AI-Assisted Coding Interview Prep: A Structured Approach

How I Use AI to Prepare for Coding Interviews (Without Cheating)

Matthew Hou uses AI to prepare for coding interviews without cheating, achieving a 75% solve rate for medium LeetCode problems. His approach involves using AI as a tutor, not a crutch, to improve problem-solving skills and gain practical experience.

Why This Matters

The technical reality of coding interviews is that they require a combination of problem-solving skills, knowledge of algorithms and data structures, and the ability to think critically under pressure. Ideal models of interview prep often focus on solo practice, but AI-assisted prep can provide a more structured and effective approach, helping candidates to identify and address their weaknesses, and to develop a more nuanced understanding of the problems they are trying to solve. For example, a candidate who uses AI to generate problems and provide feedback can gain a better understanding of their strengths and weaknesses, and can develop a more effective strategy for improving their skills.

Key Insights

• Using AI to generate problems and provide feedback can help candidates to identify and address their weaknesses, and to develop a more nuanced understanding of the problems they are trying to solve (Source: Matthew Hou, 2026)
• A structured approach to interview prep, including phases such as pattern recognition, mock interviews, and system design practice, can help candidates to develop a more effective strategy for improving their skills (Example: LeetCode’s problem-solving framework)
• AI can be used to simulate real-world scenarios and provide feedback on a candidate’s performance, helping them to develop a more realistic understanding of the challenges they will face in a real interview (Tool: ChatGPT, used by Matthew Hou)

Practical Applications

• Use case: Google’s interview process, which involves a combination of technical and behavioral questions, can be simulated using AI to provide feedback on a candidate’s performance. Pitfall: Over-reliance on AI-generated problems can lead to a lack of understanding of the underlying concepts and algorithms.
• Use case: LeetCode’s problem-solving framework, which provides a structured approach to interview prep, can be used in conjunction with AI to generate problems and provide feedback. Pitfall: Failure to practice whiteboarding and communication skills can lead to poor performance in real interviews.

References:

• https://dev.to/matthew_hou_e8ab76d6be07b/how-i-use-ai-to-prepare-for-coding-interviews-without-cheating-57h3