Question 1

What will I achieve by the end of this workshop?

Accepted Answer

You’ll know how to design and implement scalable, context-aware RAG and multi-agent systems. You’ll leave with clear architectures, patterns for context, memory, orchestration, and evaluation you can apply directly to production systems.

Question 2

What are the prerequisites for attending?

Accepted Answer

You should have basic familiarity with LLMs and how they’re used in applications. Programming experience is recommended. This workshop is not for absolute beginners and focuses on system design rather than prompt basics.

Question 3

Who is this workshop designed for?

Accepted Answer

AI engineers, ML engineers, software architects, and technical builders working with RAG, agents, copilots, or LLM-powered workflows who want to move from demos to reliable, production-ready systems.

Question 4

How is the workshop structured?

Accepted Answer

This is a live, 5-hour session combining architectural walkthroughs, practical examples, and real-world patterns. It includes explanations, diagrams, applied concepts, and interactive Q&A throughout the workshop.

Question 5

What software or tools will I need to participate?

Accepted Answer

A laptop with internet access is sufficient. Familiarity with Python and common LLM frameworks is helpful but not mandatory. No complex setup is required to follow along and benefit from the session.

Question 6

Will the sessions be recorded?

Accepted Answer

Yes, live sessions will be recorded, and recordings will be accessible exclusively to registered participants for review and reinforcement of learning.

Question 7

How interactive is this workshop?

Accepted Answer

The workshop emphasizes hands-on coding, and real-time instructor interaction, supplemented by asynchronous support.

Question 8

What if I want to cancel my ticket after purchasing it?

Accepted Answer

Once a ticket has been purchased it can only be cancelled 10 days before the event starts. Please note that all refund requests are subject to approval, and our team will review your request.

Context Engineering for Multi Agent Systems Cohort 2

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Context Engineering for Multi Agent Systems Cohort 2

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