Anyone can spin up an AI agent prototype over a weekend. Getting it to survive real users and real data is a different story. It has to pull the right information at the right moment, hold context through a full conversation, respond fast, and do it all without burning through your LLM budget. Most teams haven't built that context architecture yet.
Join a Redis Solutions Architect for a live, hands-on workshop focused on solving the context challenges that stand between AI agent prototypes and production. In just 2 hours, you'll build the components behind a working agent that can retrieve relevant information, access real-time data, intelligently route requests, reuse responses, and maintain memory across conversations.
You'll learn how Redis Iris brings these capabilities together into a context architecture designed to help agents deliver faster, more relevant, and context-aware experiences in production.
Highlights
What You’ll Build & Key Takeaways
Build a context-aware AI agent that works with relevant knowledge, live data, and persistent memory.
Learn how to address production challenges including latency, unnecessary LLM calls, intelligent routing, and maintaining context.
Have the tools to apply these capabilities to a use case relevant to your work.
Leave with working code and an architecture you can evaluate against your own AI stack.
What You’ll Need
Your usual Python setup and IDE
A free Redis Cloud account
Comfort reading Python — you won't write everything from scratch
No Redis or embeddings experience needed
Save Your Seat for the Workshop
Register to join us for this workshop! Space is limited so register today.
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