Agentic AI

Design a system where multiple AI agents collaborate to handle customer support tickets. Agents should be able to route tickets, gather information, and escalate when needed.

Create a hierarchical network of agents where parent agents delegate tasks to child agents. Implement coordination, resource management, and result aggregation.

Design an agent that uses tools/APIs to gather information, processes feedback, and iteratively improves its decisions. Implement the ReWOO pattern.

Build an agentic system that learns from past interactions and improves its performance. Include memory management, reflection, and optimization mechanisms.

Implement an efficient memory system for agents to maintain context across long conversations. Handle context window limitations and priority-based memory retrieval.

Design a system to schedule and orchestrate multiple agents working on interdependent tasks. Handle deadlocks, timeouts, and resource constraints.

Build a framework for agents to discover, select, and safely use external tools and APIs. Implement error handling and fallback strategies.

Build an agent that generates and executes code to solve problems. Implement safety constraints, error recovery, and interactive debugging.

Create a comprehensive system to evaluate agent performance including task completion rate, efficiency, safety, and user satisfaction metrics.

Design a swarm of agents that can dynamically adapt to failures. Implement health checks, agent replacement, and workload rebalancing.