ibttf/interview-coder
Interview Coder
This project is a suite of tools centered around an AI-powered interview assistant, a professional resume builder, and an engineering salary database. The core application provides real-time audio transcription and generates code and system design solutions during technical interviews.
The software is designed for stealth and detection avoidance. It utilizes an invisible screen overlay that bypasses screen-capture and screen-sharing software, allowing the user to view information without it appearing on shared displays. To further avoid detection, the system implements keyboard-only operation to eliminate visible mouse movements and employs process name masking to hide the application from system task managers and activity monitors.
Additional capabilities include a library of solved coding problems organized by algorithm and data structure, as well as career intelligence tools for benchmarking compensation and comparing job offers against market data.
User access is managed through account registration and identity authentication via email or third-party providers.
Features
- Real-Time Interview Copilots - Functions as an AI assistant that analyzes live audio to provide real-time code and system design solutions during interviews.
- AI-Powered Code Generation - Uses large language models to generate algorithmic solutions and system design responses based on live transcription.
- Real-Time Transcription - Provides instantaneous conversion of live interview audio into text transcripts for real-time AI analysis.
- Real-Time Audio Transcribers - Converts live interview audio into text in real time to facilitate AI-driven assistance.
- Keyboard-Driven Interfaces - Eliminates visible mouse movements by executing all application functions via keyboard shortcuts.
- Stealth Interface Shortcuts - Implements all application functions via shortcuts to eliminate visible mouse movements during live sessions.
- Salary Benchmarking Databases - Includes a database for benchmarking engineering compensation and comparing job offers against market data.
- Audio Processing - Implements audio processing to capture and analyze spoken conversation from live interview sessions.
- Invisible Overlays - Implements a transparent desktop layer that remains invisible during screen shares and recordings.
- Interview Answer Assistants - Integrates with video conferencing and assessment tools to provide real-time answer suggestions to the interviewee.
- Screen Share Evasion - Integrates click-through overlays and keyboard-only controls to remain invisible during screen shares.
- Screen Capture Protections - Uses native windowing flags to prevent the AI assistant interface from appearing in screen shares or recordings.
- System Process Hiding - Conceals the application's presence from system task managers and activity monitors to avoid detection.
- Screen-Sharing Concealment - Prevents the application window from appearing in screen-capture or sharing software used during interviews.
- Click-Through Controls - Renders a transparent overlay that allows mouse events to pass through to the underlying interview platforms.
- Interview Pattern Solutions - Offers a library of solved coding problems based on industry-standard interview patterns.
- Market Research Strategies - Provides market research strategies to gather salary data for informing employment negotiations.
- Professional Resume Generators - Automates the creation of professional software engineering resumes by organizing experience, projects, and skills.
- Resume Builders - Ships a dedicated platform for creating and managing professional engineering resumes.
- Interview-Focused Problem Sets - Provides curated collections of algorithm and data structure problems specifically for technical interview prep.
- Offer Evaluation Frameworks - Provides a framework for analyzing multiple job offers side-by-side against industry market data.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
