Do you use PR pre-releases to rapidly test AI-built desktop features?

Previously, testing desktop features created with AI agents meant checking out a PR branch locally, building the app, and running it manually. Which took time, slowed feedback loops, and encouraged "vibe coding" where changes are shipped without a deep understanding of the code.

By exposing a settings option to switch to specific PR builds, they can be easily installed tested - no local branch juggling or manual builds required.

Why this matters

• Faster feedback for AI-generated changes without compromising quality
• Realistic testing inside the desktop runtime, not just mock environments
• Reduced friction for reviewers and Product Owners
• Encourages the professional Plan → Discuss → Implement → Review cadence

The new workflow

1. Plan the change with context and constraints
2. Ask your AI agent to implement a small, self-contained step
3. Automatically build a PR pre-release via CI
4. In your desktop app, switch to that PR pre-release from Settings
5. Review the behavior in-app, run tests, and capture findings
6. Iterate until the feature is complete, then merge

❌ Figure: Bad example - Manual local branch switching, building, and running every time you want to test a change

✅ Figure: Good example - Switch your desktop app to the PR pre-release channel in Settings, install, and test instantly in the real app environment

Tips for professional AI-assisted development

• Prefer small, focused steps that map one-to-one to PRs
• Write down assumptions and risks in the PR description
• Add lightweight checks to catch regressions early
• Use screenshots or short videos for reviewers. The agent can capture these itself while it verifies the change
• Keep a changelog entry for user-visible behavior

References

• GitHub Action example – PR pre-release switching
• Release channel handler example
• Electron autoUpdater