Build a 'Memory' Sub-Agent to Give Your AI Assistant a Perfect Memory
Z
Zack Saadioui
8/10/2025
So, you've been using AI coding assistants like Claude, & you've probably noticed something. They're AMAZING at a lot of things, but their memory can be a bit... well, like a goldfish's sometimes. You spend a bunch of time getting it up to speed on your project's architecture, the weird legacy code you have to deal with, & your team's coding conventions. Then, a few interactions later, it's like you're starting from scratch. It's frustrating, right?
Here's the thing: it's not really the AI's fault. These models have a limited "context window," which is basically their short-term memory. Once your conversation gets too long, the older stuff starts to fall out. For complex coding projects, this is a HUGE problem.
But what if you could give your AI a better, more permanent memory? What if you could build a specialized assistant whose only job is to remember everything about your project & remind the other AI agents when they forget?
Turns out, with the new sub-agent features in tools like Claude Code, you can do just that. It's a game-changer, honestly. In this article, I'm going to walk you through how to build your very own custom sub-agent that acts as a long-term memory for your coding projects. It's like giving your AI an external hard drive for its brain. Pretty cool, huh?
Why Bother with a "Memory" Sub-Agent?
First off, let's talk about why this is even worth your time. The core issue is context. When you're deep in a project, there's a ton of implicit knowledge that you & your team share. Things like:
Architectural decisions: Why did we choose a microservices architecture? What are the boundaries between services?
Code conventions: Do we use tabs or spaces? How do we name our variables?
Project history: What were the major changes in the last sprint? What bugs have we fixed recently?
Important files & modules: Where's the code for user authentication? Which file handles database connections?
An AI with a limited context window can't hold on to all of this information. So, you end up repeating yourself, or worse, the AI gives you suggestions that don't fit your project's standards.
A dedicated "memory" sub-agent solves this problem. It's a specialized AI assistant that you can create within your main AI coding tool. Its sole purpose is to store & retrieve information about your project. Think of it as a living, breathing
1
README
file that you can talk to.
Here are the key benefits:
Context Preservation: Each sub-agent has its own separate context window. This means your main conversation doesn't get cluttered with a bunch of project details. The memory agent keeps track of all that stuff, so the other agents can focus on their specific tasks.
Specialized Expertise: You can fine-tune your memory agent to be an expert on your project. You can feed it your project's documentation, architectural diagrams, & even your team's chat logs.
Reusability: Once you've created a memory agent for a project, you can reuse it across different tasks & even share it with your team. This ensures everyone (including the AI) is working with the same information.
How to Build Your Memory Sub-Agent: A Step-by-Step Guide
Alright, let's get into the nitty-gritty. Building a memory sub-agent isn't as complicated as it sounds. Here's a breakdown of the process.
Step 1: Create a Knowledge Base
Before you can create a memory agent, you need to give it something to remember. This is your "knowledge base." It can be as simple as a collection of text files, or as complex as a dedicated database. Here's what you should include:
1
project_overview.md
: A high-level description of the project, its goals, & its tech stack.
1
architecture.md
: A detailed explanation of the project's architecture. Include diagrams if you can (you can describe them in text).
1
coding_conventions.md
: A list of your team's coding standards.
1
important_files.md
: A list of key files & a brief description of what they do.
1
changelog.md
: A running log of major changes, bug fixes, & new features.
The key is to make this information easy for an AI to parse. Use clear headings, bullet points, & simple language.
For a more advanced setup, you could use a tool like SQLite to create a simple database for your knowledge base. This would allow your agent to perform more structured queries, but for now, let's stick with text files.
Step 2: Create the Sub-Agent File
In Claude Code, you can create sub-agents by adding markdown files to a
1
.claude/agents/
directory in your project. Let's create a file called
1
memory_agent.md
& put it in that directory.
Here's a template for what that file should look like: