How Content Assistant raised the design quality bar without slowing us down

This post details the development and impact of the Content Assistant, an AI agent built on Atlassian's Rovo platform. It describes how the agent drafts UX copy, surfaces content standards, and integrates with existing workflows (Slack, Confluence, Jira). The post highlights the agent's success in improving content quality and governance, not just speed. It outlines the 'AI-native content system' architecture with four layers: context stores, agents and workflows, an operating model with trust tiers, and governance/feedback loops. The post emphasizes the importance of structured context stores for LLMs and feedback loops for continuous improvement. It also mentions the use of Rovo's capabilities for Jira actions and the integration with other Atlassian apps.