F**K LeetCode: The Tool That’s Killing LeetCode: How People Are Now Cheating Live Coding Interviews into FAANG

The Email That Kicked This Off

A subscriber sent me an email with a blunt take on the last decade of hiring. The message basically said:

That email captured a shift a lot of engineers have felt. For years, LeetCode has been the barrier. You grind. You memorize. You pray the patterns line up on interview day. But this subscriber called out something specific. Amazon is freaked. There is a tool. It is called interviewcoder.co. And it shows how easy it is to game a LeetCode interview. Recruiters already know. They are looking for new approaches.

Clicking The Link: A Page Titled F**K LeetCode

When I clicked the link, the page that loaded had a title that literally said F**K LeetCode. That immediately caught my attention. If you name your product page like that, you are not subtle. You are picking a fight with the status quo. I kept scrolling because I needed to see what was going on here.

What I found was a product built to actively defeat LeetCode-style interviews in real time. The pitch was simple. You screenshot the question from your OA(Online Assessment) or your live interview. You feed that screenshot into their AI. The tool spits back the solution on the spot. Not after the interview. Not as a study guide. During the interview itself.

What The Tool Appears To Do

Since a lot of these interviews are browser-based with an embedded editor and a panel showing the prompt, the workflow is pretty obvious. You grab a screenshot of the full prompt, including any constraints, examples, and hidden notes about input ranges or expected complexity. The tool likely uses OCR(Optical Character Recognition) to extract the text, identifies the problem pattern, and matches it to known solutions or composes a new one. Then it generates code in the language you need, along with edge cases and test handling. If the interviewer tweaks the prompt or adds a follow-up, you screenshot again and the tool adapts.

And it is not limited to the OA(Online Assessment). The page makes it clear you can use it in the final round too. The positioning was not coy. It was direct about being used during a real interview.

Proof: Watching the Unedited Runs With Interview Coder

Initially I was skeptical. A lot of tools promise the world and deliver something half-baked. So I kept scrolling. Then I ran into the part that said: throughout this whole video you will see me use Interview Coder for both the OA(Online Assessment) and the final round.

I watched the Unedited version end to end. I wanted to see the transitions, the timing, the lag, the edits, the handoffs between the question and the answer. What I saw was wild. The person screenshots the question. The tool feeds back a solution in real time. The code runs. The tests pass. Follow-up tweaks are handled. Output is corrected. They keep moving.

They used it to pass a Meta interview. They used it to pass an Amazon interview. The result was offers on the table. That is not a training montage. That is live fire. And it was mind blowing to watch because of how fast it bypassed the whole point of the exercise, which is supposed to be thinking on your feet and reasoning through a problem under pressure.

If you think I’m exaggerating, here is the video — watch it yourself. You’ll see exactly what I saw, step by step, in real time.

Inside My Old Company: How Teams Tried To Fight AI Cheating

Back at my previous company, I asked our recruiting team point blank: what is our strategy to deal with people using AI to pass coding rounds? Their answer was realistic, and it stuck with me.

One part of the approach was basically this: we know some candidates will use AI to get through certain rounds. We will try to catch them in the in person stage. That is where you can see body language, ask deeper questions, and push on the why behind the code. You can ask them to explain their decisions, change constraints, or build on top of their own solution. If they do not understand the code they typed, it shows up fast.

They also said something else that lines up with what these platforms already know. Some questions are marked internally with a kind of flag like AI has not yet been able to solve this problem. Whether it is LeetCode, HackerRank, or the platform we used, the signal is the same. Certain problem types remain hard for models. So recruiters were intentionally picking questions that had not been solved reliably by AI. Those got included in OAs(Online Assessments) and in face to face technical rounds because the hope was those questions would surface real problem solving, not copy-paste pattern matching.

The Interviewing.io Study: What Happens When People Cheat

When I saw Interview Coder in action, it reminded me of a study Interviewing.io ran about cheating in online technical screens. The study asked a specific question: how likely is it to pass if you cheat with AI compared to not cheating at all?

How They Set Up The Study

They split engineers into two groups. One group did not cheat. They were the control. They got one random question drawn from a pool that included three types of questions. The other group was allowed to cheat by using ChatGPT or similar tools. Those cheaters got one of three question categories:

• Verbatim LeetCode problems that appear exactly as they are found online.
• Modified LeetCode problems that keep the core pattern but change details, constraints, or the way the problem is phrased.
• Custom questions that are not pulled from LeetCode patterns and do not have obvious matches online.

