Build with AI: Developing a Code Review Assistant

Build with AI: Developing a Code Review Assistant

About Course

Explore the intricacies of Python programming with an emphasis on mastering data structures and gain a competitive edge by learning to write cleaner, more efficient, and highly organized code. This course helps you analyze and manipulate data effectively using Python’s powerful features, and is ideal for software developers, data scientists, and tech enthusiasts eager to refine their coding skills and elevate their programming knowledge.

Learn about key concepts such as lists, dictionaries, and sets, while understanding how they can enhance your code efficiency. Delve into the optimization of algorithms to improve your problem-solving capabilities. Uncover best practices for organizing and managing data in complex systems. Check out this course to learn how to confidently tackle coding challenges with improved speed and precision, making you a valuable asset in any development team.

     

Course content

videoCourse introduction and learning objectives
videoAutomated code review: Reducing latency and cognitive load
videoSystem architecture: Event-driven patterns for PR analysis
videoGitHub Actions: Workflow orchestration and YAML configuration
videoLLM integration: Token optimization and context window management
videoModule summary and key architectural patterns
videoStrategic approach to automated review systems
videoPMAT architecture: Parser design and AST analysis
videoCodifying review standards: Linting rules and semantic analysis
videoComparative analysis: Existing GitHub Action implementations
videoPrompt engineering: Temperature control and response determinism
videoModule summary and tool selection criteria
videoImplementation strategy and development workflow
videoDocumentation-driven development: API contract definition
videoBuilding the action: TypeScript implementation and Docker packaging
videoTest harness development: Mocking GitHub API responses
videoLocal testing: Act runner and environment simulation
videoModule summary and performance benchmarks
videoProduction deployment considerations
videoGitHub Action registration: Permissions and security boundaries
videoPR integration: Webhook handling and comment threading
videoProduction challenges: Hallucination mitigation and rate limiting
videoAdvanced features: Incremental diff analysis and caching strategies
videoModule summary and production metrics
videoDistribution strategy and marketplace requirements
videoTechnical documentation: Action metadata and usage examples
videoMarketplace publication: Versioning and semantic release
videoCourse conclusion and future enhancements

Munich Ventures Academy

Erna Stepanyan

Erna Stepanyan

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