Ai

How do you use AI code assistants like GitHub Copilot or the integrated Gemini in Android Studio in your day-to-day workflow?

What's your experience with using AI for code completion versus more advanced tasks like code generation, refactoring, or "agent mode" tasks?

Describe a time an AI assistant generated code that was subtly wrong, inefficient, or insecure. How did you identify the issue, and what was your process for correcting it?

What are your best practices for writing effective prompts (e.g., providing context, role-playing) to get useful code, layouts, or documentation from an AI tool?

Have you used AI features like Gemini's "Explain this crash" (from App Quality Insights) to accelerate debugging? What was the experience like?

What is your experience with AI-powered unit test generation? How much manual oversight and correction does it typically require?

Google has introduced "Journeys" for Android Studio. Can you explain what this AI-powered testing approach aims to solve?

Beyond writing code, how do you leverage AI to assist in tasks like code reviews, generating Kdoc, or writing commit messages?

What, in your view, is the difference between "function calling" (or "tool use") in an LLM and the Model Context Protocol (MCP)?

Why is a standard like MCP important for the future of AI developer tools and agents? What problems does it solve?

What are the security and data privacy implications of using AI assistants that have context of your entire codebase? How do you or your team manage this?

How do you see AI agents (not just assistants) changing the software development lifecycle over the next 1-2 years?

The landscape of AI developer tools is changing almost monthly. How do you stay current with new tools, plugins, and emerging standards?