Every time someone publishes a blog post about AI interview tools, the comments fill with the same accusation: "this is just cheating with extra steps."

I'm not going to dodge this. I'm going to engage with it seriously, because it's actually a hard question - much harder than the people on either side want to admit.

What "cheating" even means

The argument that AI in interviews is cheating goes something like this: you're being evaluated on your ability to solve problems independently. Using outside help defeats the purpose of the evaluation. Therefore, AI is cheating.

This sounds airtight until you ask the question: what counts as "outside help"?

What's the principled difference between using an AI to deeply prepare for a problem class, then encountering it cold in an interview... and using an AI to recognize that same problem class during the interview?

Both result in solving the problem with assistance. One just shifts when the assistance happens.

The argument for "it's clearly cheating"

The strongest version of the cheating argument isn't about cheating per se. It's about what interviews are for.

Interviews are signaling devices. Companies use them to predict whether you'll be able to do the job. The signal isn't "can you solve this exact problem" - it's "are you the kind of person who can solve problems like this."

If you use AI to solve the interview problem, you've gamed the signal. You got hired based on a false impression of your capabilities. Best case: you struggle in the role and burn out. Worst case: you cause real harm to the team and project.

This argument is honest and serious. Engaging with it honestly:

If you use AI to fake skills you don't have, this is a real risk. The job will eventually demand the skills you faked. Faking your way through interviews and then drowning in your first sprint is a worse outcome than not getting the job.

The argument for "it's not cheating, it's a tool"

The opposing view says: AI assistance is just the next evolution of tools we've always used. Calculators in math exams. Spell-checkers in writing. Stack Overflow during real engineering work.

The argument continues: nobody at your job will ever ask you to solve LeetCode hard problems with no internet access. The interview format is artificial. AI tools just adjust the artificial format closer to how real engineering actually works.

This argument is also honest, and partially correct. Engineers absolutely use Copilot, ChatGPT, and Stack Overflow constantly in their actual jobs. Pretending otherwise is theater.

But this argument has a weakness too: real work is collaborative and ongoing. You don't have to solve a binary tree inversion in 25 minutes alone. You have weeks. You can ask coworkers. You can read the codebase. The interview format may be artificial, but the skill it's testing - fast independent problem-solving under pressure - is occasionally real.

The truth that nobody wants to say

Both sides are partially right, and the tension is unresolved. Here's the unvarnished truth:

Technical interviews are a flawed evaluation system that companies know is flawed but use anyway because the alternatives are worse or more expensive.

Most senior engineers privately admit that interview performance correlates weakly with on-the-job performance. The correlation isn't zero. But it's far weaker than companies pretend.

What interviews actually evaluate:

If interviews were a perfect signal of job ability, AI use would be obviously wrong. But interviews are imperfect signals - and that's the gap AI tools are filling.

Three honest framings

I see three honest ways to think about this question:

Framing 1: Companies created this arms race

Companies introduced interview formats that don't actually evaluate job ability. Candidates have always tried to beat those formats - memorizing LeetCode patterns, studying Glassdoor reviews of company-specific questions, paying for interview-prep services. AI is just the latest entrant in this arms race.

From this angle, using AI is not cheating. It's leveling the playing field against companies that ask you to solve problems you'll never encounter at work.

Framing 2: The implicit contract matters

When a company says "we'd like to evaluate your problem-solving skills with this exercise," there's an implicit contract: you'll attempt the problem honestly, demonstrating your actual skill. Using AI to artificially inflate your apparent skill breaks that contract.

From this angle, AI use is dishonest in a way that other forms of preparation aren't. It's not about whether you got "outside help" - it's about whether you misrepresented your capabilities in the moment of evaluation.

Framing 3: Outcome is what matters

If you use AI to get the job and then succeed in the role, was anyone harmed? Not the company - they got a productive employee. Not you - you have a job. Maybe not even other candidates - maybe you were the right hire even if your interview signal was inflated.

From this angle, the question isn't "is this cheating" but "are you actually qualified for the job you're getting." If yes, the means matter less. If no, you'll be exposed quickly anyway.

How I actually think about it

Here's my honest position. I'm not going to pretend it's the only valid view.

I think AI tools in interviews are ethically gray for highly specific use cases and ethically clear in others:

Clearly fine:

Genuinely gray:

Ethically problematic:

The line for me is whether you're amplifying your real abilities or substituting for missing ones. The first feels like a tool. The second feels like fraud.

The "can I defend this answer" test

Here's a practical test that maps to ethical clarity for me: can you defend the answer if probed?

If your interviewer asks "why did you choose this approach?" and you can explain it, walk through alternatives, discuss trade-offs - you understood it. Whatever helped you arrive at it doesn't matter much. You demonstrated the skill being tested.

If they ask the same question and you freeze because you copied something you don't understand - you didn't demonstrate the skill. You demonstrated mimicry. That's the difference between using a tool and faking your way through.

What about the company's perspective?

Companies have legitimate interests too. If they're paying $200K+ for an engineer, they want to know they're getting one. The signal-distortion problem of AI tools is real for them.

But companies also need to recognize: their interview format created this problem. Decades of "trick LeetCode questions that don't reflect daily work" trained candidates to optimize for the format rather than the underlying skill. AI is the natural endpoint of that optimization.

Companies that want better signal need to update their interview formats:

These formats are harder to game with AI because they evaluate things AI can't fake - judgment, communication, specific past experience, ability to navigate ambiguity. They're also harder for companies to administer at scale.

The format is the bug. AI tools are just exposing it.

What I tell people who ask

When someone DMs me asking "should I use this for my interview," I usually ask three questions back:

  1. Can you do the job if you get it?
  2. Can you defend any answer the AI helps you generate?
  3. Are you using this to amplify real skills or substitute for missing ones?

If they answer "yes, yes, amplify" - go ahead. The tool is helping you communicate skills you actually have.

If they answer "no, no, substitute" - don't use it. You'll fake your way in and crash out. That's a worse outcome than not getting the job.

The honest meta-conclusion

This is going to sound like a cop-out, but it's the truth: AI tools in interviews are ethically defensible if you would also be ethically defensible without them, and indefensible if you wouldn't be.

The tool doesn't make you a fraud. The tool also doesn't redeem you if you already are one. It amplifies whatever you bring to it.

That's why we built Acemode the way we did. It's a tool for engineers to communicate their real abilities better - not a way for non-engineers to fake their way through.

Whether you should use it depends entirely on which one you are.