Glean: Your Work Knowledge Agent
Glean is an AI agent with deep context about the user's work — think of it as an oracle for enterprise knowledge. When you're stuck, need background, or want to understand something about the user's company, accounts, colleagues, or work history — ask Glean.
What Glean Knows
Glean has indexed the user's entire work context:
- Communications: Slack messages, email threads, meeting transcripts
- Documents: Google Drive, Confluence, Notion, SharePoint
- Code: GitHub repos, pull requests, commits
- People: Employee directory, org charts, contact info
- CRM: Salesforce accounts, opportunities, contacts
- Tickets: Jira issues, support cases
- Meetings: Calendar events, Gong recordings, Gemini notes
- 100+ enterprise apps connected and indexed
Glean synthesizes across all these sources. It doesn't just search — it thinks and answers.
Core Tool: chat
chat(message="your question here")
chat(message="follow-up question", context=["previous response"])
What Chat Does
- Understands your question — natural language, complex queries, multi-part asks
- Searches across all indexed sources — not just keyword matching
- Synthesizes an answer — connects dots across documents, conversations, people
- Returns cited sources — every claim links back to source documents
Chat Knows Who the User Is
Glean is identity-aware. It knows the authenticated user automatically:
# These just work — no need to specify the user's name or email
chat(message="What am I working on?")
chat(message="Who is my manager?")
chat(message="What meetings do I have today?")
chat(message="What did I discuss with Jane last week?")
What to Ask Glean
Account & Customer Research:
chat(message="Give me an account overview for MongoDB")
chat(message="Who are the key contacts at Tenstorrent?")
chat(message="What's the deal status for Sports Facilities Advisory?")
chat(message="What use cases is Ratio Therapeutics exploring?")
People & Org Questions:
chat(message="Who works on the agent builder team?")
chat(message="Who should I talk to about MCP integrations?")
chat(message="What's Josh Rutberg's background?")
Process & Policy:
chat(message="How do I escalate a support ticket?")
chat(message="What's the onboarding process for new accounts?")
chat(message="How does the AIOM role differ from CSM?")
Historical Context:
chat(message="What happened in my last meeting with Adam Fowler?")
chat(message="What was decided about the OCR issue at SFC?")
chat(message="What's the history of the MongoDB account?")
Synthesis & Strategy:
chat(message="What are the common blockers for agent adoption?")
chat(message="What patterns do successful agent deployments share?")
chat(message="How do other AIOMs handle high-touch accounts?")
Glean's Tools
Under the hood, the Glean agent has access to specialized tools. You don't invoke these directly — Glean decides when to use them:
| Tool | What It Does | |------|--------------| | Search | Finds documents across all indexed sources | | People Lookup | Queries the employee directory and org structure | | Email Search | Searches Gmail with filters (from, to, labels) | | Calendar Lookup | Finds meetings and calendar events | | Document Reader | Retrieves full content from URLs | | Code Search | Searches internal repositories | | Activity Tracker | Shows what the user worked on recently |
Glean orchestrates these automatically based on your question.
How to Use Glean
1. Ask First, Drill Down Later
Always start with chat. If you need more detail, ask follow-up questions:
# Start broad
chat(message="What's the status of the Tenstorrent account?")
# Then drill down
chat(message="What specific use cases are they exploring?",
context=["previous response about Tenstorrent"])
2. Be Specific
Glean is smart, but specificity helps:
Less effective: "Tell me about MongoDB"
More effective: "What are the current active projects with MongoDB and who are the key stakeholders?"
3. Multi-Turn Conversations
Use the context parameter for follow-ups:
response1 = chat(message="What meetings do I have with Ratio Therapeutics?")
response2 = chat(
message="What should I prepare for the next one?",
context=[response1]
)
4. Trust the Citations
Every response includes source links. These are real — use them to verify or dive deeper.
When to Ask Glean
| Situation | Ask Glean | |-----------|-----------| | Starting work on an account | "Account overview for X" | | Preparing for a meeting | "Prep me for my meeting with X" | | Researching a person | "What do I know about X?" | | Understanding a project | "What's the status of X?" | | Finding an expert | "Who knows about X?" | | Recalling a decision | "What was decided about X?" | | Writing a summary | "Summarize my activity on X" | | Investigating an issue | "What's the history of X issue?" |
When NOT to Use Glean
| Need | Use Instead | |------|-------------| | Public/external information | Web search | | Local project files | Read tool | | Info already in conversation | Reference it directly | | Real-time data | Glean indexes periodically | | Speculation/opinion | Your own reasoning |
Limitations
Indexing lag: New documents may take minutes to hours to appear.
Permission-scoped: Glean only sees what the user has access to. If results seem sparse, the user may lack permissions.
Structured data: Returns markdown/snippets, not raw CSVs. For full spreadsheet analysis, have the user upload the file.
External companies: Glean knows about the user's company's interactions with external companies (emails, meetings, CRM data) but doesn't have access to their internal systems.
Examples in Context
Meeting Prep
# Before a customer call
chat(message="Prep me for my call with Adam Fowler at Sports Facilities. Include recent context, open issues, and what we discussed last time.")
Account Research
# New account handoff
chat(message="Give me a full briefing on the Golden Gate Bridge account — adoption status, key contacts, risk factors, and what the previous AIOM was working on.")
Problem Investigation
# Debugging an issue
chat(message="What do we know about the agent error Adam Fowler reported? Include request IDs and any support ticket context.")
Weekly Planning
# Start of week
chat(message="What are my priorities this week based on my calendar, recent activity, and outstanding tasks?")
People Context
# Before a 1:1
chat(message="What should I know before my 1:1 with Josh Rutberg? Include recent discussions and any items I should bring up.")
Philosophy
Glean exists to reduce cognitive load. Instead of:
- Searching Slack, then Drive, then Salesforce, then email...
- Trying to remember which tool has what...
- Manually synthesizing across sources...
Just ask Glean. It handles the complexity. You get the answer.
This is the "second brain" pattern — an AI agent with deep context about your work, always available to consult when you need to understand, remember, or decide.
When in doubt, ask Glean.