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Fixing some visuals and acrolinx
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learn-pr/wwl/manage-testing-ai-powered-business-solutions/includes/2-recommend-process-metrics-test-agents.md

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## Overview
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This unit teaches solution architects how to design and implement a structured and repeatable process for testing AI agents before production deployment. Testing ensures that agents operate reliably, meet business requirements, and behave predictably across diverse scenarios. You will define key performance metrics, establish standardized test plans, and recommend measurement strategies to validate agent quality, usability, and compliance.
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This unit teaches solution architects how to design and implement a structured and repeatable process for testing AI agents before production deployment. Testing ensures that agents operate reliably, meet business requirements, and behave predictably across diverse scenarios. You'll define key performance metrics, establish standardized test plans, and recommend measurement strategies to validate agent quality, usability, and compliance.
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## 1. Testing Framework for AI Agents
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learn-pr/wwl/manage-testing-ai-powered-business-solutions/includes/3-create-validation-criteria-custom-ai-models.md

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## Overview
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This unit teaches solution architects how to design robust validation criteria for custom AI models used in enterprise environments. You will establish performance, quality, safety, and operational benchmarks to ensure that models behave predictably, meet business goals, align with compliance requirements, and operate effectively across changing data, workloads, and user interactions.
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This unit teaches solution architects how to design robust validation criteria for custom AI models used in enterprise environments. You'll establish performance, quality, safety, and operational benchmarks to ensure that models behave predictably, meet business goals, align with compliance requirements, and operate effectively across changing data, workloads, and user interactions.
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Validation criteria help architects consistently confirm that a model is:
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learn-pr/wwl/manage-testing-ai-powered-business-solutions/includes/8-summary.md

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## Key Takeaways
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AI systems require **new testing practices** due to probabilistic outputs and dynamic data dependency.
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- AI systems require **new testing practices** due to probabilistic outputs and dynamic data dependency.
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Effective validation covers **performance, quality, safety, grounding, and operational behavior**.
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- Effective validation covers **performance, quality, safety, grounding, and operational behavior**.
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Testing must evaluate **agents, prompts, custom models, and multi-app business processes**.
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- Testing must evaluate **agents, prompts, custom models, and multi-app business processes**.
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Copilot can **accelerate test creation**, improve coverage, and standardize templates when guided by clear prompts.
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- Copilot can **accelerate test creation**, improve coverage, and standardize templates when guided by clear prompts.
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Solution architects apply **governance, metrics, and repeatable frameworks** to keep AI solutions reliable throughout their lifecycle.
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- Solution architects apply **governance, metrics, and repeatable frameworks** to keep AI solutions reliable throughout their lifecycle.

learn-pr/wwl/manage-testing-ai-powered-business-solutions/index.yml

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title: "Manage testing AI-powered business solutions"
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summary: Learn to validate and maintain AI-powered business solutions with structured testing frameworks, metrics, and governance.
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abstract: |
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After completing this module, you will be able to:
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After completing this module, you'll be able to:
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- Design structured testing processes for AI agents, custom models, and multi-application scenarios.
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- Define measurable validation criteria for performance, safety, and compliance.
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- Implement scalable testing strategies using Copilot for consistency and coverage.

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