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Disclaimer: This post was originally published on Azure with AJ and has been reproduced here with permission. You can find the original post here.
One of the biggest challenges with AI coding assistants has been their stateless nature with every interaction starting from scratch, requiring developers to repeatedly explain coding conventions, architectural patterns, and repository-specific knowledge. GitHub has just changed the game with the public preview of agentic memory for GitHub Copilot, a revolutionary capability that allows AI agents to remember and learn from your codebase over time.
This isn’t just another incremental improvement, it’s a fundamental shift toward truly intelligent AI assistants that grow smarter with every interaction. Let’s dive into how this groundbreaking feature works and why it’s set to transform how we collaborate with AI in our development workflows.
The Problem: Context Lost in Translation
Picture this scenario: You’re working on a complex enterprise application with specific coding conventions, database connection patterns, and synchronised configuration files. Every time you interact with GitHub Copilot, you find yourself explaining the same architectural decisions and coding standards. The AI produces decent code, but it lacks the deep understanding of your repository’s unique patterns and requirements.
Traditional AI assistants suffer from “contextual amnesia” – they can’t retain knowledge between sessions. This means:
- Repetitive explanations: Constantly re-explaining coding conventions and patterns
- Inconsistent suggestions: AI recommendations that don’t align with established codebase patterns
- Missed relationships: Failing to understand dependencies between files that must stay synchronised
- Generic responses: One-size-fits-all solutions that don’t respect repository-specific best practices
While we can leverage GitHub Copilot’s instructions to provide context, this approach is limited. Instructions can become lengthy, hard to maintain, and still don’t solve the problem of retaining knowledge across sessions.
Introducing Agentic Memory: AI That Learns and Remembers
Agentic memory represents a paradigm shift in how AI assistants work with code. Instead of starting fresh with each interaction, Copilot now builds and maintains a persistent understanding of your repository through “memories”. Tightly scoped pieces of knowledge that it discovers and validates over time.
How Memories Are Created
The memory system works through what GitHub calls “just-in-time verification”. Here’s the elegant process:
graph TD
A[Copilot Agent Working] --> B{Discovers Actionable Pattern}
B -->|Yes| C[Create Memory with Citations]
B -->|No| D[Continue Work]
C --> E[Store Memory in Repository]
E --> F[Available for Future Sessions]
style A fill:#2563eb,stroke:#1e40af,stroke-width:3px,color:#fff
style C fill:#059669,stroke:#047857,stroke-width:3px,color:#fff
style E fill:#94a3b8,stroke:#64748b,stroke-width:2px,color:#0f172a
style F fill:#94a3b8,stroke:#64748b,stroke-width:2px,color:#0f172aWhen Copilot discovers something worth remembering, it creates a structured memory entry:
{
"subject": "API version synchronisation",
"fact": "API version must match between client SDK, server routes, and documentation.",
"citations": [
"src/client/sdk/constants.ts:12",
"server/routes/api.go:8",
"docs/api-reference.md:37"
],
"reason": "If the API version is not kept properly synchronised, the integration can fail or exhibit subtle bugs. Remembering these locations will help ensure they are kept synchronised in future updates."
}
Memory Validation and Self-Healing
The brilliant aspect of this system is its self-healing nature. Before applying any stored memory, Copilot validates it against the current codebase:
graph TD
A[Agent Starts New Session] --> B[Retrieve Repository Memories]
B --> C[Check Citations Against Current Code]
C --> D{Citations Valid?}
D -->|Yes| E[Apply Memory Knowledge]
D -->|No| F[Store Corrected Memory or Discard]
E --> G[Continue with Enhanced Context]
F --> G
style A fill:#2563eb,stroke:#1e40af,stroke-width:3px,color:#fff
style C fill:#f59e0b,stroke:#d97706,stroke-width:3px,color:#fff
style E fill:#059669,stroke:#047857,stroke-width:3px,color:#fff
style F fill:#94a3b8,stroke:#64748b,stroke-width:2px,color:#0f172a
style G fill:#94a3b8,stroke:#64748b,stroke-width:2px,color:#0f172aThis real-time verification ensures that memories remain accurate even as code evolves, branches change, and files are refactored.
Privacy and Security: Is it safe to use?
One of the first questions that comes to mind with any AI memory system is privacy and security. Is it safe to let an AI remember details about my codebase?
What I had to understand is that Copilot Memory stores repository-scoped memories only. This means memories are tied to a specific repository and can only be used by Copilot operations on that same repository.
Key points:
- Repository Isolation: Memories are strictly scoped to individual repositories (not shared across repositories or orgs)
- Permission-Based Creation: Only contributors with write permissions can create memories
- Access Control: Memories can be used by other users with appropriate repository access, but not outside that repository
- Management Tools: Repository owners can view and delete stored memories via repository settings
- Automatic Expiry: Memories automatically delete after 28 days unless refreshed through validation
This ensures that sensitive repository knowledge stays within the appropriate boundaries while enabling powerful AI assistance.
Current Availability and Getting Started
Agentic memory is currently available in public preview for:
- Copilot Coding Agent: Enhanced task completion with repository-specific knowledge
- Copilot Code Review: Smarter pull request reviews based on learned patterns
- Copilot CLI: Context-aware command-line assistance
Enabling Memory for Your Team
The feature is opt-in and available for all paid Copilot plans:
For Individual Users (Copilot Pro/Pro+):
- Navigate to Personal Copilot Settings
- Under “Features”, find “Copilot Memory”
- Select “Enabled” from the dropdown
For Organisations and Enterprises:
- Go to Organisation/Enterprise Settings
- Navigate to Copilot policies
- Enable Copilot Memory for your team
Repository Management: Repository owners can review and manage stored memories via: Repository Settings > Copilot > Memory
Implementation Best Practices
To maximise the value of agentic memory in your development workflows:
1. Start with High-Impact Repositories
Enable memory on repositories with:
- Complex coding conventions
- Synchronised configuration files
- Specific architectural patterns
- Multiple team contributors
2. Monitor Memory Quality
Regularly review stored memories to:
- Remove outdated or incorrect memories
- Validate that learned patterns align with current practices
- Ensure memories reflect your team’s coding standards
3. Leverage Cross-Agent Benefits
Use multiple Copilot features together:
- Let Code Review agents learn from expert developer patterns
- Allow Coding Agent to benefit from review insights
- Use CLI with enhanced repository context
4. Educate Your Team
Ensure team members understand:
- How memories are created and validated
- The privacy and security model
- How to review and manage repository memories
Conclusion: A New Era of Intelligent Development
GitHub Copilot’s agentic memory represents a fundamental evolution in AI-assisted development. By solving the “contextual amnesia” problem, it enables AI agents to become true collaboration partners that grow more valuable over time.
The beauty lies not just in the technical implementation, but in how it transforms the developer experience. No more explaining the same patterns repeatedly. No more generic suggestions that miss repository-specific context. Instead, you get AI assistance that truly understands your codebase and respects your team’s established practices.
As we embrace this new era of agentic AI, the question isn’t whether to adopt these capabilities, but how quickly we can integrate them into our development workflows to unlock their full potential.
Have you enabled agentic memory in your repositories yet? What patterns do you hope Copilot will learn from your codebase? Share your experiences and thoughts in the comments below.
