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AI EngineeringParadigm

Pre-training vs Fine-tuning — two phases of an AI model's life

Every large language model goes through several distinct training phases: first it absorbs trillions of tokens from the internet, then it learns to behave like a useful assistant. Understanding that split is the key to deciding when fine-tuning is worth the effort, when RAG is the right answer, and when neither makes sense.

Pretraining (Self-Supervised Pretraining)Supervised Fine-TuningReinforcement Learning from Human FeedbackPEFT / LoRA+10

10 June 2026

AI ArchitectureTechnology

The context window — what it is and why it defines what an LLM can do

The context window is a language model's working memory — it sets how much text the AI can take into account at once. Understanding how it works and where its limits lie explains both the cost and the surprising mistakes of modern models.

9 June 2026

InfrastructureAI Engineering

What is the Model Context Protocol (MCP)?

The Model Context Protocol is an open standard that unifies how AI models connect to external tools and data. It matters because, in under eighteen months, it became the de facto common integration language across the industry — from Anthropic to OpenAI and Google DeepMind.

8 June 2026

AI ArchitectureArchitecture

Do Language Models Need Sleep? LLM Sleep and Offline Recurrence

Language models increasingly handle long, multi-step tasks, yet their attention mechanism scales poorly with context length. LLM Sleep proposes that — much like biological sleep — a model should periodically "sleep on" recent context and consolidate it into persistent weights before clearing its cache.

8 June 2026

AI ArchitectureArchitecture

What are World Models?

World models are AI systems that learn an internal simulation of reality and predict what happens next — instead of merely reacting to the current image. They are one of the directions in which AI is shifting from pattern matching toward planning and reasoning about cause and effect.

2 June 2026

AI / MLTechnology

Machine Learning — what it is and how it works

Machine learning (ML) is the branch of artificial intelligence in which computer systems build their own decision rules from data instead of receiving them as hand-written code. It is today the core of nearly every practical AI technology — from spam filters to large language models and autonomous robots.

SVMTransformerLarge Language ModelReinforcement Learning+1

31 May 2026

InfrastructureTechnology

Vector Database — How It Works and Why It Powers Modern AI

Vector databases are specialized systems storing data as high-dimensional numerical representations that enable search by meaning rather than keywords. They form the critical foundation of RAG architecture, allowing language models to access current, verifiable external knowledge.

31 May 2026

Agentic AIParadigm

ReAct — what is the "reason and act" paradigm for LLM agents?

ReAct is an architectural pattern for large language models in which the model alternates between generating thoughts (reasoning), calling external tools, and reading observations back into its context. Understanding ReAct is a prerequisite for building any modern AI agent, because the Thought–Action–Observation loop sits underneath most agentic systems shipped today.

30 May 2026

ComponentsAI Engineering

Prompt Caching — What It Is and How It Works

Prompt Caching is an optimisation mechanism in large language model APIs that allows repeated reuse of processed prompt fragments without recomputing them from scratch. For queries containing long, repetitive contexts — such as extensive system instructions, documents, or few-shot examples — it can make API calls up to ten times cheaper and several times faster.

29 May 2026

AI / MLSoftware

Claude Opus 4.8 — Anthropic's Flagship Model with Adaptive Thinking

Released on May 28, 2026, Claude Opus 4.8 is the current leader in comprehensive AI intelligence rankings. With its Adaptive Thinking mechanism, one-million-token context window, and revolutionary agentic capabilities, the model redefines standards for autonomous coding, data analysis, and enterprise business tasks.

AnthropicConstitutional AI

29 May 2026

Agentic AIArchitecture

Multi-Agent Systems: How AI Learns to Cooperate and Compete

Artificial intelligence has stopped working alone. Multi-Agent Systems (MAS) create networks of specialized agents that negotiate, compete, and cooperate — reshaping the AI paradigm from the ground up.

28 May 2026

AI ArchitectureArchitecture

The Transformer Architecture: How Attention Rewrote the Rules of AI

The Transformer is a neural network architecture that in 2017 replaced recurrent models and launched the era of large language models. Understanding how it works is the key to grasping where ChatGPT, BERT, GPT-4, and Vision Transformers came from.

Transformer

22 May 2026