Show HN: Cognikernel- Local Memory for AI Coding Assistants

Every coding session in Claude Code/Codex starts blindly. It forgets the architectural decisions you made in a session you ran yesterday, a week ago, or a month ago. We end up depending on maintaining a Claude.md file or diff markdown files that these agents rely on their memory features.

I started building CogniKernel to solve this problem. Instead of relying on markdown memory files, CogniKernel observes the coding session itself. It captures decisions, constraints, architectural decisions, project-specific context, etc., as they naturally emerge.

The goal is simple: The agent should remember what it learned yesterday without me telling it what to remember.

Some things it stores automatically:

• Architectural decisions and design rationale
• Project conventions and coding patterns
• Important implementation details
• User preferences and recurring constraints
• Relationships between files, modules, and components

The memory is local-first and designed to work alongside existing coding agents rather than replace them.

A few design goals I had:

• Zero manual memory curation
• Local storage instead of cloud dependency
• Fast retrieval with relevant context instead of dumping everything
• Agent-agnostic architecture so it can work beyond a single coding assistant
• Memory that improves over time instead of growing into an unsearchable log

Was it impactful??? I built 4 full-fledged projects using CogniKernel while switching the auto-memory off from Claude Code and the same project, same prompt, same sessions using the auto memory:

• 30% Less Tokens used
• 4x less read tools used

And a bonus!!! If you use Claude Code and Codex both, you can just start a session in an alternate tool and your memory will carry forward there as well!!!

This was a hobby project and if you use it and it helped your work, please let me know any feedback!