Cheetah: AI-Powered Coaching for Remote Engineering Interviews

Elevate your remote tech interviews with Cheetah, the AI-powered Mac app that revolutionizes the hiring process, enabling seamless and efficient assessments.

Table of Content

• Introduction
• Price
• Website
• Use cases
• Pros
• Cons
• Practical Advice
• FAQs
• Case Study
• People Also Searched

Introduction

Are you tired of the traditional process of conducting remote tech interviews? Look no further! Introducing Cheetah, the revolutionary Mac app powered by AI that is set to transform the way you conduct your tech interviews remotely. With Cheetah, you can bid farewell to the days of tedious manual evaluations and outdated interview methods.

Cheetah leverages cutting-edge AI technology to streamline the entire remote tech interview process, making it faster, smarter, and more efficient. Whether you are a hiring manager or a technical recruiter, Cheetah is your ultimate tool for finding the perfect candidate for your team.

Gone are the days of sifting through countless resumes and wasting hours on phone screenings. Cheetah’s advanced algorithms analyze candidate responses, code quality, and problem-solving skills in real-time, providing you with accurate insights and eliminating bias.

Designed exclusively for Mac users, Cheetah offers a seamless user experience, combining the power of AI with sleek and intuitive design. Its intuitive interface ensures that you can focus on what truly matters – evaluating the technical prowess of the candidates.

Ready to revolutionize your remote tech interviews? Embrace the future of hiring with Cheetah – the game-changing Mac app that brings together the best of AI and remote interviewing. Say hello to effortless candidate assessment and say goodbye to traditional hiring woes.

Price

Freemium

Website

Click here

Cheetah Use cases

Use cases for the Mac app for crushing remote tech interviews with AI:

1. Real-time coaching: During a remote software engineering interview, the app provides real-time, discreet coaching to assist users. It offers hints, suggestions, and corrections to help improve their performance.

2. Live coding platform integration: The app integrates with live coding platforms, allowing users to write and execute code directly within the app. It provides feedback on their coding style, correctness, and efficiency.

3. Audio transcription: The app leverages Whisper, an AI-powered real-time audio transcription tool, to transcribe the conversation between the interviewer and interviewee. This transcription can be used for later review and analysis.

4. Generating answers: The app uses GPT-4, a powerful AI model, to generate answers to the interviewer’s questions. It analyzes the question and provides a detailed answer, taking into account various factors and constraints.

5. Answer refinement: If the interviewer provides additional constraints or clarification, the app allows the user to refine their generated answer. This ensures that the answer is accurate and tailored to the specific requirements of the question.

6. Code analysis: The app can analyze code and logs from the live coding environment in a web browser. This feature helps users identify any errors, performance issues, or areas that need improvement in their code.

7. Browser extension: To enhance the code analysis feature, the app offers a browser extension that allows users to highlight portions of generated answers and get more detailed analysis. Currently, the extension is compatible with Firefox.

8. Compatibility and requirements: The app requires macOS 13.1 or later and runs optimally on M1 or M2 Macs. It uses the SDL2 library and requires the installation of Whisper.cpp. It is recommended to use the BlackHole audio loopback driver for capturing audio input from video chat apps like Zoom or Google Meet.

9. Caution and responsibility: It is important for users to exercise caution and take responsibility for the information provided by the app. As a satirical art project, the app may generate incorrect or inappropriate solutions, and users should use their judgment in evaluating the suggestions and answers.

