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

Friday, October 31, 2025 - 12:00
School of Computer Science – JLR Challenge #1 Technical Workshop

 

AI Agent Frameworks: From ReAct to Production (1st Offering)

Presenter: Mahshad Hashemi

 

Date: Friday, October 31, 2025

Time 12:00 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 so you can make informed build/buy decisions. 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)