I'm excited to share that I recently cleared the Databricks Certified Context Engineer Associate certification.
What I found most interesting while preparing was how Context Engineering goes beyond prompt engineering. It made me think more deeply about how AI systems manage and use information through retrieval, memory, tools, context management, governance, and evaluation.
One of my biggest takeaways was that building effective AI agents is not just about choosing the right LLM. A big part of the challenge is ensuring the agent receives the right context at the right time.
I'm curious to hear from others who have taken the certification or are working with agentic systems: what part of Context Engineering do you think is the most important in building production-ready AI agents?
