Understand AI.
Visually.
Clear visual explainers for the models, agents, embeddings, infrastructure and systems behind modern AI — without the academic fog.
Learn the concept first.
Then understand why it matters.
Featured explainer
How AI Agents Use Tools
Planning, tool calling, state, memory and the execution loop behind modern agentic systems.
How Retrieval-Augmented Generation Works
Chunking, embeddings, retrieval, reranking and how external knowledge is injected into an LLM prompt.
How Embeddings Turn Meaning Into Vectors
How semantic relationships become vectors and why embeddings power search, recommendations and RAG.
Learn one concept at a time.
Short, visual guides designed to make difficult AI concepts easier to understand and easier to remember.
Self-Attention, Explained Visually
Queries, keys, values and why attention lets a model decide which parts of context matter.
How Large Language Models Actually Work
From tokenization and embeddings through transformer layers, logits and next-token prediction.
How Regression Models Work
Linear regression, loss functions, coefficients, residuals and how models learn relationships from data.
See it.
Understand it.
Use it.
Visual first
Diagrams and examples before dense technical language.
Practical context
Understand not only how something works, but when it matters.
Current AI
Focused on the systems and patterns being used in modern AI products.
Understand the technology. Then compare the models.
Use SENA Learn to understand the concepts, then use the SENA Model Index to see how leading AI models perform in practice.