AI Basics
The concepts you need to follow any conversation about AI: model, token, prompt, context window. Each article explains one term in plain words and shows where it appears in practice.
What Is a Chatbot, and When Does It Pay Off
A chatbot is a program that carries on a conversation in place of an employee: it answers questions, collects data, and hands the hard cases onward.
Generative AI — What It Is in Plain Words
Generative AI is a class of models that produce new text, images, or code on request, drawing on patterns learned from training data.
What Is a Large Foundation Model
A large foundation model is an AI trained once on an enormous body of data and then usable across dozens of company tasks without separate training for each.
Prompt engineering: how to get the answer you need from a model
Prompt engineering is the practice of drafting and testing how a task is worded for a model: the same model makes noticeably fewer mistakes when the instruction has been refined.
Long context: when it pays to feed the whole document
Long context is a model's ability to hold dozens of pages in a single request: a contract, a policy manual and an email thread are read whole, without being cut into pieces.
Context engineering — explained simply
Context engineering is the assembly of a working environment for the model: which data, rules and tools enter the request, in what order and in what volume.
Open weights — what they are and when they beat closed models
Open weights are the published parameters of a trained model: it can be downloaded, run on a company's own hardware and tuned to its own documents.
What Is a System Prompt, and Why It Decides Everything Before the First Word
A system prompt is the hidden instruction that gives a model its role, tone and limits before the conversation begins. It determines whether the model is rude or genuinely useful.
What Is a Foundation Model, and Why Companies Save Money on It
A foundation model is a large general-purpose model trained on enormous volumes of data: for a specific job it gets configured, not trained from scratch.
What a neural network is, in plain terms
A neural network is a program that derives rules from examples: trained on labelled data, it learns to process requests, texts and images without an algorithm written out by hand.
What is artificial intelligence: no myths, just facts
Artificial intelligence is a set of technologies that derive rules from examples and take over part of the decisions and routine work inside a company's process.
What Machine Learning Is and When It Pays Off
Machine learning is a way to derive a rule from accumulated data instead of writing it out by hand: the system learns from examples and produces a prediction for each new case.
What Inference Is and What Makes Up the Bill for It
Inference is the moment a trained model answers a request — and it is what gets billed every month.
What is a context window, and why does the model "forget"?
A context window is the limit on how much text a model can see in a single request: instructions, documents, the question, and the conversation history all count together, and anything past the limit is dropped silently.
What Is a Large Language Model, in Plain Language
A large language model is a program that continues any text with the most likely next word. It learned from books, articles and correspondence, and it answers in human language.
What is a prompt and why the result depends on it
A prompt is a written instruction for a language model, and its precision decides whether the right result arrives on the first try or has to be redone.