About InterviewClue
We went looking for a decent interview copilot There wasn’t one
We’re a small team of UC Berkeley EECS grads, now senior engineers, with work experience across FAANG-level companies including Google, Microsoft, LinkedIn, Amazon and Uber. Sometime in the past two years we were recruiting for hot AI roles in the SF Bay Area, and we went looking for a decent AI interview tool to skip the weeks of rote-memorizing LeetCode hards.
We realized two things.
All of them suck You end up doing the copilot’s job
No, really. Most if not all of the ones we examined are vibe-coded products by larpers scamming people for exorbitant amounts of money.
Every one of them calls itself an AI interview “copilot”. In reality you’re the pilot, doing its job for it.
The pilot’s checklist
- You press a key to record your voice, so it can capture the exact transcript to send to the AI.
- The answer arrives as a jumbled wall of words with no structure, which you get to dig through while the interviewer waits.
- You take a screenshot every time you need a problem solved, with capabilities limited to what you can display on your screen at a given point in time.
Companies and code test platforms are aware of this fatal flaw and build their tests around it. Don’t believe us? See for yourselves:
They advertise frontier models. The backend is an LLM chatbot built on top of Sonnet or Luna at low effort, which won’t get past LeetCode mediums when it comes to finding you an ideal solution, let alone a clear explanation and approach.
That’s why every single ad you see is Two Sum with 15 lines of code. If that’s what you’re expecting from interviews in this new age of AI fluency, you’re in for a rough time.
None of them handle the modern interview They were built for the old one
Companies adapted fast, and they’ve moved beyond LeetCode.
Then
The loop we memorized for
Now
The loop companies run today
The algorithm round still exists. It’s one slice now. The rest of the loop hands you a repository with code already in it and asks you to build across several files. The problem comes in parts, and Part 3 shows up with inputs that break your Part 2 answer. A test fails in one file because of a bug in another. Someone shares a pull request and grades you on what you catch: bugs that span files, design issues, missing tests, API ergonomics, backwards compatibility, error handling.
Where every other copilot stops
Five things real interviews demand Only one copilot does them all
| What the interview demands | InterviewClue | Screenshot solversOne frame at a timeEveryone else | Chat overlaysA reply thread to scroll | Audio copilotsHear the call, not the code |
|---|---|---|---|---|
01Live coding across many filesEvery file you bring on screen is tracked and kept, not only the current one | Yes | No | No | No |
Context that survives every file switchCode, edits and requirements stay for the whole session | Yes | No | No | No |
02Multi-part problems that keep evolvingEach new part builds on the code and rules before it | Yes | No | No | No |
03A structured workspace, not a chat threadApproach, code, complexity and tests in fixed places | Yes | No | No | No |
04Real-time debugging across filesThe failure traced to the file that causes it | Yes | No | No | No |
Multi-file PR review with inline commentsEach finding pinned to its line, across six checks | Yes | No | No | No |
Bugs that span files | Yes | No | No | No |
Design issues | Yes | No | No | No |
Missing tests and coverage | Yes | No | No | No |
API ergonomics | Yes | No | No | No |
Backwards compatibility | Yes | No | No | No |
Error handling | Yes | No | No | No |
05Stealth backed by published evidenceLeft out of screen capture, the Dock and ⌘‑Tab · shortcut test published | Yes | Claim onlyNo published evidence | Claim onlyNo published evidence | Claim onlyNo published evidence |
Other tools are grouped by how they work · “Claim only” means stealth is stated without published test evidence
When a tool that answers one screenshot at a time forgets Part 1 before Part 3 is on screen, the tool loses nothing. You lose the interview. Maybe the one at your dream company, the one you don’t get to take twice.
So we built this tool For the top tech firms, by people who’ve worked at them. It worked
InterviewClue tracks any line of code, still or moving, and assigns it correctly with 99.5%+ accuracy, down to each second of activity. And the rare 0.5% where a line is misread? It’s corrected in the very next second, with a 100% technical guarantee. Every line of code you write, we see too.
The key notes from your discussion with the interviewer? We note those down too. And best of all, we remember everything for the entire session, even if you don’t.
Your screen changes. Session context follows.
It follows the whole interview as one session: live coding across many files, problems that evolve part by part, real-time debugging, and multi-file pull-request reviews with each comment pinned to its line. Approach, code, complexity and tests land in a structured workspace, each in a fixed place, where a chat thread would have you scrolling. System design gets the same treatment, from tradeoffs to architecture to data model. And the stealth claim comes with published test evidence you can open.
QYou ask
“Then why aren’t all the other copilots doing the same thing?”
AThe answer
Because it’s really hard.
I interned at the Waller Computational Imaging Laboratory at UC Berkeley my freshman year and picked up a lot of useful optimizations and processes. Some of them are the same processes that, behind the scenes, make that real-time, line-by-line live tracking possible and accurately filter the prompts, problem statements and requirements out of everything else on screen, whether you drag the IDE or minimize it.
While we’re not going to disclose our exact formula, we can say this much: it needs the same screen and audio recording permission as every other AI interview copilot, and nothing more.
We did take a slightly different approach, to make sure not even a monkey can fail. The harness is reinforced to run certain checks, and to construct approaches and explanations in a way that satisfies grading-rubric criteria from the top tech firms in the world.
Tech companies aren’t stupid. Their problems are designed to filter out bad AI copilot tools instantly, and we’ve sat on that side of the table. So it’s quite amusing to watch larpers who’ve never worked a day in FAANG, let alone a top-50 company, claim they’ve built something guaranteed to land you a spot where they’ve never been themselves.
Couple that with modern AI tools that let you streamline voice commands, to keep pace with the ever-evolving state of software engineering interviews in the post-LeetCode era, and you have interviewclue.ai: the only tool on the market today capable of handling anything tech companies throw at you.
QYou ask
“Sounds sus. How can I trust it will work?”
AThe answer
There’s a free trial, no credit card required, available when you download.
If you still feel another product suits you better, that’s fine. There’s always someone hungrier for that position who won’t make the same call. Every job search has its winners and its losers.
Our users are grateful you volunteered.