Build a Self-Reflective Deep Research Agent using LangGraph
Build an OpenAI's DeepResearch-like self-improving AI agent that critiques its responses using structured feedback and external search. This hands-on project covers research-backed validation, graph-based workflows, and intelligent decision-making to refine accuracy and efficiency. You'll explore self-critique, adaptive learning, and automated performance optimization to create an AI agent that handles complex, multi-step tasks with precision. Perfect for developers looking to develop reliable, high-quality AI responses with external tool integration and continuous refinement.

Language
- English
Topic
- Artificial Intelligence
Skills You Will Learn
- Python, LangGraph, Generative AI, AI Agents
Offered By
- IBMSkillsNetwork
Estimated Effort
- 45 min
Platform
- SkillsNetwork
Last Update
- July 8, 2025
Implement AI Self-Improvement with Reflexion Agents
What You'll Learn
- Understand Reflexion agents and how they improve AI-generated responses.
- Build a production-ready Reflexion agent that refines its outputs based on structured feedback.
- Develop multi-step AI workflows with LangGraph that integrate self-critique mechanisms for continuous learning.
- Incorporate external validation tools to enhance factual accuracy and research-backed responses.
- Optimize AI decision-making with graph-based workflows and structured improvement loops.
- Ensure robustness with error handling, schema validation, and iteration limits.
What You'll Need
- Basic knowledge of AI and machine learning concepts.
- Familiarity with programming, especially Python.
- A web browser (Chrome, Edge, Firefox, Safari, or Internet Explorer).
Ready to Build Smarter AI?

Language
- English
Topic
- Artificial Intelligence
Skills You Will Learn
- Python, LangGraph, Generative AI, AI Agents
Offered By
- IBMSkillsNetwork
Estimated Effort
- 45 min
Platform
- SkillsNetwork
Last Update
- July 8, 2025
Instructors
Faranak 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 moreKunal Makwana
Data Scientist
I’m a passionate Data Scientist and AI enthusiast, currently working at IBM on innovative projects in Generative AI and machine learning. My journey began with a deep interest in mathematics and coding, which inspired me to explore how data can solve real-world problems. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and leveraging cloud technologies to extract meaningful insights from complex datasets.
Read moreJoseph 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 moreContributors
Hailey Quach
Data Scientist
Hi, I'm Hailey. I enjoy teaching others to build creative and impactful AI projects. By day, I’m a Data Scientist at IBM; by night, an Honors BSc student at Concordia University in Montreal, always exploring new ways to combine learning with innovation.
Read more