GenAI Foundations
Advanced
Operate production-grade systems · 15 tutorials · 35-45 min each
Understand and build the baseline AI application patterns used across the rest of the site.
Production RAG Architectures and Self-Healing Patterns
Move beyond basic RAG to production-grade retrieval: hybrid search, self-query, re-ranking, and self-healing loops that detect and repair retrieval failures.
Multi-Agent Systems and Orchestration Patterns
Supervisor, parallel, and sequential multi-agent patterns. Design systems where specialized agents collaborate, with state management and failure handling.
AI System Observability and Monitoring
What to log, how to trace, and how to detect drift before users do. Build the observability stack that turns AI black boxes into diagnosable systems.
Security: Prompt Injection, PII, and Red Teaming Your AI App
Prompt injection attacks, indirect injection via documents, PII leakage through context, and how to red team your AI application before attackers do.
Fine-tuning vs RAG vs Prompting: A Decision Framework
When to prompt-engineer, when to RAG, and when to fine-tune. A decision framework with cost, complexity, and quality trade-offs mapped out.
Writing AI Specifications for Engineers
The BA/PM guide to writing AI feature specs that engineers can actually implement. Eval criteria as acceptance criteria, prompt requirements, and edge case handling.
AI Cost Optimization at Scale
Token costs, prompt caching, batching, model routing, and response caching. Techniques that turn a $50K/month AI bill into $12K without sacrificing quality.
Deploying AI Systems: CI/CD, Eval Gates, and Rollbacks
AI deployments need eval gates, not just unit tests. Build the CI/CD pipeline that validates AI quality before every deploy and rolls back on degradation.
Enterprise MCP and Tool Architecture
Move from ad-hoc function calls to protocolized, auditable tool integrations using MCP and enterprise connector patterns.
Agent Runtime Durability: Checkpoints, Resume, and Human Approval
Build agent workflows that survive crashes, pauses, and human approvals without corrupting state or duplicating side effects.
Context and Memory Engineering for Enterprise Agents
Design memory layers and context budgets that improve quality and lower cost in long-running enterprise workflows.
Agent Evaluation Harness: Trace Grading and Release Gates
Build workflow-aware evals that grade not just final answers, but the trajectory of tool use and decisions.
AI Governance: Guardrails, Prompt-Leak Defense, and Oversight
Implement governance controls that prevent data leaks, unsafe actions, and silent policy violations in agentic systems.
Agent Interoperability and A2A Patterns
Design multi-agent systems with clear contracts so teams can mix runtimes and frameworks without brittle rewrites.
Long-Running Agents and Async Operations
Build background agent workflows with polling, cancellation, retries, and user-visible progress for enterprise reliability.