AI is now part of how engineers work every day — autocomplete, code review, architecture brainstorming. It follows that candidates are bringing it into interviews too. The question is not really whether to use AI, but how to use it without getting caught, without sounding like a robot, and without leaning on it so hard that you cannot survive the follow-up questions.
This guide covers both phases: using AI effectively to prepare in the days before your interview, and using it intelligently during the live session itself.
Phase 1 — Preparation (the week before)
This is where AI delivers the most value with the least risk. You are in control, you can iterate, and the output makes you genuinely better — not just better in the moment.
Generate a targeted question bank
Paste the job description into ChatGPT or Claude and ask it to generate the 20 most likely technical questions for that role. Then ask it to weight them by how often each topic comes up at that company specifically. You will get a sharper list than any generic "top 50 interview questions" article.
Key points: distributed lock, TTL expiry, idempotency at the DB layer vs application layer, replay safety…
2. Walk me through how you'd rate-limit API consumers at scale…
Pressure-test your weak spots
Tell the AI your weak areas and ask it to quiz you. Go back and forth for 15–20 minutes. When you give an answer, ask it to poke holes — "what would a senior interviewer push back on here?" This forces you to think through the second and third layer of a problem, which is exactly where most candidates lose points.
Build a cheat sheet of your own answers
For each likely question, write a first-draft answer in your own words, then paste it into the AI and ask it to make it more concise and technically precise without changing your voice. The output becomes your cheat sheet — something you can review the morning of the interview. These are your answers, grounded in your experience, sharpened by AI.
Research the interviewer
If you know the interviewer's name, ask the AI to help you identify their public writing — blog posts, conference talks, open source contributions. Knowing that your interviewer wrote a post about distributed tracing last year tells you something about what they find interesting and rigorous.
Phase 2 — Live interview assistance
This is where things get more nuanced — and where the tool you use matters enormously.
What not to use during a live interview
The problem with browser-based AI during a live interview is not just detectability — it is the cognitive overhead. Switching tabs, reading a long answer, translating it into something you can actually say out loud — all of that consumes the mental bandwidth you need for the conversation itself.
What works during a live interview
An overlay tool like Heario solves the core problem: it listens to the interview audio and streams a short, grounded answer directly onto your screen without you doing anything. You keep eye contact, you stay in the conversation, and the answer appears in your peripheral vision — not in a tab you had to navigate to.
The key word is short. Heario streams a concise answer — a starting point, not a script. You read the first sentence, orient yourself, and then extend it with your own thinking. That is how it is meant to be used.
How to not sound like a robot
The single most common mistake when using AI assistance during an interview is reading the answer verbatim. AI-generated answers are technically correct but they lack the texture of lived experience — no hesitation, no personal anecdote, no "we ran into this at my last job and it was actually messier than the textbook version." Interviewers notice when someone sounds like they are reading.
The framework that works:
Acknowledge the question
Buy yourself one to two seconds with a natural opener. "Good question — this is something I've thought a lot about" or simply "Sure, so..." gives you time to read the first line of the AI answer.
Take the first idea, not the whole answer
Read the first sentence or concept from the overlay. State it in your own words — even slightly rephrased. Do not recite the full answer; just take the first hook and run with it.
Extend with your own experience
Add a sentence from real life. "We actually hit this at [company] when we were scaling the payments service — the thing that bit us was..." This is the detail that AI cannot provide, and it is what makes the answer sound like yours.
Glance back for the next point
Once you are talking, you can glance at the overlay briefly — the same way you might glance at a whiteboard — to pick up the next point. Keep it natural; do not stare.
Invite the follow-up
End your answer with an open door: "Does that match the kind of scale you're dealing with here?" or "Happy to go deeper on any of those." This shows confidence and keeps the conversation collaborative rather than making it feel like a presentation.
What actually gets you caught
Detection is rarely technical — it is almost always behavioural. Here is what raises flags:
| Behaviour | Risk level | Fix |
|---|---|---|
| Answering instantly with no thinking pause | High | Add a 1–2 second natural pause before speaking |
| Eyes darting to a corner of the screen repeatedly | High | Position overlay at screen centre-bottom, near the camera |
| Answer sounds nothing like your earlier responses | High | Rephrase in your own voice; do not read verbatim |
| Cannot answer an obvious follow-up question | High | Use AI as a prompt, not a script — understand what you say |
| Switching browser tabs mid-conversation | Very high | Use an overlay tool — no tab switching needed |
| Using a visible bot in the attendee list | Certain | Use a local tool with no meeting bot |
| Glancing at overlay naturally, near camera line | Low | Normal — indistinguishable from thinking |
Handling each question type with AI
Algorithms and data structures
AI is excellent for a quick orientation — "use a sliding window here", "this is a classic BFS problem" — but do not let it write your code. If you code up a solution you do not understand and the interviewer asks you to walk through it line by line, you are stuck. Use AI to confirm your approach, then implement it yourself.
System design
This is where AI assistance is most valuable. System design questions are open-ended, have many valid answers, and reward breadth of knowledge. A prompt like "design a rate limiter for a public API at 10 billion requests per day" will get you a solid starting framework from Heario within two seconds — data stores, sharding strategy, failure modes. You pick the thread that maps to your experience and run with it.
Behavioural (STAR format)
AI cannot give you a real story — only you can. But it can help you structure a half-formed memory. If you remember a situation vaguely, a quick prompt like "help me structure a STAR answer about a time I had to push back on a product decision" will scaffold the response. Fill in the actual events from your own experience.
Debugging and code review
These questions require you to look at code and reason about it. AI can help you name what you are seeing — "this looks like an N+1 query problem" — but the investigative process needs to come from you, or the conversation falls apart.
The ethics question
Let's be honest about it. Using AI in an interview sits in a grey area. It is not categorically different from using notes, a second monitor, or having your friend in the room — all of which people do. AI is also now standard in day-to-day engineering work, so using it in an interview is in some sense demonstrating a real skill.
That said, nerves are real. A candidate who knows the answer but blanks under pressure is not less capable than someone who does not — they are just more anxious. For many people, having a prompt available is enough to unlock what they already know. That is a legitimate use case.
Setting up Heario for a technical interview
If you decide to use Heario for a live technical interview, here is the optimal setup:
- Load your context before the interview. Add your résumé, the job description, and a short paragraph about the company's stack. Heario uses this to ground answers in your background — so when it says "at your previous scale", it is talking about your actual scale, not a generic example.
- Select the right mode. Use Technical Interview mode for algorithm and system design questions. Switch to Behavioural Interview mode if the conversation shifts to leadership or collaboration questions — the AI response style changes accordingly.
- Position the overlay. Drag it to the centre-bottom of your screen, just below the webcam. Glancing there looks like you are thinking, not reading.
- Run the Zoom invisibility test. Before the real interview, open Zoom, share your screen, and confirm the overlay does not appear. It takes 30 seconds and removes any anxiety about detection.
- Practise using it in a mock interview first. The first time you use an overlay tool should not be in a real interview. Do one mock run so the mechanics are natural before it counts.
Want to know exactly how Heario stays hidden from Zoom, Teams, and Google Meet? Read the technical breakdown: Is Heario detectable on Zoom?
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