Coding Assistant

AI pair programmer that understands your codebase and coding style

advancedTechnologyprogrammingcode-reviewdebuggingdeveloper-tools

Overview

A coding assistant with memory goes beyond autocomplete to become a true pair programmer. It understands your codebase architecture, remembers past decisions, learns your coding style, and maintains context across sessions.

Memory Dimensions

Codebase Knowledge

Deep understanding of the project:

  • Architecture patterns and conventions
  • Module relationships and dependencies
  • Common utilities and where to find them
  • Historical evolution of the codebase
  • Developer Preferences

    Learning individual coding style:

  • Naming conventions (camelCase vs snake_case)
  • Comment verbosity preferences
  • Testing philosophy (TDD, coverage targets)
  • Preferred libraries and patterns
  • Session Continuity

    Maintaining context across conversations:

  • Current feature being developed
  • Recent bugs and their fixes
  • Ongoing refactoring efforts
  • Code review feedback to incorporate
  • Decision History

    Remembering why things are the way they are:

  • Architectural decisions and trade-offs
  • Technical debt and its rationale
  • Past approaches that didn't work
  • Performance optimizations made
  • Use Cases

    Contextual Code Generation

    "Add error handling to this function"

    With memory, the assistant knows:

  • Your project's error handling patterns
  • The custom error classes you've defined
  • Logging conventions in use
  • Whether you prefer exceptions or result types
  • Intelligent Code Review

    Memory enables deeper review:

  • Flag deviations from established patterns
  • Reference similar past code and how it was improved
  • Remember feedback from previous reviews
  • Track recurring issues across PRs
  • Debugging Assistance

    "This API is returning 500 errors"

    With context:

  • Know the API's recent changes
  • Remember similar past issues and resolutions
  • Understand the service's dependencies
  • Reference relevant monitoring and logs
  • Onboarding Acceleration

    Help new team members:

  • Explain why code is structured this way
  • Point to relevant examples in the codebase
  • Share tribal knowledge captured in memory
  • Guide through common workflows
  • Memory Architecture

    What to Index

  • Code semantics: Functions, classes, relationships
  • Documentation: READMEs, comments, ADRs
  • Git history: Commits, PRs, code review discussions
  • Conversations: Past questions and answers about the code
  • Retrieval for Coding

    When the developer asks a question:

  • Semantic search over codebase for relevant code
  • Fetch recent changes to related files
  • Load developer's style preferences
  • Retrieve past conversations on similar topics
  • Privacy and Security

    Code memory raises unique concerns:

  • Proprietary code: Never leak between organizations
  • Secrets detection: Don't store API keys, passwords
  • Access control: Respect repository permissions
  • Audit trails: Track what was accessed and when
  • Example Interaction

    **Without Memory:**

    "How do I add a new API endpoint?"

    "Here's a generic Express.js endpoint example..."

    **With Memory:**

    "How do I add a new API endpoint?"

    "Based on your project's patterns, you'll want to:

  • Add the route in `src/routes/index.ts` following your resource-based naming
  • Create a controller in `src/controllers/` using your BaseController class
  • Add the schema in `src/schemas/` with Zod like your other endpoints
  • Write tests in `__tests__/api/` - I see you aim for 80% coverage
  • Here's a template matching your existing endpoints..."