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Start at AI →Practical guidesFOUNDATIONS
Start before LLMs. Understand where AI, ML and neural networks fit.
TRANSFORMERS & LLMs
Follow text from characters to tokens, attention, transformers and generation.
PROMPTS & APIs
Understand how applications send instructions to models and handle production API behavior.
KNOWLEDGE, EMBEDDINGS & RAG
Teach models to look up relevant information before answering.
TOOLS, AGENTS & ORCHESTRATION
Move from a model that talks to a system that can inspect and act.
FRAMEWORKS & MCP
Understand the names you will hear when teams build agentic systems.
MODEL ADAPTATION
Know when to prompt, retrieve, fine-tune or compress a model.
EVALS & OBSERVABILITY
Measure whether the AI is good and trace where it fails.
LLMOPS & AI INFRASTRUCTURE
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.
RELIABILITY & SRE
Apply familiar SRE thinking to AI dependencies and workflows.
AI SECURITY
Understand how untrusted text, tools and autonomy create new attack paths.
AI INCIDENTS & COST
Recognize the failure modes an AI SRE will actually troubleshoot.
PRODUCTION ARCHITECTURE
Connect every term into systems you can design and operate.