Atlassian Corporation today announced new capabilities in Jira designed to advance AI-native software development for engineering organizations. The launch addresses a widening productivity gap where AI usage by engineers has increased by 65%, yet developer velocity gains remain at approximately 10%. The new system provides a single place to plan, orchestrate, and scale agentic work across the full software development lifecycle.

The core of the update is the Atlassian Teamwork Graph, which connects work, teams, goals, code, and knowledge across the software development lifecycle (SDLC). By providing this enterprise context, agents can act with greater relevance. In internal benchmarking, agents enriched by Teamwork Graph showed 44% more accurate results while using 48% fewer tokens than agents operating without that context.

Accelerating Planning and Spec-Definition

The new capabilities help teams turn conversations, requirements, and codebase context into work agents can understand. Jira for Slack allows users to turn conversations into context-rich specs and kick off agent tasks by asking @Jira. The all-new Jira Planner pulls from the Teamwork Graph to define requirements and generate a structured technical spec in Confluence. Additionally, Loom now turns screen recordings and voice instructions into structured action plans that agents can execute.

Delegating and Monitoring Agent Work

Jira now serves as the single source of truth for coding agents, whether execution happens inside Jira, in a cloud agent, or locally. Users can assign work items directly to Claude Code, Cursor, or GitHub Copilot from Jira. The built-in Jira Coding Agent, included in every paid plan, uses Teamwork Graph context to turn work items into ready-to-review pull requests. A new unified view provides visibility into agent sessions across spaces and repos.

Enterprise Deployment and Measurement

To support enterprise adoption, Atlassian introduced autonomous workflows in Jira's automation rule builder. Teams can automate bug fixes, vulnerability remediation, test generation, and documentation updates. A new Agentic Engineering project template helps teams stand up agent-ready projects with pre-configured workflows. Furthermore, the DX AI cost management report unifies spend and token data across third-party tools to calculate an estimated cost per pull request.

Availability and Key Metrics

BTIG analyst Allan Verkhovski has reiterated a Buy rating on Atlassian (NASDAQ: TEAM) while maintaining a price target of $130. The endorsement underscores continued confidence in the company's business trajectory and market position.

Rating and Price Target

The decision to hold the Buy rating reflects a positive outlook on Atlassian's operational performance. The maintained price target of $130 provides a specific valuation benchmark for investors.

This stance aligns with the view that Atlassian's fundamentals remain strong enough to support the current valuation level.