AI agent demos are easy to build. Building agents that work reliably in production is much harder. Enterprise agents need access to the right business context, fresh operational data, and relevant memory, all while meeting latency and cost constraints.

Explore why context has become a key challenge in production AI systems and get hands-on with the Redis Iris platform. Examine topics such as retrieval, memory, real-time data access, and low-latency inference, and discuss the design considerations behind deploying reliable AI agents in enterprise environments.

Learn more about:

• Common context management patterns for production AI agents.
• The trade-offs between retrieval, memory, and real-time data.
• Architectural considerations for building reliable enterprise AI systems.

Important Notes:

• Please make sure you RSVP at official Luma page of Lorong AI. Meetup.com RSVP is not sufficient. RSVP link: https://luma.com/u3m2b2gk
• Please bring an internet-facing laptop for the session.
• The workshop will be technical. Participants should have basic familiarity with Python and APIs, but do not need deep prior experience with Redis or agent frameworks.
• As this is a hands-on session, please update your RSVP in advance if you're unable to attend. Last-minute cancellations or no-shows are strongly discouraged.
• Lorong AI members will be prioritised for the session. Registration is subject to approval.