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Rescale used the open-source AI-Driven Development Lifecycle (AI-DLC) and Strands Agents to build an agent that classifies and routes nightly end-to-end test failures. The agent runs in Argo Workflows on Amazon EKS, invokes Claude Opus 4.8 via Amazon Bedrock, queries logs through the Model Context Protocol (MCP), and produced a staged deployment in five days and production deployment within weeks.
GitHub's Copilot app guide explains four ways to give Copilot project-specific context: repository custom instructions (e.g., .github/copilot-instructions.md and path-specific files), agent skills (folders under .github/skills with SKILL.md), custom agents (.github/agents), and Model Context Protocol (MCP) servers that connect Copilot to external tools and data such as Playwright. The article shows how these features can be combined so Copilot follows project conventions, loads repeatable procedures, provides specialized agent roles, and uses external services to interact with or test an application.
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