Acedly AI on HackerRank: Real-Time AI for HackerRank Live Coding (2026)
How Acedly AI works inside HackerRank's live coding interview — reading the problem, test cases, and editor while staying hidden from screen sharing. What to verify before your HackerRank round.
Devon Park
Head of Research, Acedly
What is a HackerRank helper?
A HackerRank helper is a desktop or browser-extension AI tool designed to assist a candidate during a HackerRank coding interview. HackerRank ships two distinct interview surfaces — CodePair for live interviews with a human on the other end, and CodeScreen for async assessments where you submit code on your own time — and the AI helper category exists for both, even though the appropriate use is very different.
Unlike a generic chatbot in another tab, a serious helper understands what HackerRank actually is: a heavy, browser-based coding environment with its own modified Monaco editor, a visible+hidden test case panel, a language switcher, and — crucially for any AI tool — an active proctoring layer that logs paste events, focus changes, and (when the customer enables it) webcam and screen recording.
The category exists because HackerRank is the default coding platform at a large slice of Big Tech and finance: Amazon's senior engineering rounds, Goldman Sachs, JPMorgan, Bloomberg, Capital One, Walmart Labs, IBM, and many companies that bought HackerRank for Work as their assessment vendor. If you have a phone screen for a principal-level role at one of these companies, there's a strong chance it's on HackerRank — and a strong chance you're searching for an AI tool that won't get you flagged.
Where HackerRank shows up: senior and principal rounds at Big Tech
HackerRank is the heavier-weight live coding product, and where it sits in a typical loop tells you what to expect:
- Amazon uses HackerRank heavily for SDE-2, SDE-3, and Principal Engineer phone screens, and for parts of the on-site coding panel. The questions tilt toward leadership-principle-flavored coding — a problem with constraints that reward the engineer who clarifies before coding.
- Goldman Sachs, JPMorgan, Bloomberg, Capital One run HackerRank for their software engineering pipelines, often at multiple rounds: an initial CodeScreen take-home, then a CodePair live round with a senior engineer.
- Walmart Labs, IBM, Cisco, Oracle ship HackerRank for engineering hiring, typically with CodePair as the live interview surface.
- Companies that bought HackerRank for Work (the enterprise assessment product) get CodePair, CodeScreen, and a customizable proctoring layer in one bundle — which is why HackerRank's anti-cheating signals tend to be on by default at larger employers.
The distinction between CodePair (live, with an interviewer in the call) and CodeScreen (async, no interviewer, customer-controlled time limit) matters more than people think. They share an editor, but the ethics of running an AI helper through them are not the same — and the AI-detection that HackerRank applies to each is also not the same. We'll come back to this.
How an AI helper works inside a HackerRank CodePair round
A real-time helper inside a CodePair round has four jobs, and each one has a constraint that's specific to HackerRank.
1. Read the problem statement
The problem renders inside HackerRank's left-hand panel — markdown plus rendered LaTeX for math-heavy problems plus the occasional embedded image for tree or graph diagrams. A helper that reads the screen at the OS level (not the DOM) catches everything, including the rendered math and the diagrams. A helper that scrapes the DOM tends to miss anything image-based.
2. Read the visible test cases
HackerRank shows visible test cases in a tabbed panel under the editor — usually two or three sample inputs and expected outputs — and hidden test cases that only run when you submit. The helper can read the visible ones; it cannot read the hidden ones, because they are not in the candidate's browser at all (they're evaluated server-side). Any tool that claims to "read all the test cases on HackerRank" is misrepresenting how the platform works. Acedly only reads what's actually on screen, which is the right thing — and we say so.
3. Read the editor in real time
HackerRank's editor is a heavily-modified Monaco. Some helpers that work on raw Monaco (LeetCode, Coderpad's Ace fork) silently fail on HackerRank because the wrappers strip or rename the events they hook into. Acedly does OS-level screen reading instead of DOM injection — which means we don't depend on HackerRank's editor internals at all, and we don't break when HackerRank ships a frontend update.
