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Atlassian Teamwork Graph

Wiki status: stub. This page is a placeholder created by the 2026-06-01 Jira-AI-agents ingest. The Teamwork Graph is named as one of the agent context substrates but the source post does not architecturally decompose it. To be expanded when a deeper architectural disclosure ingests.

What it is

Atlassian's Teamwork Graph is Atlassian's named cross-product knowledge graph spanning Jira, Confluence, Bitbucket, and other Atlassian products. It surfaces relationships between work items, people, documents, repositories, and decisions — the substrate Atlassian uses to serve cross-product context to AI agents and product features.

Role on this wiki

The Teamwork Graph appears at the work-item-as-agent-prompt altitude: it is one of the three context substrates the agent draws on when running on a Jira work item.

"Each work item is a record of the tasks we need to complete and acts as a prompt for agents. All the context an agent needs is shared using the work item, Atlassian's Teamwork Graph, and the explicit instructions we include in our workflow automations." (Source: sources/2026-06-01-atlassian-how-we-cut-up-to-80-of-engineering-chores-using-ai-agents-in)

The substrate split (per the same source):

Substrate Lifetime Editor Carries
Work item Per task Cron / human / agent Task-specific brief (flag name, paths, desired final state)
Teamwork Graph Long-lived org-wide Atlassian-product-wide Cross-task context (related work, ownership, prior decisions)
Workflow automation prompt Per procedure Workflow admin "How to do this kind of work" instructions

What the source doesn't disclose

  • Access protocol. Whether the agent reads the Teamwork Graph via an MCP server, a REST API, or a Jira-side fetch is not named.
  • Schema. Entity types, relationship types, query language, and freshness contract are not described.
  • Specific data the agent reads. The post lists "the work item, Atlassian's Teamwork Graph, and the explicit instructions" without specifying what cross-product context the agent actually pulls during a flag-cleanup or flaky-test run.

These are deferred to a future ingest if Atlassian publishes a deeper architectural post on Teamwork Graph itself.

Sibling cross-product knowledge graphs

The Teamwork Graph is structurally similar to:

  • Netflix Service Topology — service-dependency knowledge graph for engineer-facing reasoning + automation. Different domain (service-runtime), same shape (knowledge-graph-as-substrate-for-agents and automation).
  • LinkedIn Project ChickenSpot's metadata layer — cross-system metadata graph.
  • GitHub's Code Search graph — cross-repo code reference graph.

The unifying architectural shape is knowledge-graph-as-substrate: expose a cross-product / cross-system relationship graph as a queryable substrate that both human-facing UI and agent loops consume.

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