Cheetah Pros

• Cheetah is an AI-powered macOS app that provides real-time, discreet coaching during remote software engineering interviews.
• With Cheetah, users can improve their interview performance and increase their chances of landing a high-paying software engineering job without spending excessive time on leetcode challenges and algorithm memorization.
• Cheetah leverages advanced AI technology, such as Whisper for real-time audio transcription and GPT-4 for generating hints and solutions.
• The app requires users to have their own OpenAI API key or alternatively, they can use gpt-3.5-turbo for generating solutions.
• Cheetah runs locally on the user’s system, utilizing Georgi Gerganov’s whisper.cpp for audio transcription.
• The app is designed for optimal performance on recent M1 or M2 Macs and requires macOS 13.1 or later.
• To ensure the best results, Cheetah advises users to capture both sides of the conversation during video interviews using a free audio loopback driver like BlackHole.
• Cheetah features three buttons in its user interface: “Answer” generates answers for the interviewer’s questions, “Refine” updates existing answers based on additional constraints, and “Analyze” analyzes code and logs from the live coding environment in a web browser.
• The app also supports a browser extension (currently only available for Firefox) that allows users to select and refine specific portions of a generated answer for more detail.
• While Cheetah is classified as a satirical art project, users must exercise caution and take responsibility for the information provided by the app as it may generate incorrect or inappropriate solutions.

Cheetah Cons

• Requires a recent M1 or M2 Mac for optimal performance.
• Requires macOS 13.1 or later.
• Users need to have their own OpenAI API key to use the app.
• If users do not have access to GPT-4, they can use gpt-3.5-turbo as an alternative.
• Whisper runs locally on the user’s system, which may take up significant resources and affect overall performance.
• Users need to have whisper.cpp checked out in a specific directory, which may require additional steps and technical knowledge.
• The SDL2 library needs to be installed, which may also require technical knowledge.
• For the best results, users need to ensure that the audio input captures both sides of the conversation, which may require additional setup and configuration.
• Running the app in debug mode may result in very slow audio transcription performance.
• The UI features three buttons, which may require users to navigate and understand their functionality.
• Using the Refine button to update existing answers may not always provide accurate or helpful refinements.
• The Analyze feature requires a browser extension, which currently only supports Firefox.
• As a satirical art project, Cheetah may generate incorrect or inappropriate solutions, which may mislead users in a real-world interview setting.
• Users should exercise caution and take responsibility for the information provided by the app, as it may not always be reliable or appropriate.

Practical Advice

To effectively use the Mac app for crushing remote tech interviews with AI, here are some practical advice:

1. Get the required tools: Download GitHub Desktop and Xcode if you don’t already have them installed on your Mac. This will ensure that you have the necessary development environment.

2. Set up Codespaces: Sign in to use Codespaces, a feature that allows you to develop in the cloud. This will help you access your code and collaborate with others during the interview process.

3. Install dependencies: Make sure you have Git and SVN installed, as the app requires them for version control. If you don’t have them, you can download them using the provided web URLs.

4. Use a compatible Mac: For optimal performance, use a recent M1 or M2 Mac. This will ensure that the app runs smoothly during the interview.

5. Obtain an OpenAI API key: To use the app, you need to have your own OpenAI API key. This will allow the app to leverage the power of GPT-4 or gpt-3.5-turbo for generating hints and solutions.

6. Capture audio input: For the best transcription results, ensure your audio input captures both sides of the conversation. You can use BlackHole, a free audio loopback driver, to achieve this when using video chat apps like Zoom or Google Meet.

7. Familiarize yourself with the UI: The app’s UI features three buttons – Answer, Refine, and Analyze. Understand the purpose of each button and how they can assist you during the interview.

8. Use Firefox for the browser extension: If you want to analyze code and logs from the live coding environment, make sure you have the Firefox browser installed, as it’s currently the only supported browser for this feature.

9. Exercise caution: Remember that the app is a satirical art project and may generate incorrect or inappropriate solutions. Use it responsibly and take responsibility for the information provided by the app.

10. Practice and prepare: While the app can assist you during remote tech interviews, it’s still important to practice and prepare beforehand. Familiarize yourself with common interview questions and coding challenges to increase your chances of success.

FAQs

1. What is Cheetah?
Cheetah is an AI-powered macOS app designed to assist users during remote software engineering interviews by providing real-time, discreet coaching and live coding platform integration.

