From Jira to AI-Native Task Management
Using Atlassian and Linear as examples
Using Atlassian and Linear as examples
Using Atlassian and Linear as examples
Center: context and agents
Classic: requirements, status, handoff
AI-native: context, permissions, agents
Anthropic: ~50% agentic activity — dev
Linear: ~25% issues by agents
PDLC: engineering process changes
AI-native org: structure changes
This article: work management
Question: how do we redesign work?
Roles, stages, audit
Roles, stages, artifact handoff
Visibility, responsibility, audit
Atlassian: 350K+, 80% Fortune 500
Works while implementation is manual
Code, tests, docs, triage — with AI
Ticket as one artifact
Two companies show the shift
Atlassian and Linear: different bets
FY23–FY26: strategy shift
FY23: $3.5B+, 260K+ customers
Dec 2023: Atlassian Intelligence GA
FY24: $4.4B, 300K+ customers
May 2024: Rovo launch
From products to apps and agents
Software Collection + Rovo Dev GA
DX acquisition for ~$1B
Enterprise question: where is ROI?
$1.6B — Quarterly revenue
$1B+ — Cloud revenue
5M+ MAU — Rovo users
Stock volatility shows uncertainty
Aug 2024: shares −11%
May 2025: −14%
Feb 2026: −8% after strong quarter
Mar 2026: −1600 employees
From product quality straight to the future model
2023: Similar Issues
2024: design reset
2024: Initiatives
Profitable, 10K+ paying customers
May 2025: MCP server
Summer 2025: Agent Interaction SDK
Aug 2025: Cursor agents
Jun 2025: Series C $82M
Linear Next and Linear Agent beta
Linear Agent — Context and scope
75% — Enterprise with coding agents
5× — Agent-completed work
Enterprise substrate for people and agents
Scale of state + cross-functional context
Rovo MCP: internal/external agents
DX: DevEx and AI adoption
System of record + coordination
A deep AI-native tool for product development
Agents as process participants
Context + backlog + code + sessions
New operating model
Closer form, weaker chain position
Agent platforms claim the universal executor role
Not only Atlassian vs Linear
Cursor Automations: always-on agents
Self-hosted cloud agents
Anthropic: dev dominates agents
Context + permissions + execution
Ticket as one interface
Atlassian: 350K + context + Rovo MCP
AI-code clients expand seats faster
Old process won't outwait AI-native
Bottleneck: decisions + handoff
Product cycle compresses coordination
Atlassian protected; Linear clearer
Context → execution → measurement
Context: one truth about work
Execution: action from context
Measurement: better delivery, less noise
Key sources
Anthropic autonomy; Linear Next.
Linear MCP, SDK, Cursor agents.
Linear Series C; Atlassian FY26.
Atlassian Software Collection; DX.
From Jira to AI-Native Task Management
More materials on this topic are in the "Book Cube" channel
Alexander Polomodov, Technical Director & Fellow, T-Technologies
@Book_Cube