How Rescale built an AI triage agent with Strands Agents and AI-DLC
Machine Learning Blog
This article describes how Rescale built an AI-powered triage agent using the AI-Driven Development Lifecycle (AI-DLC) framework to automate classification and routing of test failures.
- AI-DLC methodology emphasizes AI execution with human decision-making and team collaboration through mob sessions
- Triage agent uses Claude Opus on Amazon Bedrock to classify failures into categories: infrastructure, code bug, flaky test, or environment
- Agent retrieves historical patterns from knowledge base and queries pod logs via Model Context Protocol for supporting evidence
- Built and deployed to staging in five days using structured inception, construction, and operations phases
- Production results show 20% reduction in deployment blocking time and classification accuracy improved from 44% to 68%
- Rescale is scaling AI-DLC across the organization for broader AI-native development practices
AI-DLC provides a structured methodology for teams to move from problem definition to production AI systems while maintaining human oversight and accountability.
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