Github Issues AI Copilot

How to Use AI to Generate Github Issues Issues

Use AI to generate issues that your team will love.

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The Importance of Github Issues Issues

Prevailing wisdom dictates that quality and velocity in software development are diametrically opposed: you get one or the other, not both. But that's not always the case – high-craft teams that ship are possible, especially with a strong foundation. Documentation is a cornerstone of these teams, enabling lock-step coordination between product, design, and engineering, a hallmark of next-generation design engineering. That said, documentation can be slow and finicky. It's annoying, frankly – which is where AI comes in. But before we get to that, let's review the basics. What makes a great Github Issues issue? Is there even such a thing?

What Makes a Great Github Issues Issue?

Nailing your project's development requirements starts in the project's discovery phase. If you're the PM, this likely means stakeholder meetings, documentation review, and product thinking to answer key questions like "What are we building?" and "Why?" A thorough discovery phase enables high-velocity, high-quality engineering work. The two project phases, discovery and development, converge at a single point: Github Issues issues. High-quality Github Issues issues are clear, unambiguous, and thorough, enabling not only your engineers but also your QA process with Acceptance Criteria (a list of criteria that must be true for the Github Issues issue to be "done.")

Clarity

Leave little to no room for interpretation. Your issues should be clear and exact.

Detail

The more detail you provide your engineers about the intended outcome, the more precisely the result will correspond with your expectations.

Edge Cases

Anticipate as many edge cases as possible while you create your issues. Document how you expect to address each edge case.

Structure

Proper structure makes your issues easily actionable, especially when using the same template for all of your issues.

How to Write Great Github Issues Issues

Writing high-quality Github Issues issues is easy with the right template and guiding principles. The template below is tried-and-true and battle-tested in large and small companies and should serve as a jumping-off point for you and your team. That part is key: ensure you work with your engineers and stakeholders to find a template and structure that works well for your team's workflow. Once your template is set, consistently follow its structure and adhere to the above guiding principles. Your teammates will appreciate your consistency, helping the entire team move faster.

Template

Github Issues Issue Template

You can copy and paste this Github Issues issue template to create your own, or use Magical.pm to generate it with AI.

Overview

[Provide a concise and clear description of the task or feature here.]

To-Do

• [Identify and list the first actionable task here.] • [Specify the second actionable task here.] • [...continue listing all relevant tasks...]

Acceptance Criteria

• [Clearly define the first success condition or expected outcome here.] • [Specify the second success condition or expected outcome here.] • [...continue listing all acceptance criteria...]

Template in action

Example Github Issues Issue

The example below follows our Github Issues issue template for a hypothetical task to exclude internal IP addresses from Segment tracking events.

Overview

The goal of this card is to modify the analytics system to exclude internal IP addresses from data collection in Segment. This will ensure the data we collect is related to genuine user activity, excluding any internal testing or development related activities.

To-Do

• Identify all internal IP addresses to be excluded from analytics. • Implement a filter within Segment to exclude activity from these identified IP addresses.

Acceptance Criteria

• All identified internal IP addresses are excluded from data collection in Segment. • Data collected in Segment reflects only genuine user activity, excluding all internal activity.

Generating Github Issues Issues With AI

Fortunately, whether you're a seasoned PM or early in your career, the rise of AI means that Github Issues issues no longer need to be created by hand. Using Magical.pm's free AI product management co-pilot, you can generate perfectly formatted Github Issues issues from natural language. Inputs as simple as "when the user types in the notepad, turn the generate button #5260FF" turn into perfectly formatted Github Issues issues, ready for your developers.

Skeptical? Try it now

Experience the magic of AI-generated Github Issues issues

Write lazy requirements"when the user types in the field, turn the button #5260FF"

Get perfectly formatted requirementsMagical.pm will return perfectly formatted requirements.

Copy and paste into your toolsBe it Linear, Jira, Confluence – or anything else. Magical.pm's requirements are in markdown format.

Go further with TemplatesSelect the perfect template for your use case.

Lazy RequirementsDescribe your product requirements in natural language.

Your Github Issues IssueReady for dev, in seconds.

A funny thing happens when writing a PRD takes seconds...You start shipping. A lot.

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