Hrushikesh Dokala

Hrushikesh Dokala

Software Engineer

Atlan

Hrushikesh is a Software Engineer at Atlan, where he focuses on building intelligent systems that transform how teams search, understand, and interact with complex data. His work involves designing AI-powered search experiences and agentic frameworks that enable contextual, conversational, and explainable interactions in enterprise environments.

He is a core maintainer of AG2 (formerly AutoGen), one of the leading open-source AI agent frameworks, boasting over 700,000 monthly downloads and a thriving community of 20,000+ developers. At AG2, he contributes to developing scalable patterns and developer-friendly tools for building robust, goal-driven, multi-agent applications.

In addition to his professional work, Hrushikesh leads fAIght Club, a Hyderabad-based AI community with over 1,200 members, where he organizes hands-on sessions, talks, and workshops on AI agents, generative AI, and applied machine learning. A regular speaker at AI meetups and conferences, he enjoys bridging the gap between cutting-edge research and real-world engineering.

In this hands-on technical workshop, you'll master the fundamentals of building production-grade AI agent applications with AG2 (formerly AutoGen), a lending  open-source AI Agent framework that is adopted by millions of users and downloaded over 700k times per month. 

You'll explore essential AI agent design patterns and discover how to customize agents for specific domains using reference implementations from the AG2 team. You'll also learn production deployment strategies using FastAgency and build complete agent solutions for real business scenarios.

Through guided exercises, you'll develop AI agent systems that can tackle real-world applications like customer support, marketing research, and data analysis. By the end of the day, you'll have the knowledge to build specialized, scalable agent applications that deliver reliable results in production environments.

What You’ll Learn

  • Fundamentals of AI Agents: Understand the core concepts and architecture of agent-based AI systems
  • AG2/AutoGen Framework: Master the key components and capabilities of AG2 framework
  • AI Agentic Design Patterns:  Key AI Agent design patterns
  • Customized Agent Creation: Build specialized agents for specific tasks and domains. Learn from reference agents built by the AG2 team.
  • Integration Strategies: Connect your agent systems with external tools and APIs, and MCPs
  • Development: Build specialized agents for specific tasks and domains
  • Practical Applications: Apply agent technology to real-world use cases
  • Best Practices: Optimize agent performance and reliability in production environments

 Prerequisites

  • Basic Python programming knowledge
  • Familiarity with LLMs 
  • GitHub account for accessing workshop materials
  • Local development environment with Python 3.9+

Technical Requirements

  • Python 3.9 or higher
  • Git
  • Code editor of choice
  • Virtual environment management (venv, conda, etc.)
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