Engineering teams spend countless hours creating documentation.

Unfortunately, most documentation starts becoming outdated the moment it's published.

Features evolve.

Workflows change.

Architectures shift.

But the documentation often stays exactly the same.

As a result, many teams rely on tribal knowledge instead of documentation, creating bottlenecks around senior engineers and making onboarding increasingly difficult.

A growing number of engineering organizations are solving this problem by turning pull requests into video documentation automatically using AI pull request walkthroughs generated directly from code changes.

Instead of documenting software after changes are made, they generate documentation directly from the development process itself.

1. Why Traditional Documentation Fails

Documentation usually falls into one of two categories.

It Never Gets Written

Engineers prioritize shipping software over documenting it.

Documentation becomes a task for "later."

Later rarely comes.

It Becomes Outdated

Even when documentation exists, maintaining it requires ongoing effort.

Every feature update creates another maintenance task.

Over time, documentation drifts away from reality.

This creates confusion and reduces trust in documentation systems.

Many engineers stop using them altogether.

2. Pull Requests Already Contain the Story

Every significant software change passes through a pull request.

The pull request typically includes:

• The problem being solved
• The implementation details
• The files affected
• Review discussions
• Design decisions

In many ways, pull requests already contain the most accurate documentation available. The challenge is that written descriptions often fail to capture the full context behind a change. That's why many teams are adopting walkthroughs alongside traditional descriptions. See pull request walkthroughs vs PR descriptions.

The problem is accessibility.

Most people don't want to read hundreds of pull requests to understand how a system evolved.

3. Why Video Documentation Works

Video documentation provides context that written documentation often struggles to communicate.

A short walkthrough can explain:

• Why a feature was created
• How it works
• What changed
• What reviewers should know
• What users experience

This makes knowledge significantly easier to consume.

It's especially valuable for:

• New team members
• Product Managers
• QA teams
• Customer-facing teams
• Future maintainers

Instead of reading pages of documentation, they can watch a concise explanation. The same approach is commonly used during code reviews. Here's how teams create pull request walkthrough videos that communicate changes clearly.

4. How Pull Requests Become Documentation

Modern workflows make it possible to generate documentation automatically from pull requests. This process often starts with a pull request walkthrough, which captures the context behind a change before it becomes documentation.

The process typically looks like this:

1. A Pull Request Is Opened

The implementation is completed and submitted for review.

2. An AI Agent Reads the Changes

The agent analyzes:

• Code diffs
• Pull request descriptions
• Related tasks
• Changed files

3. A Walkthrough Is Generated

The agent creates an explanation describing:

• What changed
• Why it changed
• User impact
• Important implementation decisions

4. A Video Is Created

The explanation becomes a walkthrough video.

5. The Video Becomes Part of Your Knowledge Base

Instead of disappearing after the review process, the walkthrough remains searchable and reusable.

The documentation is created as a byproduct of development rather than a separate task.

5. Benefits of Video Documentation Generated From Pull Requests

Documentation Stays Current

The documentation is created when the change happens.

This dramatically reduces the risk of stale information.

Better Developer Onboarding

New engineers can learn how systems evolved by watching walkthroughs instead of digging through months of pull request history.

This reduces dependency on senior engineers for context.

Reduced Knowledge Silos

Important implementation decisions remain available even when team members leave.

Knowledge becomes organizational rather than individual.

Better Product and Engineering Alignment

Product teams gain visibility into feature evolution without reading code. This is particularly valuable for organizations where Product stakeholders need to validate implementation regularly. Learn how Product Managers can review pull requests without reading code.

This improves collaboration and reduces misunderstandings.

Faster Incident Investigation

When issues occur, teams can quickly understand:

• Why a change was made
• What assumptions existed
• Which systems were affected

Historical walkthroughs provide valuable context during debugging and incident response.

6. Documentation as a Byproduct of Development

Traditional documentation treats documentation as additional work.

Modern teams increasingly treat documentation as a byproduct of existing workflows. This philosophy closely mirrors the shift toward async pull request reviews, where context is captured once and reused across the organization.

This shift matters.

When documentation requires extra effort, it competes with feature development.

When documentation is generated automatically, adoption becomes significantly easier.

The highest-performing engineering teams are moving toward systems that capture knowledge automatically rather than relying on manual processes.

7. AI Is Making This Practical

Historically, creating video documentation required engineers to:

• Record demos
• Write scripts
• Edit videos
• Upload content

Most teams simply didn't have time.

AI changes the economics completely.

Modern AI agents can:

• Understand pull requests
• Generate explanations
• Create walkthroughs
• Organize content
• Make videos searchable

The cost of creating documentation drops dramatically while consistency improves.

8. Example Workflow

A team ships a new onboarding experience.

Traditionally:

• Pull request is merged
• Review comments disappear
• Knowledge is lost

With automated walkthroughs:

• Pull request is opened
• AI generates a walkthrough
• Reviewers watch the explanation
• Video is stored permanently
• Future team members can search and watch it

The same artifact supports reviews, onboarding, documentation, and knowledge sharing.

9. Pull Request Walkthroughs vs Traditional Documentation

The goal isn't to replace written documentation entirely.

The goal is to ensure critical knowledge is captured while it's still fresh.

10. The Future of Engineering Knowledge Management

Engineering teams are producing more code than ever before.

According to Jellyfish, organizations with full AI coding adoption experience a 113% increase in pull request throughput.

As development velocity increases, knowledge management becomes increasingly important.

The challenge is no longer creating software.

The challenge is preserving the context behind that software.

Pull request walkthroughs offer a scalable way to capture that context automatically.

Conclusion

Most engineering documentation struggles because it depends on manual effort.

Pull request walkthroughs change the equation.

By automatically turning pull requests into video documentation, teams can create a living knowledge base that improves onboarding, reduces knowledge silos, and keeps critical context accessible long after a feature is shipped.

As AI agents become more capable, generating documentation from pull requests is likely to become a standard part of modern software development workflows.

The future of documentation isn't writing more documents.

It's capturing knowledge automatically as work happens.

Source

Jellyfish – AI-Assisted Pull Requests Are 18% Larger

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