How I Built a Real Interview Coach with Claude Code Instead of ChatGPT's "Great!

ChatGPT Always Says "Great!" but I Don't Remember Anything—Built a Real Interview Teacher with Claude Code

A Pain Point for Everyone

When you use ChatGPT / Claude to prepare for interviews, have you ever encountered this situation:

• You give an obviously flawed answer, it replies "Great answer!" and moves straight to the next question
• Every time you start a new conversation, it doesn't remember what you learned yesterday, and you have to re-introduce yourself
• You've memorized a bunch of "Eight-Legged Essay" style answers, but don't know when to review them, and forget everything after a couple of days
• It explains a concept, you feel you understand after reading, but when it comes to the interview, you can't articulate it

The root cause is simple: ChatGPT is a considerate chat companion, not a strict teacher.

Its operating principle is "make the user happy," not "make the user learn." It thinks whatever you say is great because it's afraid you'll be unhappy.

Is There a Way to Make AI a Strict Teacher?

Yes. I did it using Claude Code (Anthropic's CLI programming tool).

Claude Code has a unique capability: rule files (CLAUDE.md) + persistent memory system. In simple terms, you can "program" the AI's behavior by writing rule files, and these rules are automatically loaded in every conversation.

I applied this capability to interview preparation.

What I Did

I wrote a set of configuration files, with two core components:

1. Strict Learning Process (rules/interview.md)

Rules:
1. Mixed questions (3-4 modules, not just one topic)
2. Correct answer → Brief confirmation + related knowledge points → Next question
3. Wrong answer → Must explain (including reference URL) → Give verification question → Only proceed to new question after passing
4. No skipping steps, can't go directly to the next question after answering

The difference from a regular AI: The rules are hardcoded, not decided by the AI itself. It can't take the easy way out and say "Great," because the rule file tells it it must complete the explanation → verification process.

2. Forgetting Curve Review Scheduling (knowledge/interview_tracker.md)

Knowledge Point	First Learned	D+1	D+2	D+4	D+7	D+15	Status
Smart Pointers	5/29	✅	✅				Mastered
Virtual Table	5/29	❌					Weak

At the start of each session, Claude automatically checks which knowledge points are due for review and prioritizes review questions. You don't need to keep track of when to review yourself.

3. Daily Wrap-up Verification

When you say "That's it for today" each day, it triggers the wrap-up process:

1. Claude provides an outline of today's learning
2. You recall based on the outline and give your own understanding
3. Claude judges whether you truly understand or are just reciting answers
4. Updates the review schedule

This is the AI version of the Feynman Technique—it's not about whether you feel you understand, but whether you can explain it, with AI as the judge.

Effect Comparison

Capability	ChatGPT Interview	Anki	NotebookLM	SaaS Platform	This Project
Cross-session Memory	None	Deck-level only	None	Partial	Yes
Spaced Repetition	None	Yes	None	None	Yes
Wrong Answer→Explain→Verify	None	None (just gives answer)	None	Partial	Yes
Native Questioning from Project Code	Need to manually paste code	Not applicable	Requires file upload	Not supported	Native Support
Additional Cost	None	None	None	$29-300/session	No extra cost

The core difference: Other tools either have memory without understanding (Anki), understanding without memory (ChatGPT), or neither (SaaS). Claude Code's rule file + memory system is the only solution that combines both.

The Biggest Killer Feature: Starting from Your Project Code

All interview tools on the market work on a "I ask, you answer" model.

This project is different: It probes deeper starting from your own code.

For example, my project has a BoundedQueue (Bounded Queue) that uses two condition_variable. When preparing for interviews, Claude doesn't just ask you "Please explain condition_variable," but instead asks:

"Your BoundedQueue uses two condition_variables (not_full_ and not_empty_), would one work?"

This kind of question forces you to think about principles from code you've written yourself, giving knowledge an anchor point, not just memorizing "Eight-Legged Essay" answers.

Quick Start

1. Fork the Repository

gh repo fork happiness-cheng/ai-interview-engine --clone

2. Open with Claude Code

cd ai-interview-engine
claude

3. Say Your First Sentence

I'm preparing for a C++ backend development interview, aiming for a big tech internship. Start reviewing.

That's it. Claude will read the rule files and start the first round of questions.

4. Switch to Your Own Tech Stack

The repository comes with example question banks for C++ backend. If you're using Java / Go / frontend, just replace them with blank templates:

knowledge/TEMPLATE.md → Copy as interview_tracker.md → Fill in your knowledge points

My Experience

I'm a sophomore preparing for the 2026 fall recruitment internship. Using this system to prepare for C++ backend interviews, the most obvious feelings are:

1. Less anxiety — No need to plan "what to review today" myself; the system automatically schedules based on the forgetting curve
2. Actually remembered — The wrong answer → explanation → verification process forces true understanding, not fleeting exposure
3. More confident about projects — The probing questions starting from your own code let you clearly explain the "why" behind every design decision in your project.

This Isn't Just an Interview Tool

The underlying engine is universal: Question → Answer → Judge → Explain → Verify → Forgetting Curve Scheduling.

Interviews are just one scenario. You can use it to prepare for:

• Technical interviews (currently supported)
• Career change/job hop reviews
• Final exams (same principle, swap the knowledge point bank)

Open Source Repository

GitHub: https://github.com/happiness-cheng/ai-interview-engine

If it helps you, give it a star. If you have suggestions for improvement, feel free to open an issue.