Bad Agentic AI output is rarely a generation problem. It's usually bad retrieval, bad planning, or bad execution upstream. Measure every stage, not just the result.
Azure AI Foundry turns RAG setup from a week of manual plumbing into an afternoon of configuration — but access control, security, and cost planning are still on you.
A practical framework for graduated autonomy in self-healing infrastructure, covering three remediation tiers and policy-driven blast-radius controls for cloud SRE teams.
Evaluation has real costs (inference spend, latency, storage) — budget for it explicitly, and treat every user-reported regression as a permanent new test case.
Legacy VMware on-prem, reactive AWS, and a ticket queue that never emptied — we deployed agentic AI across both substrates and changed how the team operates entirely.
Secure MCP servers against prompt injection, data leaks, and denial-of-wallet with four practical, OWASP-aligned gates from code to production. Runnable code.
Practical patterns, code examples, and hard-earned lessons from implementing enforceable guardrails around autonomous agents in real enterprise environments.
Learn key concepts like embeddings, vector search, chunking, hybrid search, semantic ranking, and how these pieces fit into a scalable, enterprise-grade AI application.
Explore a three-part field manual on building reliable production AI agents through context engineering, guardrails, and human-in-the-loop architecture.