Android Studio Panda 4

What is Android Studio Panda 4?

Android Studio Panda 4 is a new stable release of Android Studio that adds AI-assisted workflow features for building Android apps. The update focuses on two areas: Planning Mode for structured multi-stage planning before the AI starts work, and Next Edit Prediction (NEP) for code completion that anticipates related edits beyond the current cursor location.

In practice, these features are designed to support non-linear development—where a change in one file often requires follow-up updates elsewhere—while also giving the AI more space to evaluate logic before proposing an implementation.

Key Features

• Planning Mode (agent input mode: “Planning”): Switch the agent conversation mode to “Planning” to request a project plan before executing tasks, helping reduce the risk of immediately jumping into complex work.
• Multi-stage reasoning for implementations: Instead of generating code in a single pass (next-token style), Planning Mode supports a staged process that allows the agent to evaluate proposed logic for potential issues before presenting output.
• Implementation Plan workflow with review loops: The agent can generate an “Implementation Plan” for large or complex tasks; you can add comments and submit them so the agent revises the plan based on your feedback.
• Task List artifact for execution tracking: During execution, the agent organizes work and produces a “Task List” artifact so you can monitor progress across multiple steps.
• Walkthrough artifact for change summaries: After completion, the agent produces a “Walkthrough” artifact summarizing what was changed to make review and verification easier.
• Next Edit Prediction (NEP) for non-linear code changes: NEP analyzes recent edits and suggests the next relevant edit even when it’s not at the cursor—such as updating function invocations after a change to a data class or constructor.

How to Use Android Studio Panda 4

To use Planning Mode, open the agent input box and switch the conversation mode to “Planning”, then enter your prompt. The agent may generate an Implementation Plan; you can add comments to the plan and use “Submit Comments” to have the agent revise the plan before it begins execution.

To use Next Edit Prediction, continue coding normally and rely on autocomplete suggestions that reflect your recent edit patterns. When NEP suggests related edits in other locations, you can accept the multi-location suggestions with a single keystroke to continue without manually hunting through the code.

Use Cases

• Architectural planning for complex refactors: When you’re about to implement a large change and want an upfront plan, use Planning Mode to request a structured implementation approach before the agent writes or modifies code.
• Iterating on an AI-generated approach before execution: If the initial plan includes an approach you don’t want, add comments to the Implementation Plan and submit feedback to revise the plan prior to execution.
• Managing long-running multi-step changes: For tasks that require several coordinated edits, use the Task List artifact to track what the agent is doing across steps.
• Reviewing automated edits with context: After the agent completes changes, use the Walkthrough artifact to review exactly what was modified before you merge or deploy.
• Updating dependent code after an API change: When you change a data class or constructor, NEP can suggest follow-on edits in distant functions—such as updating invocations—helping you keep momentum.

FAQ

• How do I enable Planning Mode? Switch the agent conversation mode in the agent input box to “Planning”, then enter your prompt.

• Can I change the plan before the agent starts coding? Yes. You can open the Implementation Plan, add comments, and use “Submit Comments” to revise the plan before execution.

• What does NEP do when the next change isn’t at the cursor? NEP recognizes patterns from recent edits and suggests the next relevant edit even when it occurs in another location, allowing you to accept suggestions with a single keystroke.

• What artifacts will I see when using Planning Mode? The agent can generate an Implementation Plan, a Task List during execution, and a Walkthrough summary after the work is done.

Alternatives

• Traditional IDE autocomplete: Standard completion helps fill in code at or near the cursor, but it doesn’t explicitly anticipate related non-linear edits in other files or locations.
• General-purpose code assistants with chat-only workflows: Chat-based tooling may still provide guidance, but it may not provide the specific Planning Mode artifacts (Implementation Plan, Task List, Walkthrough) described here.
• Manual refactoring and navigation (IDE search/jump-to-definition): For teams that prefer fully manual control, workflows using search and navigation can handle multi-location updates, but with more context switching than NEP’s multi-location suggestions.
• Other IDE planning/review workflows (human-first design + code execution): Teams can avoid AI planning features by doing design and implementation planning themselves, then using standard completion/editing while keeping all execution decisions manual.