Day 1: Foundations of AI Agents
Learned the core concepts of autonomous agents, their architecture, and how they differ from traditional AI models.
Understood the importance of prompt engineering and context management.
Day 2: Building Your First Agent
Hands-on experience creating a simple agent using frameworks like LangChain or AutoGen.
Explored integration with APIs and data sources for dynamic responses.
Day 3: Advanced Capabilities
Implemented multi-agent collaboration for complex workflows.
Learned about memory management and persistent state for long-term tasks.
Day 4: Real-World Applications
Applied agents to procurement workflows, automating vendor communication and document validation.
Discussed ethical considerations and compliance in enterprise environments.
Day 5: Deployment & Scaling
Learned best practices for deploying agents securely in production.
Explored monitoring, performance optimization, and cost management.
Key Takeaways
AI agents can transform repetitive tasks into automated workflows.
Collaboration between agents and humans is critical for accuracy and trust.
Continuous learning and iteration are essential for success.
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