4. Generate code in the right language and idiom
HackerRank lets the candidate choose from a list of languages per problem (Python 3, Java 17, C++, JavaScript, Go, Kotlin, Swift, and more depending on the company's question pack). The helper has to generate code in the language the candidate selected — not its preferred language — and in the idiom HackerRank expects (read-from-stdin entry point for older problems, function signature for newer ones). Acedly handles 12+ programming languages and reads the editor's current language indicator before generating.
The whole pipeline runs in roughly 98 ms median end-to-end on consumer hardware. That's fast enough that the candidate can finish reading the problem out loud, glance at the helper's draft, and start typing their own version without an awkward pause.
HackerRank's anti-cheating signals — what they actually check
This is the section that matters most, and it's where most marketing copy lies. HackerRank's proctoring is more aggressive than Coderpad's, and pretending otherwise sets candidates up for a flagged submission.
Here's what HackerRank actually tracks, based on the platform's own documentation and its visible behavior:
- Focus changes. Every time the candidate clicks out of the HackerRank tab — to ChatGPT in another tab, to a notes window, to a Slack message — HackerRank logs a
focus_lostevent with a timestamp. The interviewer sees these in the post-interview report. A round with five focus changes during a thirty-minute coding problem looks suspicious and will get raised. - Paste events. Pasting code into the HackerRank editor triggers a
paste_detectedevent that's attributed to the candidate's account. This is hard to spoof; the event fires at the editor level, not the OS clipboard level. Helpers that paste code are leaving an obvious fingerprint. - Copy events from external sources. HackerRank can detect when the editor's content was sourced from outside the page — heuristics, not perfect, but good enough to flag the obvious cases.
- Screen recording and webcam (when enabled). HackerRank for Work offers an optional webcam + screen-recording layer that customers can turn on, and a growing share of finance and Big Tech customers do. If the recruiter sent you a CodeScreen link with a webcam check, you're on this tier.
- AI-generated code detection (CodeScreen specifically). HackerRank has rolled out heuristics that look for "AI-likeness" in submitted code — uniform formatting, unusual variable naming consistency, comment style that matches LLM defaults, suspiciously fast typing of large blocks. The detection is imperfect but it is improving. If you submit a 200-line solution with zero typos, no false starts, and exactly the comment density Claude prefers, you're in the flagged bucket.
Acedly is built around the constraint that the candidate still types. We don't paste, we don't autotype, we don't modify the editor, and we don't move the cursor. The helper renders on a separate, screen-share-excluded surface; the candidate reads it, decides what to type, and types at their own cadence — which means HackerRank's paste_detected and focus_lost events stay clean. But we're explicit about what we don't protect against: if the candidate types perfect, comment-perfect, idiom-perfect code in 90 seconds for a hard problem, HackerRank's AI-detection heuristics may still flag it. The cadence has to be believable.
CodePair vs. CodeScreen: where AI assistance is more vs. less defensible
This is the section we get the most mail about. We're going to be candid.
CodePair is a live coding interview with a real interviewer in the call. The interviewer asks follow-up questions, watches the candidate think, listens for misunderstanding, and probes when the code is too clean. An AI helper in a CodePair round is closer to a thinking aid — like a candidate having well-organized notes in front of them — than to outright cheating, because the interviewer is right there to test whether the candidate actually understands what they wrote. We think the reasonable use case for Acedly is here: the candidate uses the helper to avoid blanking, to remember a tricky API, to check an off-by-one before submitting, while still doing the talking and typing themselves. If you can't explain what your helper drafted under follow-up, the interviewer will find out — and that's the right correction mechanism.
CodeScreen is the async product. There's no interviewer. It's a take-home assessment with a timer, and the candidate's submitted code is scored against hidden test cases. Using an AI helper to autocomplete an entire CodeScreen submission is much closer to outright cheating than a CodePair use case is, because there's no human in the loop checking your understanding. CodeScreen's AI-detection heuristics are also more aggressive than CodePair's, for exactly this reason: HackerRank knows that a take-home is the highest-leverage place for a candidate to misuse an AI tool, and they've put more detection budget there.
