AI Agent Frameworks: From ReAct to Production (2nd Offering) -JLR Challenge #1 Technical Workshop by: Mahshad Hashemi

Friday, November 21, 2025 - 13:30
School of Computer Science – JLR Challenge #1 Technical Workshop
 

 AI Agent Frameworks: From ReAct to Production (2nd Offering)

Presenter: Mahshad Hashemi

Date: Friday, November 21, 2025

Time: 1:30 pm

Location: Workshop Space, 4th Floor - 300 Ouellette Ave., School of Computer Science, Advanced Computing Hub

 

Abstract

This session explains modern AI agent patterns and frameworks, enabling you to make informed decisions about building or buying. We’ll clarify ReAct (Reason→Act→Observe), plan-and-execute, graph/workflow orchestration, and multi-agent teams; compare popular frameworks (LangGraph, AG2/AutoGen, CrewAI, LlamaIndex, Microsoft Semantic Kernel, Haystack, and Swarm-style); We close with a production checklist, reliability, safety, and cost controls that teams can apply immediately to ship dependable agentic applications.
 

Workshop Outline:
  • Why agents now
  • Core patterns: ReAct vs. plan-and-execute vs. graph/workflow vs. multi-agent
  • Framework landscape & selection matrix
  • Production readiness
  • Safety: policy checks, sandboxed tools, audit trails, human-in-the-loop
  • Cost discipline

 

Prerequisites:

Familiarity with AI terminology (LLM, RAG) is helpful but not required.

 

Biography

Mahshad Hashemi is a PhD candidate in Computer Science at the University of Windsor, specializing in artificial intelligence, graph neural networks (GNNs), and large language models (LLMs). Her work covers data-driven modelling across biology and AI, and she explores practical, workflow-oriented applications. Mahshad has delivered numerous technical workshops for the School of Computer Science’s Advanced Computing Hub, focusing on practical, production-minded AI.

 

Registration Link (Only MAC need to pre-register)