Building Reliable AI Assistants That Don't Break
Engineering robust, production-ready AI assistants and agents that work reliably in real business environments. Covers prompt engineering fundamentals, error handling and graceful degradation, testing and validation frameworks, context management, memory and state patterns, tool use and function calling, monitoring and observability, cost optimization, and building assistants that handle edge cases without failing.
| Responsible | OdooBot |
|---|---|
| Last Update | 03/24/2026 |
| Members | 1 |
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Error Handling and Graceful Degradation6Lessons ·
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Understanding Errors in AI
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Understanding Errors in AI - Quiz10 xp
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Implementing Error Handling Strategies
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Graceful Degradation Techniques
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Testing Error Handling Mechanisms
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Project: Build a Resilient AI Assistant
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Context Management and Memory Patterns6Lessons ·
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The Role of Context in AI
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The Role of Context in AI - Quiz10 xp
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Implementing Context Management
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Memory Patterns for AI Assistants
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Testing Context Management
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Project: Build a Context-Aware AI Assistant
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Testing and Validation Frameworks5Lessons ·
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Introduction to Testing Frameworks
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Unit Testing Your AI Assistant
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Integration Testing for AI Systems
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Validation Strategies for AI Assistants
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Project: Create a Testing Framework for AI Assistants
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Monitoring and Observability5Lessons ·
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Introduction to Monitoring AI Systems
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Implementing Monitoring Tools
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Analyzing Performance Metrics
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Designing Observability Strategies
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Project: Build a Monitoring System for Your AI Assistant
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Cost Optimization and Edge Case Handling5Lessons ·
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Understanding Cost Drivers in AI Systems
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Implementing Cost Optimization Techniques
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Handling Edge Cases in AI Systems
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Testing Cost Optimization and Edge Case Handling
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Project: Optimize Your AI Assistant for Cost and Edge Cases
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