Features
Live observation of candidates using Claude Code and Codex
Real-time split view: terminal, code editor, AI chat
Full audit trail: every file read/write, command, AI interaction
Built-in code workspace with backend, frontend, scripts, tests
Supports multiple AI agents simultaneously
Custom scenario-based coding tasks
Time-stamped event log for post-interview review
Assesses AI prompt engineering skill
Multi-stage Dockerfile optimization scenario
Kubernetes resource tuning exercise
Integration with GitHub repositories
Collaborative evaluation tools for hiring teams
Candidate replay with session analytics
Real VM with VS Code and dependencies pre-configured
GPU available for specialized tasks
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
