top of page
Banner_Workshops.png

Mastering AI Agents: Building from Scratch for Real-World Applications

  • Twitter
  • LinkedIn

About the Instructor

Hamza_edited_edited_edited.png

Hamza Farooq

Traversaal.ai /

Optimized AI Conference
CEO / Director

Hamez Farooq is an AI startup founder, educator, researcher, and practitioner with years of experience in cutting-edge AI development. He has worked with global organizations, governments, and top universities, including Stanford and UCLA, to design and develop state-of-the-art AI solutions.

​

Hamez is the author of Building LLM Applications from Scratch, and the founder of Transcensal — a company specializing in Enterprise Knowledge Management and AI Guardrails.

​

Known for his engaging teaching style and deep technical expertise, Hamez has taught thousands of students and professionals to master AI concepts and build production-ready applications.

Time & Location : TBD

This workshop is designed to provide participants with a comprehensive understanding of designing and building AI agents from the ground up. Moving beyond reliance on pre-built frameworks like CrewAI or Autogen, this session emphasizes learning the core mechanics of agent development to enable fully customizable solutions.

​

Led by Hamza Farooq, a seasoned AI expert and educator, the workshop is both technically rigorous and highly practical. Participants will gain hands-on experience in building intelligent agents capable of autonomous decision-making, task orchestration, and real-world problemsolving.

 

By the end of the workshop, attendees will walk away with the knowledge and tools needed to develop robust, scalable, and production-grade AI agents tailored to their specific use cases.

Curriculum

Workshop Outcomes

By participating in this workshop, attendees will: 

  1. Learn Core Fundamentals: Understand the architecture and foundational concepts of AI agents, including reasoning frameworks, decision trees, and multi-agent orchestration. 

  2. Build Agents from Scratch: Gain hands-on experience in coding AI agents from the ground up, bypassing pre-built frameworks for maximum customization. 

  3. Implement Advanced Techniques: Explore cutting-edge approaches like semantic chunking, task decomposition, and performance optimization for agents. 

  4. Deploy in Production: Learn deployment strategies using open-source tools such as vLLM, Ollama, and Hugging Face endpoints for scalable real-world applications. 

  5. Solve Real-World Problems: Work through guided exercises that apply agent development to domains like customer service automation, enterprise RAG systems, and knowledge management. AI agents from scratch 2 

  6. Contribute to Open Source: Learn how to structure and share your work with the broader AI community to accelerate innovation.

Agenda

​

  1. Introduction to AI Agents What are AI agents? Key use cases in enterprise, healthcare, and customer service. Limitations of existing frameworks. 

  2. Building the Core Agent Architecting an agent: Decision-making loops and task planning. Developing basic capabilities: Task execution and environment interaction. 

  3. Advanced Agent Techniques Task decomposition and multi-agent orchestration. Integrating semantic chunking for contextual reasoning. 

  4. Hands-On Development Coding your first agent from scratch: Guided exercise. Fine-tuning and optimizing agent performance. 

  5. Deployment and Real-World Integration Deploying agents using open-source tools (vLLM, Ollama, etc.). Creating scalable and production-ready workflows. 

  6. Stretch Goals Implementing autonomous feedback loops. Exploring multi-agent collaboration for complex problem-solving. 

  7. Wrap-Up Discussion of lessons learned. Resources for continued learning and open-source contributions.

Who Should Attend?

  • AI practitioners and researchers.

  • Developers seeking to transition into advanced agent-building roles.

  • Organizations looking to implement custom AI solutions.

  • Must have knowledge of Python and basic ML.

bottom of page