Beyond the Black Box: Demystifying Agentic AI with Weights & Biases
Join us for a dynamic meetup exploring the cutting edge of AI agentic workflows! This collaborative event with Weights & Biases will dive into both the design principles and practical implementation of autonomous AI systems, along with crucial strategies for ensuring their traceability and reliability in production. Whether you're building your first agent or scaling complex multi-agent systems, this session offers valuable insights for all.
Are you building intelligent agents? Or are you curious about how autonomous AI systems are designed and put into production?
This meetup brings together experts from the community and Weights & Biases to demystify agentic workflows. We'll cover two crucial aspects:
Session 1: Designing & Building Agentic Workflows
The Blueprint for Autonomy: We'll explore fundamental design patterns for agentic workflows, moving beyond simple LLM calls to create truly intelligent and adaptable systems.
Model Context Protocol (MCP): Learn how MCP empowers individual agents to interact with external tools and data sources, providing the necessary context for effective decision-making and action.
Agent-to-Agent (A2A) Communication: Discover how A2A enables multiple, specialized agents to collaborate seamlessly, delegate tasks, and share information to achieve complex goals. We'll discuss how these protocols form the backbone of robust multi-agent systems.
Practical Implementation: I'll share practical examples and strategies for building these workflows, from initial concept to a deployable architecture.
Part 2: Traceability and Observability for Agentic Workflows with Weights & Biases
The Black Box Problem: Agentic systems can be complex and non-deterministic. Weights & Biases will demonstrate how to gain full visibility into your agent's decision-making process, tool usage, and interactions.
Debugging and Iteration: Learn how W&B tools like Weave provide detailed traces of agent rollouts, helping you quickly identify and debug issues, evaluate performance, and iterate faster.
Monitoring in Production: Understand the importance of continuous monitoring for agentic systems to ensure their reliability, safety, and performance in real-world applications.
Evaluation Metrics & Guardrails: W&B will cover how to establish robust evaluation pipelines and implement guardrails to mitigate risks like hallucinations and prompt attacks.
Who Should Attend:
AI/ML Engineers & Developers
Data Scientists
Researchers interested in AI agents