Reflexion Agent 101
LangGraph ReAct agents: end the era of unreliable AI responses. Build nutritional advisors that actively research, critique, and improve their answers through systematic self-reflection using the powerful Reflexion framework. Learn to create AI systems that don't just respond but iterate, validate, and refine their expertise like human professionals who double-check their work before giving advice.

Language
- English
Topic
- Artificial Intelligence
Skills You Will Learn
- Artificial Intelligence, AI Agent, LangGraph, Machine Learning, LLM
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- July 8, 2025
What You'll Learn
- Implement the Reflexion framework: Master the core technique that enables AI agents to self-critique and iteratively improve their responses, a crucial skill for building reliable AI systems.
- Design sophisticated agent workflows: Use LangGraph to create complex, cyclical processes where agents can loop through reflection, research, and revision until reaching satisfactory conclusions.
- Structure AI outputs with Pydantic: Learn to enforce specific response formats that ensure agents provide structured self-critiques, search queries, and evidence-based revisions.
- Integrate external knowledge sources: Connect agents to real-time information through web search APIs, enabling them to access current research and evidence beyond their training data.
- Build production-ready agent architectures: Create robust systems with proper error handling, iteration limits, and structured data flows that can scale to enterprise applications.
Who Should Enroll
- AI/ML Engineers building production systems who need to ensure their agents provide reliable, evidence-based responses rather than hallucinated or outdated information. This project teaches essential patterns for creating trustworthy AI systems.
- Data Scientists working in healthcare, finance, or research domains where AI recommendations must be backed by evidence and subject to rigorous validation processes.
- Product Managers and Technical Leaders who need to understand the architecture behind next-generation AI systems and how to build agents that can be trusted with critical decision-making.
- Developers with LLM experience who want to move beyond simple prompt engineering to sophisticated agent architectures that can handle complex, multi-step reasoning tasks.
Why Enroll
What You'll Need

Language
- English
Topic
- Artificial Intelligence
Skills You Will Learn
- Artificial Intelligence, AI Agent, LangGraph, Machine Learning, LLM
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- July 8, 2025
Instructors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreFaranak Heidari
Data Scientist at IBM
Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.
Read moreContributors
Abdul Fatir
Data Scientist
Abdul specializes in Data Science, Machine Learning, and AI. He has deep expertise in understanding how the latest technologies work, and their applications. Feel free to contact him with questions about this project or any other AI/ML topics.
Read more