---
title: "AI Engineering Terms, Explained"
source: https://bitvaria.com/en/ai-engineering-begriffe
---

# AI Engineering Terms, Explained

The building blocks of modern AI systems, one at a time. Explained concretely, by the people who build them.

AI systems are made of a handful of building blocks that keep coming back: Token, Embeddings, Context Window, RAG, Evals. Understanding these terms is understanding why an AI project holds up or falls over.

This series explains them one by one. Each post takes a single term, starts from a concrete example rather than a definition, and stays easy to read. For more depth, every post has a separate, skippable technical box with the details.

## The Machine

How a model runs, what it costs, and where the memory runs out first.

-   [Token live](https://bitvaria.com/en/was-ist-ein-token)
-   [Sampling live](https://bitvaria.com/en/sampling)
-   Context Window soon
-   Embedding soon
-   [Vision live](https://bitvaria.com/en/wie-sieht-ki-ein-bild)
-   Attention soon
-   [KV Cache live](https://bitvaria.com/en/kv-cache)
-   [Prefill & Decode live](https://bitvaria.com/en/prefill-decode)
-   Quantization soon

## The Harness

How a text generator turns into a system you can hand a task to.

-   Structured Output soon
-   Tool Use soon
-   Agents soon
-   RAG soon

## The Discipline

How to measure, observe, and safely run AI systems for many tenants.

-   Evals soon
-   Observability soon
-   Prompt Injection soon
-   Multi-Tenancy soon

## The Judgment

Which tool for which problem. The decisions that make a system.

-   Fine-tuning vs. RAG soon
-   Build vs. Buy soon

The series grows post by post. Terms without a link are in the works.

## AI in your own company, not just as a term?

In 30 minutes we figure out which use case has the biggest leverage for you. Free, no commitment.

[Book a conversation](https://bitvaria.com/en/contact)