Asking Effective Questions

The more specific your questions, the better Conversational Search can find relevant memories and provide accurate answers.

Use Specific Keywords

Include unique keywords related to what you're looking for—project names, ticket numbers, package names, or specific topics.

Good: "What is the status of project Aurora?"

Bad: "What is the status of my project?"

If you can't remember specific keywords, try asking: "Give me the titles of all the project documents I've been working on last month" to find keywords for more specific prompts.

Include Time Ranges

Specify when something happened to narrow down results. Conversational Search stores up to 9 months of memories.

Examples:

  • "What decision did we make about the database schema last week?"
  • "What were the plans I received in December?"
  • "What was I debugging yesterday afternoon?"

Mention Source Applications

Reference specific apps to separate similar content across different sources.

Example: "What did Sarah and I discuss in Teams about the deployment?"

This separates Teams conversations from emails or document comments.

Combine Techniques

Mix keywords, time ranges, and applications for the most accurate results.

Example: "What is the URL for the Project Aurora document I discussed in Teams with Sarah last Thursday?"

This combines the keyword "Project Aurora," the application "Teams," the person "Sarah," and the time "last Thursday" to narrow down results precisely.

Use Filters Instead of Prompts

If you know the exact source app or time range, use the Sources and Time Ranges filters instead of describing them in your prompt. Filters are more accurate than natural language time expressions. See Scoping Your Prompt for details.

Example Prompts

* "Show examples of React Context usage." * "What was my last implementation of API error handling?" * "Have I previously optimized rendering performance in React components?" * "Track the evolution of the dashboard feature." * "Review documented challenges with the payment system." * "Show the decisions made around UI updates for the onboarding flow." * "Find recent bookmarks about Kubernetes." * "What resources did I save recently related to Python decorators?" * "Show notes taken about GraphQL in March." * "Show code review comments related to database indexing." * "Did we finalize naming conventions for the latest API endpoints?" * "What feedback did I leave on recent pull requests?" For MCP-specific prompting patterns, see the [MCP Prompting Guide](/products/mcp/prompting) and the [LTM Prompting Guide](/products/quick-guides/ltm-prompting).

Learn how to scope your searches with filters in Scoping Your Prompt.