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AI-Powered Development Workflow.md
AI-Powered Development Workflow
Our team was losing too much time on repetitive development tasks - searching documentation, waiting for code reviews, and explaining the same business patterns over and over to new developers. We implemented a complete AI-powered development workflow using two key components: 🔧 Amazon Q Custom Agents We created specialized agents: one for Scala/Spark development, another for CI/CD. Pre-loaded with business rules and code patterns, they provide instant contextual assistance without needing explanations. 🔍 Automated AI Code Review GitHub Action that automatically reviews every pull request using custom prompts tailored to our functional programming standards, providing detailed feedback before human review. Key Insight: Generic AI isn't enough. The magic happens when you customize AI with your domain-specific knowledge, code patterns, and business rules.
Achievements:
  • Faster development - instant expert assistance available 24/7
  • Consistent code quality - every PR receives thorough automated review
  • Better onboarding - new developers get expert guidance from day one
  • More time for creative work - AI handles routine checks
  • Significant reduction in code review time and feedback cycles
Tech Stack:
Amazon Q DeveloperGitHub ActionsScalaApache SparkFunctional ProgrammingCI/CDCustom AI AgentsPrompt Engineering
Robert Huaman Caceres - Software Engineer