Imagine agents that learn from every interaction and share those learnings with each other. A support agent discovers that customers prefer step-by-step solutions with code examples. A technical writer agent learns that “Operational Thinking” produces better documentation. These insights shouldn’t be lost—they should become part of a shared culture that benefits all agents, forever. Culture turns these patterns into reusable rules your agents can follow from day one.Documentation Index
Fetch the complete documentation index at: https://agno-v2-shaloo-ai-support-link.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
How Culture Works
Culture provides a shared knowledge layer where agents store universal principles, best practices, and reusable insights that apply across all interactions. Unlike Memory, which stores user-specific facts (“Sarah prefers email”), Culture stores universal knowledge that benefits everyone (“Always provide actionable solutions with clear next steps”). When an agent completes a task, it can reflect on what worked well and distill that into cultural knowledge. Later, when any agent faces a similar situation, it automatically accesses this shared culture and applies those learnings.Notice: Culture is an experimental feature and is subject to change. The current goal is helping agents stay consistent in tone, reasoning, and behavior. The eventual goal is to transform isolated agents into a living, evolving system of collective intelligence.
Why Use Culture?
Culture enables intelligence to compound. Instead of each agent starting from scratch, they build on collective experience:- Consistency: All agents follow the same communication standards, formatting rules, and best practices
- Evolution: Your agent system improves over time as agents learn what works
- Efficiency: Agents don’t re-learn the same lessons repeatedly
- Technical documentation agents that maintain consistent style and structure
- Customer support teams that apply proven problem-solving patterns
- Development assistants that follow your organization’s coding standards
- Content generation that adheres to brand voice and formatting guidelines
Getting Started with Culture
Setting up culture is straightforward: connect a database and enable the culture feature. Here’s a basic setup:- Loads relevant cultural knowledge when starting a task
- Applies that knowledge during reasoning and response generation
- Reflects on the interaction afterward
- Updates or adds cultural knowledge based on what it learned
Three Approaches to Culture Management
Agno gives you three ways to manage cultural knowledge, depending on your needs:1. Automatic Culture (update_cultural_knowledge=True)
After each agent run, the system automatically reflects on the interaction and updates cultural knowledge. This is the recommended approach for most production use cases.
2. Agentic Culture (enable_agentic_culture=True)
The agent gets full control over culture management through built-in tools. It decides when and what to add to the cultural knowledge base.
3. Manual Culture Management
Create cultural knowledge explicitly using theCultureManager or by directly instantiating CulturalKnowledge objects. Perfect for seeding organizational standards.
Storage: Where Culture Lives
Cultural knowledge is stored in the database you connect to your agent. Agno supports all major database systems: Postgres, SQLite, MongoDB, and more. Check the Database documentation for the full list. By default, cultural knowledge is stored in theagno_cultural_knowledge table (or collection for document databases). A custom table name can also be configured. If this table doesn’t exist, Agno creates it automatically.
Manual Culture Retrieval
You can manually retrieve cultural knowledge using theCultureManager:
Cultural Knowledge Data Model
Each cultural knowledge entry in your database contains the following fields:| Field | Type | Description |
|---|---|---|
id | str | Unique identifier (auto-generated) |
name | str | Name/title of the cultural knowledge |
content | str | The main content of the principle/knowledge |
summary | str | Brief summary of the knowledge |
categories | list | Categories (e.g., “communication”, “engineering”) |
notes | list | Additional notes or context |
metadata | dict | Arbitrary metadata (source, version, etc.) |
input | str | Original input that generated this knowledge |
created_at | int | Timestamp when created (epoch seconds) |
updated_at | int | Timestamp when last updated (epoch seconds) |
agent_id | str | ID of the agent that created it |
team_id | str | ID of the team associated with it |
Best Practices
- Start with Manual Seeding: Define core organizational principles, communication standards, and best practices upfront
- Use Automatic Updates in Production: Let
update_cultural_knowledge=Truehandle the evolution naturally - Review Periodically: Check what cultural knowledge has accumulated and refine as needed
- Keep Culture Focused: Culture should contain universal principles, not task-specific details
- Combine with Memory: Use Culture for “how we do things” and Memory for “what I know about you”