What Is an AI Player?
PlayerZero’s AI Players acts as your knowledge-rich agents, designed to help you understand, investigate, and solve problems across your codebase and systems. Whether you’re debugging a tricky issue, exploring architecture, or researching historical changes, the AI Player provides fast, context-aware insights. To use it, navigate to any project in PlayerZero and start a conversation through the free‑form prompt interface.Starting Points
Free‑Form Input
Free‑Form Input
- Access Point: Available on the homepage and within any project view.
- Use Case: Ideal for open-ended questions, quick lookups, or initiating deep investigations.
- Behavior: AI builds context from your selected project and branch, then continues to expand the conversation as you refine your queries.
Debug Report
Debug Report
- Access Point: From any session replay or Debug Report timeline.
- Use Case: Perfect when you need to investigate user-reported issues with full session, DOM, and trace context.
- Behavior: Clicking “Find in My Code” or “Debug” launches a chat that’s pre-loaded with session data, related logs, and linked code paths for faster root-cause analysis.
Log Error
Log Error
- Access Point: From any error log, stack trace, or telemetry panel.
- Use Case: For digging into specific errors or performance alerts without starting a fresh session view.
- Behavior: AI automatically correlates the log or stack trace with relevant files, recent commits, and known historical issues, so you can jump straight to a potential fix.
PR Summary
PR Summary
- Access Point: Directly from Pull Request pages in PlayerZero.
- Use Case: Quickly understand what a PR changes, potential risks, and how it may impact customers.
- Behavior: AI generates a natural-language summary, identifies impacted areas, and lets you ask follow-up questions about specific functions, modules, or risks.
Modes of Operation
Fast Mode
Fast Mode
- Purpose: Instant responses for straightforward questions.
- Best For: Simple code lookups, lightweight explanations, or quick verifications.
- Ideal When: You need an answer now and don’t need detailed reasoning.
Normal Mode
Normal Mode
- Purpose: Balanced speed and detail, with transparent reasoning.
- Best For: Most investigation and debugging work.
- Special Feature: Toggle “View Thought Process” to see how the AI connects files, context, and logic.
DeepThink / Deep Research Mode
DeepThink / Deep Research Mode
- Purpose: Comprehensive exploration of your codebase and systems.
- Best For: Complex investigations (e.g., “How does authentication work across all services?”).
- Behavior: The AI systematically analyzes files, dependencies, and historical changes to produce a detailed, end‑to‑end understanding.
Context & Navigation Features
Repo and Branch Selection
Repo and Branch Selection
- Point the agent at specific Repositories branches at any time during your chat.
- Switch between Git branches at any time during your chat.
- The AI keeps your investigation context, analyzing how code and logic differ between versions.
Follow‑Up Questions
Follow‑Up Questions
- Build deeper understanding by layering questions.
- The AI remembers your conversation history and evolves responses as you refine your investigation.
Fork Conversation
Fork Conversation
- Split into parallel threads to explore multiple topics (e.g., one thread for performance bottlenecks, another for API behaviors).
- Keeps your original investigation intact while exploring side questions.
Context Workspace
Context Workspace
- A persistent workspace tracks:
- Files you’ve viewed
- Code patterns analyzed
- Problems under investigation
- The AI uses this workspace to maintain continuity across your session.
Semantic Code Search
Semantic Code Search
Ask about functionality in plain English and the AI will:
- Search your entire repository with semantic understanding (not just keywords).
- Map relationships across files.
- Suggest related areas of code you may not have considered.
Model Training Dataset
Code
Code
- Full repository structures and files
- Branch-specific code and diffs
- Semantic embeddings of functions, classes, and modules
- Cross-file dependency mapping
- Historical changes and commit context
Tickets
Tickets
- Pull from support tickets, bug reports, feature requests, and customer issues
- Surface historical context for recurring or related problems
- Correlate reported behavior with relevant code or changes
Telemetry
Telemetry
Leverage session and performance data, including:
- User session traces
- Error logs and stack traces
- Network requests and console logs
- Performance metrics and usage trends
Actionable Outputs
Diagrams
Diagrams
Generate visualizations like:
- Mermaid diagrams
- Network and flow charts
- System architecture diagrams
- Process workflows for debugging or onboarding
Documents
Documents
Automatically create:
- Technical documentation
- Investigation summaries
- Troubleshooting guides
- Structured code analysis reports
Code Snippets
Code Snippets
Write and deliver:
- Example code snippets and test implementations
- Fix and refactor suggestions
- Executable stubs based on your actual code patterns
Tickets
Tickets
Generate structured content to support issue tracking:
- Bug write‑ups and root cause summaries
- Feature requirement outlines
- Problem descriptions for direct ticket creation