The idea was to measure pass rates across these categories and see where cheating works and where it breaks down.

The Results That Matter

Here is what they found when they looked at pass rates:

• Control group, not cheating, random question: 53 percent pass rate.
• Cheaters given verbatim LeetCode problems: 73 percent pass rate.
• Cheaters given modified LeetCode problems: 67 percent pass rate.
• Cheaters given fully custom questions: 25 percent pass rate.

That drop from 67 to 25 when moving from modified to custom is brutal. And here is the kicker. The 25 percent for custom questions is not just lower than the other cheating categories. It is significantly lower than the control group. So a cheater facing a custom question performs worse than a non cheater facing a standard LeetCode style question.

Why Custom Questions Are Everywhere Now

This matches my experience as an interviewee and as an interviewer. I had two stages of interviews, one in 2023 and one in 2024. The difference between those years was stark. In 2024, the number of custom questions I saw went way up, especially in the quantitative trading space. Both in OAs(Online Assessments) and in the in person technical interviews, custom questions were the default rather than the exception.

It makes sense. Companies recognize that some candidates will try to cheat. If you give a verbatim or lightly modified LeetCode problem, AI can often solve it at a high rate, like the 73 and 67 percent we just talked about. But when you create a fresh problem that targets the fundamentals and forces you to reason, the pass rate for cheaters craters to 25 percent. That aligns with the shift I have seen firsthand.

The Wildest Part: No One Was Caught Cheating

There is something even more surprising in the Interviewing.io results. No one was caught cheating. Think about that. If you cheat and the worst outcome is that you fail the interview and try again later, then the deterrent is weak. There is no blacklisting. There is no permanent mark. You just do not pass that round. Then you queue up another attempt at some future date.

Personally, if you are caught cheating, I think you should be banned from interviewing at that company again. That is my take. When I interview candidates, the tells are often obvious if you watch closely. Someone pastes in a chunk of code and cannot explain a key line. They stumble on the invariants they supposedly used to derive the approach. Their eyes dart around the screen. You notice color shifts reflected in their glasses as a new window pops open. You hear the keyboard cadence change when they switch from thinking to pasting. Or you see them tab to a prompt window. It is not subtle if you are looking for it.

But here is the problem with remote interviews. Unless you are in the same room, you do not control the environment. You cannot always see the side monitor. You cannot always tell what is off-screen. And according to the study, interviewer confidence was actually high. Seventy two percent of interviewers said they were confident in their hiring decision. So not only were cheaters not being caught, interviewers felt good about the calls they were making. That is a scary combination if your pipeline depends on these interviews being an honest signal.

What This Signals For The LeetCode Era

Going back to that email from my subscriber, the take lands harder now. The LeetCode era looks fragile. If a tool like Interview Coder lets you screenshot a prompt and get a runnable solution in real time, then the barrier between LeetCode-style interviews collapses. Recruiters and hiring managers know this. Amazon is reportedly freaked, and I do not think they are alone.

What fills the gap? The subscriber called it. Companies will demand strong evidence of raw technical ability based on past work. Doing 500 LeetCode problems will not get you through the door. They will want to see projects you have built. They will want to see if you grasp the foundations. They will want to probe how you design, read other peoples code, handle edge cases, and stitch systems together. The signal will shift toward proof you can ship, not proof you can memorize patterns.

My Closing Thoughts: You Can Cheat An Interview, You Cannot Cheat The Job

I am really curious what you guys think about tools like this. Because here is where I land. Yes, some people will use a tool like Interview Coder to fluke their way into a six figure job. That might happen in an OA(Online Assessment). It might even happen in a final round if the interviewer is not watching for the tells or if the questions align with what the tool can handle.

But that is step one. After that, the work starts. There is no substitute for actually getting cracked. When your team needs you to build a custom backend solution that integrates cleanly into a messy, real world infrastructure, AI will not be there to hold your hand end to end. When the inputs are noisy, the constraints are evolving, and the failure modes are not spelled out in a prompt, you either know how to code or you do not. You either know how to read other peoples code and extend it without breaking the system or you do not. You either write fast, clean, scalable solutions to niche problems that no model has memorized or you do not.

Bottom line: you can game a LeetCode round. You cannot game being a strong engineer. Build the skill. Learn the foundations deeply. Get good at reading and writing code. Deliver working systems. If tools like this push companies to ask for stronger proof of real ability, the industry might actually get better at hiring people who can do the job for real.