Agentic Workflows in Beam: The Opportunity Ahead of Us

Use of LLMs and agents is steadily growing in prominence and importance across the data processing ecosystem and more broadly across all of software. Today, though, many agentic prototypes fail to reach production for familiar reasons, including: overly complex resource management, the inability to colocate the correct context, high deployment costs, and a lack of guardrails for non-deterministic agents. Agentic workflows can solve some of these problems by providing boundaries for an agent to operate within, but there is a lack of scalable tools to do this well.

This talk will discuss why streaming data processing systems are broadly well positioned to safely scale and deploy agentic workflows, and why Beam is a particularly good fit. It will then spend some time talking about the gaps in Beam (and other systems), and how moderate targeted investments can close those gaps.

Attendees can expect to come away with a high level understanding of agentic workflows, the current state of agentic workflows in Beam, and the path forward to take Beam’s agentic support from solid to excellent.