEO fraud fell **53%** in 2025, to a record low. Prevention works. But the rule must not be tied to an amount.

Beginner Business owner Explainer Business, Law & Security

Sep 13, 2026

The One-Page AI Policy: A Template You Can Fill In

Krisztian Eyssen, Krisztian Eyssen

The One-Page AI Policy: A Template You Can Fill In

The strongest argument for having a policy is not security, it is **Directive (EU) 2016/943**: under EU trade secret law, protection only exists if the holder has taken reasonable steps to keep the information secret. With no written rule, a court can legitimately ask whether your pricing was ever a trade secret at all. Here is the eight-point template.

Beginner Business owner Template Business, Law & Security

Sep 13, 2026

Shadow AI: The Tools Your Team Already Uses

Krisztian Eyssen, Krisztian Eyssen

Shadow AI: The Tools Your Team Already Uses

In a 48,340-person survey spanning 47 countries, **6%** of employees work under a policy that bans generative AI — while 41% have **no rule at all**, and 19% do not know whether one exists. The "everyone bans it, they use it anyway" story is false. The real problem is a different one, and you can map it in a single day.

Beginner Business owner Explainer Business, Law & Security

Sep 13, 2026

AI Literacy for Your Team: A Practical Training Plan

Krisztian Eyssen, Krisztian Eyssen

AI Literacy for Your Team: A Practical Training Plan

Since August 2026 it has been a supervised and enforceable EU obligation that your company does something for AI literacy — but the wording of the law was softened in July 2026, and it does not ask that your colleagues know something. It asks that you made the effort. Four sessions, homework, and one measurable outcome that is not a knowledge test.

Beginner Business owner Template Business, Law & Security

Sep 13, 2026

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

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

Local AI Runners: Which One to Pick

Krisztian Eyssen, Krisztian Eyssen

Local AI Runners: Which One to Pick

The most important thing to know: **Ollama, LM Studio, Jan, KoboldCpp and Docker Model Runner all use the same engine** — llama.cpp, and MLX on a Mac. They do not differ in speed but in the packaging and in the **defaults**. And the defaults are exactly where the trap is: Ollama **truncates at 4,096 tokens** out of the box, even when the model could handle 256k.

Beginner Developer Tool review Ollama 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

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

Where AI Saves Real Time in an Office Day

Krisztian Eyssen, Krisztian Eyssen

Where AI Saves Real Time in an Office Day

Seven task types, with measurements. In some the saving is large and real: in a 444-person experiment a writing task fell from 27 minutes to 17. In some it is exactly zero: in a 6,000-person experiment measured by telemetry, time spent in meetings did not move. And in some the machine slows you down. The difference is not luck, it is the type of task.

Beginner Office worker Explainer Work & Productivity

Sep 13, 2026

Meeting Notes People Actually Read

Krisztian Eyssen, Krisztian Eyssen

Meeting Notes People Actually Read

A good set of meeting notes is not a summary, it is three lists: decision, owner, deadline. Nobody reads whatever else is in there. The machine can write all three — but in the most recent measurement **more than 40% of the claims in generated summaries were not supported by the recording**, and outside the big languages even the transcript gets every seventh word wrong.

Beginner Office worker Recipe Work & Productivity

Sep 13, 2026

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