Smart Fusion

For product owners who need throughput, not another meeting

Move tickets forward without pulling a developer off their task.

Refine your issue with technical knowledge from your project and let AI Developer pick up a the issue to create the implementation.

Use the "Inquiry" feature to ask AI Developer to refine the ticket in regards to technical feasibility or clarity.

Example "Inquiry" prompt
Interview me about this issue/ticket before implementing it, as if I'm the product owner, not the engineer. I don't know the codebase — phrase every question, recommendation, and alternative in plain language: user-facing behavior and business tradeoffs, not implementation. Never mention model/class/variable names, file paths, or code structure anywhere in the interview — translate any technical finding into its plain-language consequence instead.

Explore the codebase to answer as many questions as possible yourself — don't ask what you can discover by reading.

Output only the questions. No preamble, no narration of what you explored or which tools worked or failed, no summary of next steps at the end. This is an ephemeral interview, not a deliverable — don't create, save, or reference any plan file.

List remaining open questions, grouped by dependency: order each branch so earlier questions gate later ones, and mark conditional questions ("Only relevant if you chose X above").

For each question, in plain language throughout: the tradeoff, your recommended answer and why, the realistic alternatives, and its stakes — HIGH (changes what the feature does or how it fits the existing product) or LOW (safe default, no user-visible ambiguity).

Surface HIGH-stakes questions up front. Collapse LOW-stakes ones into a secondary section with assumed defaults to skim and override.

AI Developer panel on a Jira issue with Implement, Enhance Description, and Inquiry actions

What moves without a developer's time

Clarify and verify requirements against real code

Ask questions on any ticket to clarify scope, optimize requirements, or verify technical feasibility against your repository—answered instantly, as if a developer on your team responded directly.

Assign your Jira issues to AI Developer

Seamlessly integrate AI-assisted development into your workflow to resolve tasks and prototype solutions in minutes, directly within Jira.

A real branch to review

Working code lands on a dedicated branch, ready whenever a developer has a moment to look.

How it works

Clarify and verify requirements

AI Developer checks the requirements against your repository.

Assign the issue

Click Assign to AI Developer on any Jira issue — no extra setup per ticket.

AI analyzes the task

It reads the issue summary and description to understand what's being asked.

AI generates a solution

Claude Code or OpenAI Codex writes the implementation — code, tests, and dev notes as applicable.

Code pushed to branch

The implementation is committed and pushed to a dedicated branch in your configured repository.

Comment posted on issue

A comment on the Jira issue links the branch and summarizes what changed, so the team can review.

Comment feedback to refineOptional

Not quite right? Mention AI Developer in a comment with what to change, and it updates the same branch.

Developer reviews & merges

A developer reviews the branch and merges it on their own schedule — this step always happens, it's never skipped.

What this doesn't change

Who reviews the code before it ships?
A developer still does. AI Developer pushes its implementation to a branch and comments on the issue — nothing merges or deploys on its own. It moves the ticket from "not started" to "ready for review," it doesn't remove review from the process.
What if the first implementation isn't right?
Leave a comment on the issue mentioning AI Developer with what should change. It updates its latest implementation on the same branch — no need to start over.

Keep tickets moving

Available on the Atlassian Marketplace for Claude Code and OpenAI Codex.