Our honest recommendation: Acedly is a good fit for CodePair rounds. For CodeScreen, think harder. If the role explicitly forbids AI assistance and the company has invested in AI-detection (most large finance and Big Tech customers have), submitting AI-generated code is risky in a way that goes beyond etiquette — it can end the process. You should make that decision deliberately, not by default.
Comparison: AI helpers on HackerRank, head to head
The comparison below is what we use internally when we evaluate competitors on HackerRank specifically. Different from the generic "AI interview assistant" matrix because HackerRank's anti-cheating signals matter more here.
| Feature | Acedly | Browser-extension copilots | Desktop OCR copilots | ChatGPT in another window |
|---|---|---|---|---|
| Reads HackerRank's modified Monaco editor | Yes (OS-level screen read) | Sometimes (breaks on HackerRank wrappers) | Yes (OCR-based) | No |
| Reads visible test cases | Yes | Some | Yes | Only if pasted in |
| Generates code in 12+ programming languages | Yes (Python, Java, C++, Go, Kotlin, Swift, JS, TS, Rust, SQL, PHP, Scala) | Limited | Limited | Yes |
| End-to-end latency | ~98 ms median | ~500–900 ms | ~700 ms–2 s | ~3–6 seconds |
| Stealth on screen share | Yes (OS-level capture exclusion) | No (browser tab is visible) | Partial | No (separate window) |
| Triggers HackerRank's paste event | No (candidate types) | Often yes (autopaste) | Sometimes (autopaste) | Yes (manual paste) |
| Triggers HackerRank's focus-lost event | No (helper is hidden, candidate stays in tab) | No (in-page extension) | No (separate display surface) | Yes (alt-tab) |
| Verified across 8 interview platforms | Yes (Zoom, Teams, Meet, Webex, Lark, Chime, Coderpad, HackerRank) | Usually one platform | Variable | N/A |
The two rows that decide most candidates' choice are the paste-event and focus-lost rows. Browser-extension copilots and desktop OCR tools that autopaste leave a trail HackerRank's report will show. ChatGPT in another window forces the candidate to alt-tab, which logs focus_lost events the interviewer sees later. Acedly's design — the candidate types, the helper just shows — is what keeps both signals clean.
The 10-minute pre-interview checklist for a HackerRank round
Before you turn on Acedly for a real HackerRank interview, run through this checklist. Most blunders during a CodePair round come from skipping one of these.
- Practice on HackerRank's free practice problems with Acedly running. Don't make your first HackerRank session with the helper be the real interview. Solve two problems — one easy, one medium — with Acedly on, and watch where your eyes go. If you feel pulled to read the helper's code verbatim, slow down; the cadence has to be believably human.
- Never paste code. Acedly doesn't paste, but reinforce the habit anyway: even if a teammate's snippet is sitting in your clipboard, type it. The HackerRank
paste_detectedevent is the single most damning signal in a post-interview report. - Pick a language you can type fluently. If your helper writes Kotlin and you can't type Kotlin without thinking, the slow typing will look fine but your verbal explanation will fall apart on the first follow-up. Pick the language you'd be most comfortable in if the helper crashed mid-round.
- Have a clean local IDE open as a scratch pad. Some candidates think out loud by sketching pseudocode in a separate editor. That's fine, and it's a normal interviewer-visible move when you say "let me sketch this on paper" — but make sure that scratch pad is on the same screen and visible to the interviewer; don't put it on a hidden display where it looks like you're reading off it.
- Verify the Acedly hotkey works under Chrome's focus model. HackerRank's CodePair runs in Chrome and captures most keystrokes. Test that your show/hide hotkey for Acedly still fires when the editor has focus — some candidates discover during the interview that their helper hotkey is shadowed by HackerRank's own shortcut. Pick a hotkey HackerRank doesn't use (avoid Cmd/Ctrl-S, Cmd/Ctrl-Enter).