30 Lessons from Building Memory-Aware Agents
A comprehensive summary of lessons learned from building production-ready memory systems for AI agents.
Insights on AI coding agents, persistent memory, and the future of development.
A comprehensive summary of lessons learned from building production-ready memory systems for AI agents.
Practical prompting patterns that leverage persistent memory for better AI responses.
Exploring where the Model Context Protocol is headed and what it means for developers.
Building SaaS applications with isolated memory spaces using MCP in Go.
Optimizing memory retrieval speed with indexing strategies and caching techniques.
How memory improves the quality of AI-generated code through persistent context.
A comprehensive checklist for deploying MCP applications to production.
Adding logging, tracing, and metrics to your MCP-enabled applications.
Building an AI agent that tracks and manages technical debt using persistent memory.
Real-time memory synchronization patterns for high-performance applications.
Troubleshooting common memory issues and debugging techniques for MCP applications.
Building privacy-conscious memory systems that comply with regulations like GDPR.
Managing token costs and optimizing context usage with intelligent memory budgeting.
Scaling memory systems for large codebases with millions of lines of code.
Using persistent memory to maintain consistency during large-scale refactoring.
Quick integration checklist for adding MCP to popular agent frameworks.
Production-ready middleware patterns for MCP servers in Go.
Using memory snapshots for debugging and state management.
Metrics and validation techniques for ensuring memory retrieval quality.
Understanding the key differences between RAG and persistent memory systems.
Coordinating shared memory across multiple AI agents without conflicts.
Security best practices for memory caching to prevent data leaks.
Clarifying the differences and when to use MCP versus vector databases.
Reducing wrong memory retrievals with scoring and filtering strategies.
Best practices for modeling and structuring your memory data.
Building a code review agent that remembers your team patterns and preferences.
A technical guide to building MCP clients in Go for memory management.
Get started with MCP in one line of code. The fastest path to persistent memory.
Understanding the different types of memory and when to use each.
The amnesia problem in AI coding assistants and how MCP solves it.
Learn how to set up CodeMem and give your AI coding assistant persistent memory in under 5 minutes.
Exploring how persistent memory transforms AI coding assistants from tools into true collaborators.
Deep dive into the Model Context Protocol and why it's becoming the standard for AI tool connectivity.