2. How can Cheetah help me during a remote tech interview?
Cheetah can help you improve your interview performance and increase your chances of landing a high-paying software engineering job by providing real-time coaching, generating hints and solutions, and assisting with live coding.

3. What technologies does Cheetah use?
Cheetah leverages Whisper for real-time audio transcription and GPT-4 for generating hints and solutions. However, if you don’t have access to GPT-4, you can use gpt-3.5-turbo as an alternative. Whisper runs locally on your system using whisper.cpp by Georgi Gerganov.

4. What are the system requirements for Cheetah?
For optimal performance, Cheetah requires a recent M1 or M2 Mac and macOS 13.1 or later.

5. How do I set up Cheetah?
To build Cheetah, make sure to check out whisper.cpp in the ../whisper.cpp directory and install the SDL2 library. For audio input, it is recommended to use a free audio loopback driver like BlackHole when using video chat apps like Zoom or Google Meet.

6. What are the features of the Cheetah UI?
The Cheetah UI features three buttons: “Answer” generates an answer for the interviewer’s question, “Refine” updates the existing answer, and “Analyze” analyzes code and logs from the live coding environment in your web browser. You can also select a portion of a generated answer to get more detail by clicking “Refine”.

7. Is the Cheetah browser extension available for all browsers?
Currently, the Cheetah browser extension is only supported on Firefox.

8. Is Cheetah suitable for real-world use?
No, Cheetah is a satirical art project and is not intended for use in real-world settings. It may generate incorrect or inappropriate solutions. Users should exercise caution and take responsibility for the information provided by the app.

9. Can I use Cheetah without an OpenAI API key?
No, you need to have your own OpenAI API key to use Cheetah.

10. Can I use an alternative to GPT-4?
Yes, if you don’t have access to GPT-4, you can use gpt-3.5-turbo as an alternative.

Case Study

Mac app for crushing remote tech interviews with AI

Introduction
Cheetah is a macOS app designed to revolutionize the way remote software engineering interviews are conducted. It utilizes artificial intelligence (AI) to provide real-time coaching and integration with live coding platforms. With Cheetah, users can enhance their performance during interviews, increasing their chances of securing high-paying software engineering jobs without the need to spend countless hours cramming algorithms and challenges.

Features
Cheetah incorporates two main AI technologies: Whisper for real-time audio transcription and GPT-4 for generating hints and solutions. Users are required to have their own OpenAI API key to use the app. In case GPT-4 is unavailable, an alternative option such as gpt-3.5-turbo can be used. Whisper operates locally on the user’s system, utilizing whisper.cpp developed by Georgi Gerganov. For optimal performance, it is recommended to have a recent M1 or M2 Mac and macOS 13.1 or later.

Usage
To start using Cheetah, the user needs to have whisper.cpp checked out in the ../whisper.cpp directory and install the SDL2 library. The app works best when the audio input captures both sides of the conversation. This can be achieved by using BlackHole, a free audio loopback driver, in conjunction with video chat apps like Zoom or Google Meet. By setting up a Multi-Output Device, the audio input is properly captured without using the loopback device as the input for the video chat app.

The Cheetah UI features three buttons:
1. Answer: Generates an answer for the interviewer’s question.
2. Refine: Updates the existing answer based on additional constraints or clarification provided by the interviewer.
3. Analyze: Analyzes code and logs from the live coding environment in the user’s web browser. This requires the installation of the browser extension, currently only supported on Firefox.

Disclaimer
It is important to note that Cheetah is a satirical art project and not intended for use in real-world scenarios. It may generate incorrect or inappropriate solutions. Users are advised to exercise caution and take responsibility for the information provided by the app.

In conclusion, Cheetah is a groundbreaking Mac app that leverages AI to provide invaluable assistance during remote tech interviews. By combining real-time audio transcription and AI-generated hints and solutions, Cheetah aims to optimize interview performance and help users secure their dream software engineering jobs.

People also searched

Mac app | remote tech interviews | AI