A structured mindmap covering foundations, architectures, tooling, and production patterns across modern Generative AI.
Most GenAI content explains techniques in isolation. This map shows how they connect into working systems.
From core theory to production deployment — every major area of the GenAI stack, organised by how they relate to each other.
Core technical concepts that explain how models work — the theory behind the tools.
How GenAI applications are constructed in practice — prompting, retrieval, agents, and the tooling around them.
What is required to deploy and operate GenAI reliably at scale — infrastructure, patterns, and engineering practices.
How GenAI systems are evaluated, monitored, and controlled — quality, safety, and risk management.
Common patterns of real-world GenAI solutions — where the stack lands in production.
Explore in any order — follow a structured path or jump directly to what you need.
Opens an explanation, diagram, copy-ready code example, and key questions by role — Leader, PM, and Engineer — in the side panel.
Drills into a cluster to reveal sub-topics and tools. Use the toolbar to jump to any depth instantly.
Type in the search bar to jump directly to any topic — even ones hidden deep inside a cluster.
Nodes marked ◆ include code examples and diagrams.
Understand architectures, tooling choices, and implementation patterns across the full GenAI stack.
Build structured understanding from fundamentals to real-world systems — with code and diagrams on every key concept.
Every major node includes Leader and PM-specific questions — on strategy, prioritisation, and trade-offs — so you can engage GenAI discussions with sharper instincts.
Standalone pages covering the most complex topics — comparison tables, Python code examples, method cards, and references.
Start from any concept — or use the search to go directly to what matters to you.
Open the MapOpen source · MIT License · Work in progress
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