Autonomous Agent Systems at Scale
Build fully autonomous AI systems that can operate with minimal human intervention. Cover long-running agents, self-improvement, and safety constraints.
Prerequisites
- Advanced experience with multi-agent systems
- Strong software engineering background
- Understanding of ML safety and alignment concepts
Who Should Attend
- AI/ML Engineers
- Software Developers building AI products
- Technical Leads evaluating agent frameworks
- Senior engineers scaling production systems
- Technical architects designing enterprise solutions
Course Outline
- 1Designing for autonomy: when agents should act independently
- 2Long-running agent orchestration and state management
- 3Self-reflection and self-improvement patterns
- 4Safety constraints and guardrails for autonomous agents
- 5Human oversight patterns: approvals, escalations, and interventions
- 6Handling uncertainty and graceful degradation
- 7Distributed agent systems and fault tolerance
- 8Ethical considerations for highly autonomous AI
Learning Outcomes
- Build agents that operate autonomously for extended periods
- Implement self-reflection and improvement mechanisms
- Design effective safety constraints and guardrails
- Handle failures gracefully in autonomous systems
- Balance autonomy with human oversight requirements
- Deploy fault-tolerant distributed agent systems
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