GenAI & Agent Foundations
Learn this hub in order: start with GenAI fundamentals, move into application engineering, then finish with agent-system design.
1. GenAI Foundations
Start with the core mental models: how models, tools, structure, and context fit together in GenAI systems.
2. Application Engineering
Move into the decision frameworks and system components that turn model calls into useful, production-ready applications.
3. Agent Systems
Finish with reasoning and orchestration patterns for multi-step and multi-agent workflows.
1. GenAI Foundations
Start with the core mental models: how models, tools, structure, and context fit together in GenAI systems.
What Are AI Agents?
Understanding autonomous AI systems that perceive, reason, plan, and act to achieve goals.
Learn moreTool Use & Function Calling
How agents interact with external tools, APIs, and services to take action in the real world.
Learn moreModel Selection & Routing
How to choose the right model for each task and route workloads by capability, latency, and cost.
Learn moreStructured Outputs
Generating validated JSON, typed objects, and schema-constrained results instead of brittle free-form text.
Learn moreContext Engineering
How prompts, retrieved documents, tool results, memory, and instructions are assembled into the model context.
Learn moreMultimodal GenAI
How GenAI systems work across text, images, audio, video, and documents instead of text alone.
Learn more2. Application Engineering
Move into the decision frameworks and system components that turn model calls into useful, production-ready applications.
Memory Systems
Short-term, long-term, and episodic memory architectures that give agents persistent knowledge.
Learn moreFine-Tuning vs RAG vs Tools vs Workflows
A practical framework for choosing whether to adapt the model, retrieve knowledge, call tools, or design a workflow.
Learn moreHuman-in-the-Loop Design
How to place approvals, escalation points, and review loops into GenAI and agent workflows.
Learn moreAuth, Tenancy & Data Boundaries
How to design access control, tenant isolation, and data boundaries for production GenAI systems.
Learn moreModel Context Protocol
The open standard that lets LLM applications seamlessly connect to any external data source or tool.
Learn moreRAG & Agentic RAG
Retrieval-augmented generation and its evolution into agentic systems with hierarchical retrieval.
Learn more3. Agent Systems
Finish with reasoning and orchestration patterns for multi-step and multi-agent workflows.
Planning & Reasoning
Chain of Thought, ReAct, Tree of Thought, and other reasoning strategies agents use to solve problems.
Learn moreWorkflow Reliability
Retries, idempotency, fallback chains, and bounded autonomy for reliable multi-step agent workflows.
Learn moreComputer Use & Browser Automation
When agents should act through user interfaces and what controls those systems require.
Learn moreMulti-Agent Systems
Coordinating multiple AI agents to collaborate, delegate, and solve complex problems together.
Learn more