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Introduction
The tech hiring landscape has dramatically shifted in 2025, with artificial intelligence tools increasingly being used to bypass traditional screening processes. Coding interviews, particularly those based on Leetcode-style problems, have become a central battleground where candidates and employers are locked in a technological arms race. This article explores the top 10 AI tools being used to circumvent coding interviews and examines the recent high-profile case of Chungin "Roy" Lee, a Columbia University student who was suspended after creating and publicizing an AI tool designed to cheat on tech job interviews.
The Rise of Leetcode Interview Cheating
The technical interview process at major tech companies has long been criticized for its focus on algorithm puzzles and data structure challenges that many argue have little correlation with day-to-day programming tasks. This disconnect has fueled a growing market for AI tools designed to help candidates "beat the system." With the average software engineering interview process taking 3-4 weeks and often including multiple rounds of technical assessments, the stakes are high, and some candidates are turning to controversial methods to secure positions.
The Roy Lee Case: A Turning Point
In early 2025, Chungin "Roy" Lee, a second-year computer science student at Columbia University, made headlines when he built an AI tool called "Interview Coder" that could covertly solve technical coding problems during interviews. Lee recorded himself using the tool during an Amazon internship interview and shared the video online, claiming he received an offer as a result.
According to Business Insider and NBC News reports, Lee's tool worked by taking screenshots of coding problems without being detected by the browser's monitoring systems. It then processed these images using AI to generate solutions in real time. Lee claimed he received offers from multiple tech giants including Amazon, Capital One, Meta, and TikTok using his tool.
The stunt was apparently designed as a protest against what Lee described as the "miserable" experience of preparing for Leetcode interviews. In his own words, he was "in the top 2% of global Leetcode users," but considered the 600 hours he spent practicing as wasted time since "the questions are not indicative of what you do in the real world."
The consequences were swift: Columbia University suspended Lee for a year, though interestingly not for creating the cheating tool itself. According to disciplinary documents, Lee's suspension was for publishing unauthorized recordings of a disciplinary hearing and posting photos of Columbia staff on social media. Lee has since announced he's moving to San Francisco to focus on his AI startup, which he claims is generating about $170,000 in monthly subscriptions with 50% week-over-week growth.
Top 10 Leetcode Interview Cheating AI Tools of 2025
1. Interview Coder by Roy Lee
Key Features: The tool that started the recent controversy, Interview Coder takes screenshots of coding problems without being detected and generates solutions in real time using advanced AI models. It's designed to be "invisible" to browser monitoring systems.
Price: $60/month, with Lee claiming the tool is on track to generate approximately $2 million in annual revenue.
2. Leetcode Wizard
Key Features: One of the most established players in the interview-cheating space, Leetcode Wizard bills itself as "The #1 AI-powered coding interview cheating app." It provides real-time solutions to common interview problems across multiple platforms.
Price: Subscription-based with tiered pricing.
3. CodeWhisperer Pro
Key Features: Unlike more obvious cheating tools, CodeWhisperer Pro positions itself as an "interview assistant" that provides subtle hints rather than complete solutions, making detection more difficult during monitored interviews.
Price: Monthly subscription with a free trial period.
4. AlgoSolver AI
Key Features: Specializes in algorithmic problems with visualization tools to help candidates understand the solution process, allowing them to explain their approach convincingly during interviews.
Price: Paid subscription with enterprise options for bootcamps.
5. InterviewGPT
Key Features: A comprehensive tool that combines coding assistance with interview preparation, offering not just technical solutions but also guidance on how to articulate problem-solving approaches.
Price: Tiered subscription model with academic discounts.
6. Shadow Helper
Key Features: One of the most covert tools in the market, Shadow Helper runs as a background process that can be triggered by specific keyboard combinations, making it nearly undetectable during remote interviews.
Price: Premium subscription model with verification requirements.
7. LeetPilot
Key Features: Focuses specifically on the most common Leetcode problems asked by FAANG companies, with optimized solutions for speed and efficiency.
Price: Monthly or annual subscription options.
8. CodeCraft AI
Key Features: Provides multiple solution approaches for each problem, allowing candidates to select the one that best matches their professed skill level.
Price: Tiered pricing with basic and premium plans.
9. TechInterview Assistant
Key Features: A browser extension that appears as a harmless productivity tool but contains hidden functionality to analyze and solve coding challenges during interviews.
Price: Free base version with paid premium features.
10. AlgoBuddy
Key Features: Offers specialized assistance for different types of technical problems, including system design, algorithms, and database queries.
Price: Subscription-based with academic discounts.
The Ethics and Implications
The proliferation of these AI cheating tools raises serious ethical questions for both candidates and employers. For job seekers, using such tools may provide short-term gains but can lead to long-term career issues when they're unable to perform tasks commensurate with their presumed skill level.
For companies, this new reality challenges the fundamental reliability of technical interviews. According to Isabel de Vries, head of marketing at Leetcode Wizard, their tool exists because Leetcode "doesn't properly allow engineers to demonstrate their abilities when it comes to programming, while also ignoring the use of AI in daily programming work."
Tech companies are responding to this challenge in various ways. Amazon's spokesperson Margaret Callahan stated that while the company welcomes candidates sharing their experiences with generative AI tools when relevant to their roles, they must acknowledge they won't use unauthorized tools during interviews or assessments.
Detection and Countermeasures
Tech companies are enhancing their interview processes to detect AI assistance. Common strategies include:
- Real-time explanation requirements: Candidates must explain their thought process throughout coding exercises, making it more difficult to rely solely on AI.
- Custom problems: Moving away from standard Leetcode questions to custom challenges that aren't found in training datasets.
- Multi-modal assessments: Including verbal reasoning, system design, and behavioral components that AI tools struggle to address.
- Proctoring technology: Advanced browser monitoring and secure interview environments.
- Post-interview verification: Follow-up assessments to verify skills demonstrated during initial interviews.
The Future of Technical Interviews
The Roy Lee case highlights a turning point in technical interviews. As AI tools become more sophisticated, the traditional assessment methods must evolve. Some companies are already shifting toward pair programming exercises, project-based assessments, and technical discussions that evaluate how candidates approach problems rather than focusing solely on solution correctness.
Lee himself stated that his goal was to force tech companies to change their interview formats, saying, "I think cheating on these online assessment interviews is really much more common than people think. Many CS students who are pretty serious about recruiting and stuff know that there are apps like this. It's just not understood at a large scale."
Conclusion
The rise of AI tools for cheating on coding interviews represents a significant challenge to traditional technical assessment methods. The suspension of Chungin "Roy" Lee from Columbia University underscores the controversial nature of these tools, even as his company continues to grow and prosper. Whether you view these developments as ethical breaches or inevitable technological progression, one thing is clear: the technical interview landscape is being permanently altered.
As we move further into 2025, companies will need to fundamentally reconsider how they evaluate technical talent. Meanwhile, candidates face increasingly difficult ethical choices about their use of AI assistance during the hiring process. In this new reality, the definition of technical competence itself may need to be reconsidered to account for the role of AI as both a challenge to assessment integrity and a legitimate tool in modern software development.
For both employers and job seekers, understanding these top 10 interview cheating AI tools isn't about endorsing their use, but rather recognizing the changing landscape of technical assessment in an AI-accelerated world.