【#OpenDataSpaces】# Interview Part 3 is live! Break down silos across organizations and borders and turn data into capital. Part 3 explores how Open Data Spaces serves as #ContextLayer# for AI, including #DynamicOntology#. Watch the full version on🔗

Atlassian is becoming the context layer for your business. The formula: Information in. Intelligence out. 🤝 Connectors In: Pull signals from your entire toolchain. 🧠 The Graph: Data is mapped into the Teamwork Graph and compounds daily. 🔄 Context Out: Through our MCP server, that intelligence is pushed to whatever AI your teams already use.

🧠 One answer to "how do you give agents accurate business context?": auto-build ontologies and a knowledge graph from existing data, then serve it via MCP. An open-source project from AWS. Title: Context Ontology Accelerator (aws/context-ontology-accelerator) URL: A semantic context layer that gives AI agents validated business context. Three highlights stand out. 🔎 A Scan → Model → Serve pipeline Connect diverse data sources to discover schemas and ingest documents (Scan), induce formal ontologies and build a unified knowledge graph (Model), and expose it via VKG SPARQL federation and MCP (Serve). It derives semantic structure from existing data, no manual knowledge engineering. ✅ Consistency validated by reasoning engines HermiT and ELK validate ontology consistency, enabling rule-based checks from formal constraints. Agents query validated business rules instead of relying on memorized training data. 🏗 AWS-native and production-minded Deployed via AWS CDK, a VKG powered by Ontop, and namespace RBAC (owner/maintainer/data-steward/data-analyst). API design via Smithy, UI in React + Cloudscape. A solid foundation for running agents within validated context while keeping explainability. #KnowledgeGraph# #AIAgents#

Are you fully agent pilled? We made a plan just for you. Introducing Builder: unlimited external-agent calls for $10/month. Run Cursor, Codex, and Claude Code side by side with MagicPath as your visual context layer as you build. Your design roundtrip is complete.

Every company in the AI era is going to face the same structural question: what do you actually own? Models are commoditizing and agents are making interfaces irrelevant. Your context layer is your identity, but most enterprises don't even know they have one. Between the systems of record that hold your data and the agents that act on it, there's a layer that doesn't have a name in most org charts. It's the semantic intelligence wrapped around your data — the context that tells an agent not just what the data is, but what it means, when it's relevant, and how to use it. Context is what agents eat. Via APIs, via MCP tools, via event streams flowing across your organization. The richest context in any enterprise already exists, buried in API traffic, transactional systems, and years of operational signals.

A friend asked me how to actually build a company that runs on AI agents. I drew him 4 simple diagrams and this is what I told him: For this to work, a few things have to be true. - The humans move up to strategy, taste, and judgment while agents handle the execution. - The whole business becomes readable to agents. Your data, SOPs, pricing, permissions, and decisions all live in one shared context layer. - And you point it at the right work. Repetitive enough for an agent, complex enough that the incumbents never bothered. That's the goldmine. In the old world, the company was the people. They held the knowledge, made the calls, did the work. In this new world, the people become the creatives, the agents become the labor, and the company itself becomes the context layer. That shared brain is the actual company now. The humans and the agents are just plugging into it. Which means the most valuable thing you can build in 2026 is a business so well-documented that an agent can run it. I see it everyday with @MeetLCA. I don't talk about it much publicly, but we've built a SWAT team for building AI-native orgs and AI-native products. The moat is how legible your company is. I drew it all out below.