> ## Documentation Index > Fetch the complete documentation index at: https://docs.duckie.ai/llms.txt > Use this file to discover all available pages before exploring further. # Context, Knowledge, and Memory > Understand what Duckie knows now, what it can look up, and what carries forward in a ticket Duckie answers well when it knows the current situation, can search the right company information, and can continue an ongoing conversation without starting over. Use **context** for the current situation, **knowledge** for reusable facts, and **memory** for continuity across turns. ## The Difference | Concept | Question it answers | Examples | | ---------------- | ----------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | | **Context** | What is happening in this conversation? | Customer message, prior conversation history, ticket metadata, source channel, tool results, workflow outputs | | **Knowledge** | What does our company know about this topic? | Product docs, policies, troubleshooting steps, FAQs, internal procedures, approved answers | | **Memory** | What has Duckie already learned or done in this ongoing ticket? | The order number the customer provided, a prior lookup result, a question Duckie already asked | | **Agent Tables** | What structured working set should an autonomous agent query or update? | Per-ticket checklist rows, run scratchpads, workspace queues, agent-specific review lists | ## Context: What Duckie Knows Right Now Context is the situation around the current run. It can include: * The customer's latest message * Prior conversation history * The source channel and ticket metadata * Customer or account details from connected systems * Tool results * Workflow outputs * Handoff details from a parent run or sub-agent Context is temporary and situational. It changes from run to run. Example: the customer is writing from a Zendesk ticket, already shared an order number, and the order lookup shows the shipment is delayed. ## Knowledge: What Duckie Can Look Up Knowledge is reusable information Duckie can search or read before answering. Use knowledge for: * Product facts * Help center articles * Refund, billing, security, and account policies * Troubleshooting steps * Common questions * Internal procedures * Approved answers Manage this in **Train > Knowledge** with Knowledge Base sources, Custom Knowledge, Support Knowledge, Knowledge Tags, and Gaps. Example: your refund policy, password reset steps, and known outage response belong in knowledge, not only in one agent's instructions. ## Memory: What Carries Forward Memory is continuity within an ongoing conversation or ticket. For autonomous agents, Duckie can use prior conversation context and saved run memory to continue work across turns on the same ticket. Example: if Duckie already asked for an order number and the customer replies with it later, memory helps Duckie continue instead of starting over. ## Agent Tables: Structured Working Memory [Agent Tables](/concepts/agent-tables) are for structured rows that an autonomous agent should query or update during a run. Use Agent Tables when the agent needs a scoped table-like working set: a checklist, queue, candidate list, extracted facts table, or status tracker. Use ordinary memory when the agent only needs conversational continuity. ## How They Work Together For a failed payment question: 1. Context tells Duckie the customer's plan, billing ticket, and latest message. 2. Knowledge gives Duckie the payment retry policy. 3. A tool lookup returns the current invoice status. 4. Memory helps Duckie remember that it already checked the invoice when the customer follows up. 5. An Agent Table can track structured follow-up rows if the process needs a checklist or review queue. ## Common Mistakes * Do not put permanent policy only in agent instructions. Put it in knowledge. * Do not expect memory to replace clear knowledge articles. * Do not pass every detail to a sub-agent. Pass only the Conversation history or Additional context it needs. * Do not rely on customer-provided identifiers alone for account actions. Use verified context and scoped tools. ## Where to Manage Each | Area | Where to work | | ------------ | --------------------------------------------------------------------------------------------- | | Context | Analyze > Runs, workflow inputs, source metadata, tool outputs, custom tool Context Variables | | Knowledge | Train > Knowledge, Knowledge Tags, Knowledge Gaps, connected sources, Custom Knowledge | | Memory | Multi-turn testing, Test > Playground, Test > Replay Chats, Test > Batch Test, Analyze > Runs | | Agent Tables | Build > Tables and the Tables section in autonomous agent configuration | ## Related Docs Manage the information agents can search. Scope knowledge, runbooks, workflows, tools, and callable agents. Give autonomous agents scoped structured working memory. Pass Conversation history and Additional context to child agents. Inspect context, steps, tool calls, and outcomes.