Orchestration

Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel

Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel

Learn how Vercel's open-source Workflows platform simplifies deploying durable, observable, and long-running AI agents by abstracting away the infrastructure complexities of queues, databases, and error handling.

The End of Ad-Hoc BI Dashboards

The End of Ad-Hoc BI Dashboards

Nick Schrock, CTO of Dagster, introduces Compass, a Slack-native tool for collaborative, exploratory data analysis, and discusses the rising importance of 'context engineering' as the new data pipeline in the AI era.

How to Future-Proof Your Career in the Age of AI (with Sheamus McGovern)

How to Future-Proof Your Career in the Age of AI (with Sheamus McGovern)

Sheamus McGovern outlines a multi-tiered skills hierarchy for AI and data professionals to navigate the future of work. He argues against fear-mongering, providing a practical roadmap that progresses from foundational GenAI prompting and advanced engineering to orchestration, human-centered skills, and the meta-skill of continuous learning, emphasizing the need to sunset old skills and build a personal brand.

Orchestrating Complex AI Workflows with AI Agents & LLMs

Orchestrating Complex AI Workflows with AI Agents & LLMs

Eric Pritchett, President and COO of Terzo, explains the transformative impact of AI agents and LLMs on workflow orchestration. He contrasts the goal-oriented, flexible nature of AI agents with the limitations of traditional RPA, illustrating how a multi-agent system can automate complex processes like quote generation, marking a paradigm shift in automation capabilities.

Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal

Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal

Preeti Somal from Temporal explains that as AI agents move to production, they face significant reliability and scalability challenges. She introduces Temporal as a platform to abstract away this complexity, allowing developers to build robust, stateful AI agents by focusing on business logic instead of infrastructure plumbing like retries and error handling.