AGI System Design and Development Training in Madrid, Spain

The AGI System Design and Development Training explores the architectural principles, system design patterns, and research-aligned approaches for building advanced general-purpose AI systems.

The course focuses on scalable AI system design, cognitive architectures, agent frameworks, safety-by-design, and evaluation methodologies, preparing participants to design next-generation intelligent systems responsibly and within current technological and ethical boundaries.

What Do We Mean by AGI?

• Definitions and misconceptions
• Narrow AI vs general intelligence
• Current state of AGI research
• Practical enterprise implications

Architectures for General-Purpose AI Systems

• Modular AI architectures
• Service-oriented vs monolithic AI systems
• AI platform vs AI application
• Layered intelligence architectures

Cognitive Architecture Concepts

• Perception, memory, reasoning, and action loops
• Symbolic + neural hybrid systems
• Blackboard architectures
• Cognitive pipelines

Agent-Based System Design

• Single-agent vs multi-agent architectures
• Planner–executor–critic patterns
• Tool-using agents
• Long-running agent processes

Memory Systems for General Intelligence

• Short-term vs long-term memory
• Vector memory and episodic memory
• Knowledge stores and retrieval systems
• Memory governance and lifecycle

Planning, Reasoning & Decision Systems

• Task planning architectures
• Hierarchical planning
• Reasoning chains and verification
• Goal management systems

World Models & Environment Interaction

• Simulated environments
• Tool and API interaction as environment
• Feedback loops
• Learning from interaction

Multi-Modal Intelligence Architectures

• Vision, language, and audio integration
• Cross-modal reasoning
• Multimodal perception pipelines
• Sensor-to-action architectures

Learning Systems & Adaptation

• Continual learning concepts
• Feedback-driven system improvement
• Online vs offline learning
• Guarded adaptation strategies

Evaluation & Benchmarking for General Systems

• Measuring generalization
• Task diversity benchmarks
• Robustness and stress testing
• Regression testing for intelligent systems

Safety-by-Design for AGI-Oriented Systems

• Alignment concepts
• Human-in-the-loop architectures
• Oversight and control mechanisms
• Containment and capability boundaries

Governance, Ethics & Compliance

• AI governance frameworks
• Documentation and auditability
• Accountability models
• Responsible research practices

Platform Engineering for AGI-Oriented Systems

• Building extensible AI platforms
• Plugin and tool ecosystems
• Model abstraction layers
• Versioning and lifecycle management

Research-to-Production Pathways

• From prototypes to platforms
• Managing experimental features
• Risk assessment for advanced capabilities
• Controlled rollout strategies

Hands-on Exercises

Summary and Conclusion