🤖 [AI Proposal] Reduce development time for developers by automating code generation from project management tickets

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Experiment

Problem to be solved

User problem

Developers spend significant time setting up initial code structures for common feature requests, which can be time-consuming and repetitive.

Solution hypothesis

By integrating AI-powered code generation (like Devin or Cursor AI composer) with project management tools (Linear or Jira), we can automate the initial code creation process, significantly reducing the time developers spend on setting up new features.

Assumption

• AI models like Devin or Cursor AI composer are capable of generating relevant, high-quality code based on ticket descriptions.
• The generated code will serve as a useful starting point for developers, requiring minimal adjustments.
• The integration with Linear and Jira is technically feasible and can be implemented without major hurdles.

Personas

• Software Developers
• Project Managers
• Tech Leads

Proposal

Develop a feature that allows users to generate code directly from project management tickets (Linear or Jira) for common feature requests. This automation will streamline the development process and increase productivity.

Key components:

1. Add a "Generate Code" button to Linear and Jira ticket interfaces
2. Integrate with Devin or Cursor AI composer for code generation
3. Automatically create a merge request with generated code
4. Provide a preview of the generated code in the merge request
5. Use comments to provide feedback to AI agent

Success

We will measure the success of this experiment based on the following metrics:

1. Time saved: Compare the average time taken to set up initial code structures manually vs. using the AI-generated code.
2. Usage rate: Percentage of eligible tickets where developers choose to use the AI code generation feature.
3. Code quality: Measure the amount of changes required to the AI-generated code before it's considered production-ready.
4. Developer satisfaction: Survey developers on their experience with the feature.

UX maturity requirements Experiment to Beta

Criteria	Minimum Requirement	Assessment for Beta
Problem validation How well do we understand the problem?	Mix of evidence and assumptions	Somewhat, Somewhat
Solution validation How usable is the solution?	Usability testing, Grade C	>80% and grade C
Improve How successful is the solution?	Quality goals set by the team are reached.	✅ Reached all quality goals for this phase.
Design standards adherence How compliant is the solution with our design standards?	Should adhere to (Pajamas, checklist)	Mostly adheres to design standards

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