#YearInReview insights from the last few months building Azure SRE Agent...
To kick things off, sanchitmehta and visagarwal just shared a great deep dive on context engineering for reliable AI agents, and it’s a must‑read if you’re building or operating agents in real systems. The core idea: reliability doesn’t come from bigger models alone—it comes from how well you design, structure, and control context. The post breaks down practical lessons learned from building real agent flows, including how context boundaries, memory, and guardrails directly impact consistency, debugging, and trust. If you’ve ever asked: Why does my agent behave differently run to run? How do I make agent decisions more predictable? Where should logic live vs. prompts? This write‑up tackles those questions with concrete examples, especially relevant for folks working with Azure SRE Agent or thinking about agent reliability in production systems. Give it a read, drop your thoughts here, and share how you’re approaching context design in your own agents. Curious what’s worked—or not—for you 👇
