Evaluation-Driven Development: Why QA Is About to Own the AI Stack

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QA teams will play a crucial role in AI development as evaluation-driven development becomes key to differentiating AI models

intermediate Published 11 Jul 2026

Action Steps

Apply evaluation-driven development principles to AI model development
Use metrics such as accuracy and F1 score to evaluate AI model performance
Implement automated testing and validation for AI models
Collaborate with QA teams to identify and prioritize evaluation metrics
Develop and refine evaluation frameworks for AI models

Who Needs to Know This

QA teams and AI developers will need to collaborate closely to ensure effective evaluation and development of AI models

Key Insight

💡 Evaluation-driven development will become a key differentiator for AI models, and QA teams will play a crucial role in ensuring effective evaluation and development

Key Takeaways

QA teams will play a crucial role in AI development as evaluation-driven development becomes key to differentiating AI models

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Title: Evaluation-Driven Development: Why QA Is About to Own the AI Stack

URL Source: https://medium.com/@ashishjsharda/evaluation-driven-development-why-qa-is-about-to-own-the-ai-stack-1a357fab9a63?source=rss------artificial_intelligence-5

Published Time: 2026-07-11T12:46:53Z

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# Evaluation-Driven Development: Why QA Is About to Own the AI Stack

## Prompt engineering was the hype cycle. Eval engineering is the job

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Models are commodities now. Every lab ships a frontier model within weeks of the last one. Claude, GPT, Gemini, Kimi, Qwen — pick your poison, they’re all good enough for most tasks.

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Evaluation-Driven Development: Why QA Is About to Own the AI Stack

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