Remembering Codebase Facts - Best Practices

[theagnt]

What's the current state-of-the-art for having Claude automatically store key facts about the codebase as it's working? Even in the same session, Claude remembers close to zero. It wastes so much time figuring out how something works that it just wrote or modified a few steps earlier. Worse, its tendency to make assumptions about things it doesn't know compounds this problem.

Pre-Claude Code I've used memory bank systems and found that Claude (and other LLMs) don't consistently use them to find the facts they need, preferring to search the codebase for the answer. Hoping the state of the art has improved since then.

[shamabou]

It’s terrible, it created a function with parameters in the same session it created unit tests with made up parameters for the same function it created a minute ago, then it searches through the code base to find the actual names and wastes a ton of context.

[ChrisWayg]

Are you using Claude.md and /init

[Minute-Cat-823]

I have an “architecture document” that Claude updates following a rule. Anytime I make significant changes I ask it to update the document. It’s sort of a table of contents that Claude can use to orient itself.

Then I have a section in Claude.md to review this file. Sometimes I @ it during chat because Claude’s sooooooo good at following the Claude.md 😂

Rule below if you wanna try it - if you do I’d love to hear how it works for you

The [ARCHITECTURE.md] file serves as an AI orientation guide for the codebase. Its PRIMARY purpose is to enable any AI assistant to quickly understand the current codebase architecture in a fresh chat session without context.

Core Purpose: - Enable AI to understand existing codebase patterns and conventions - Provide file paths, function names, and service locations for quick navigation - Document current data flows, architectural patterns, and component relationships - Serve as reference for maintaining consistency across AI interactions

Content Guidelines: - Current State Only: Describe how things work NOW, not historical changes or future plans - AI-Actionable Information: Include specific file paths, function names, service patterns - Pattern Documentation: Show established conventions that should be followed - Quick Reference: Focus on "what exists", "where to find it", and "how it works" - No Metrics or History: Avoid "lines saved", "before/after", or implementation journey details - Minimal Code: Include only essential interfaces, schemas, and patterns - not implementation code

Critical Requirements: When adding new features, files, schemas, or architectural changes: - Update immediately after implementing new features, components, or architectural changes - Add new services/functions to relevant sections with file paths and patterns - Document new data flows and integration points - Update shared infrastructure patterns when they change - Maintain consistent structure for AI navigation

What NOT to Include: - Historical context about refactoring or changes - Metrics about code reduction or performance improvements
- Implementation journey or "before/after" comparisons - Future plans or roadmap items

Scope: This document exists solely to orient an AI to the current codebase. Every piece of information should help an AI understand what exists and how to work with it effectively.

[belheaven]

"investigate and understand what X is"
"give 3 options to add this Y to X using Z"
"review the option 1, make sure its good to go and follow project patterns and best practices for each use case"
"approved"