Building Agent Architectures: Design Decisions That Matter
You can ship an agent in an afternoon. Getting multiple agents to work together in production without losing context, overreaching, or silently breaking—that's a different problem entirely. And most of the decisions that matter aren't about code. They're about scoping.
Luke Bechtel has built multi-agent systems in production—agentic data pipelines, DAG-based workflows, hybrid RAG context systems—and will break down the design decisions that actually determine whether an agent system works or falls apart.
What he'll cover:
What an agent actually is at the architecture level, and what it isn't
The two decisions that define every agent system: what can it see, and what can it do
Context window management
Reflexive systems (flexible bot swarms) vs. fixed systems (narrowly scoped repeaters)
Getting multiple agents to coordinate without everything falling apart
Production failure modes and how to avoid them
About Luke:
Founding engineer at Ardent AI, where he built agentic data engineering pipelines, DAG-based agent workflows, and hybrid RAG context systems. Currently at Infinity (inference). MS in CS from Georgia Tech, ML specialization.
Presented by Rally SF.