TERBISBuild what actually works — AI you can trust, and a business model that holds together
Practical guides, data storytelling, and strategic thinking for people building something new.
What every board needs to know about AI
Free guide
Learn to talk with AI
A modern guide to better results — model-independent advice and a simple method that works no matter which AI service you use.
Latest articles
Tokens and n-grams: the basics nobody explains, and the bill nobody sees coming
You don't pay per word when you use an AI service. You pay per token, and the difference is bigger than it sounds. Here's what a token actually is, where the idea comes from, and why the old n-gram technique still works in the machine room.
Sep 20 · 2Attention: the history behind the breakthrough, and why it also explains hallucinations
N-gram models forgot everything beyond a few words. Attention solved that, and made modern language models possible. The same mechanism is also a big part of why they sometimes sound certain about things that aren't true.
The Lindy Effect: why the old survives – and when it's still right to bet on what hasn't yet
The longer something has existed, the longer it's likely to keep existing. But that same logic is also the reason to deliberately, in a controlled way, bet on what hasn't survived yet. Here's the difference between breaking the Lindy effect and using it correctly.
Oct 16Antifragility: building things that gain from disorder
The previous article showed that some things can never be predicted. This one is about what to do about it – not by getting better at guessing, but by building something that benefits when the guess is wrong.
Stop cleaning all your data: the trap of generic data quality projects
55–60% of company data is never used at all. Layering a generic quality project over everything isn't quality work. It's cleaning a room no one ever enters.
Aug 17 · 2What is data actually worth?
Data that doesn't create value is just a cost. Here are three ways to actually turn data into money, and the five capabilities that decide whether you can pull it off.
From the field
Checklists
Guides
Guide: learn to talk with AI
A modern guide to better results — model-independent advice and a simple method that works regardless of which AI service you use.
Aug 22 · 2Guide: how to create OKRs that actually work
Most OKR implementations don't fail because the model is wrong — they fail because the steps happen in the wrong order. Eight steps from strategic alignment and timeframe to evaluation.
Series
Consequence thinking
Part 8: Antifragility: building things that gain from disorder
2 partsAI Fundamentals
Part 1: Tokens and n-grams: the basics nobody explains, and the bill nobody sees coming
3 partsOKR
Part 3: OKR vs KPI: the difference between measuring and moving
3 partsBeyond the Prompt
Part 3: The silent exclusion: competence that erodes without anyone closing the door
2 partsThe AI Alphabet
Part 2: Into the engine room: bagging, boosting, attention and why it all happened at once
2 partsThe Fundamentals of Strategy
Part 2: From vision to advantages – why one vision needs several strategies, not one
4 partsFrom Syntax to Ontology
Part 4: Context – and is "context engineering" the new black?
1 partsBoard & AI
Part 1: What every board needs to know about AI
Things to read
Natural Language Processing with Transformers
Practical guide to transformers with code. From theory to implementation — perfect for those who want to build something real.
Deep Learning
The standard reference in deep learning. Comprehensive, mathematical, and essential for those who want to understand the foundation behind modern architectures.
Build a Large Language Model (From Scratch)
For those who want to go from theory to code. Raschka walks through the architecture, training, and practical implementation of a language model from scratch.