Definition: Agent Knowledge Training is the system that allows AI agents to learn from your projects, documents, and data. It creates persistent, contextual understanding that makes agents experts in your specific domain.
How Knowledge Memory Works
Traditional AI: Generic knowledge only, no business context, forgets between sessions, same for everyone
Agent Knowledge Memory: Learns your specific domain, understands your context, remembers and compounds, unique to your business
Knowledge Sources
Projects: Connect any Taskade project, agents learn from content, real-time updates, structured understanding
Documents: Upload PDFs, docs, and files, automatic processing, searchable knowledge, version awareness
External Links: Website content, documentation, knowledge bases, API data
Building Agent Memory
Step 1: Select Knowledge Sources - Choose which projects and files your agent should learn from
Step 2: Configure Access - Set what the agent can read vs. what it can modify
Step 3: Train and Test - Ask questions to verify understanding
Step 4: Refine and Expand - Add more sources as needed
Knowledge Compounding
Every interaction strengthens agent memory: Conversations teach communication patterns, corrections improve accuracy, feedback refines responses, usage optimizes relevance.
Related Wiki Pages: AI Agents, Living Knowledge Systems, Workspace DNA