AI Systems Thinking: How to Design Workflows That Scale
Applying systems thinking principles to AI workflow design for scalable, maintainable solutions. Covers systems theory for AI, feedback loop design, emergent behavior in AI pipelines, bottleneck analysis, resilience patterns, multi-agent coordination, workflow orchestration architecture, observability and debugging, and designing AI systems that improve themselves over time.
| Ответственный | OdooBot |
|---|---|
| Последнее обновление | 22.03.2026 |
| Участники | 1 |
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Introduction to Systems Thinking in AI10Уроки -
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What is Systems Thinking?
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What is Systems Thinking? - Quiz10 xp
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Components of AI Systems
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Components of AI Systems - Quiz10 xp
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Designing Workflows
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Designing Workflows - Quiz10 xp
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Feedback Loops in AI
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Feedback Loops in AI - Quiz10 xp
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Implementing Systems Thinking
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Implementing Systems Thinking - Quiz10 xp
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Feedback Loop Design8Уроки -
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Types of Feedback Loops
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Types of Feedback Loops - Quiz10 xp
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Designing Feedback Mechanisms
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Designing Feedback Mechanisms - Quiz10 xp
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Evaluating Feedback Effectiveness
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Evaluating Feedback Effectiveness - Quiz10 xp
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Iterative Improvement Using Feedback
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Project: Implementing Feedback in Workflows
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Emergent Behavior in AI Systems5Уроки -
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What is Emergent Behavior?
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Case Studies of Emergent Behavior
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Designing for Emergent Behavior
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Strategies for Managing Emergence
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Project: Designing for Emergence
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Resilience Patterns in AI Systems5Уроки -
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Understanding Resilience in AI
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Resilience Patterns Overview
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Designing Resilient Workflows
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Testing for Resilience
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Project: Implementing Resilience Patterns
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Workflow Orchestration and Observability6Уроки -
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Principles of Workflow Orchestration
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Principles of Workflow Orchestration - Quiz10 xp
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Designing Observability into Workflows
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Monitoring and Debugging Strategies
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Project: Orchestrating AI Workflows
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Final Project: Building a Self-Improving AI Workflow
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