Last month I watched someone demo three different “AI interview helper” tools in a Slack community I’m in. All three claimed to do basically the same thing. One of them was a flashcard app with an AI label on it. One was a live audio overlay that lagged by two seconds. One actually worked. The terminology in this category is a mess, which makes picking the right tool harder than it should be.
This is a breakdown of how I’d think about the category in 2026, what the tools actually do, and where I’m uncertain.
Two very different kinds of tools share the same name
The first type is a preparation tool. You practice with it before the interview. It gives you mock questions, feedback on your answers, and sometimes generates questions tailored to a job description you paste in. ChatGPT does this reasonably well for free. So does Pramp for peer-to-peer technical practice. So does Interviewing.io if you want live sessions with real engineers, though that’s expensive.
The second type is a live copilot. It runs during the actual interview, listens to the conversation, and surfaces suggestions in real time. This is the more technically complex category, and the one where product quality varies most.
These two types are frequently described with identical language, which I think is partly marketing and partly because most people writing about them haven’t used both. They solve different problems for different people.
Who actually benefits from a live copilot
Not everyone. This is worth being direct about.
If you’re a junior engineer who hasn’t done much LeetCode prep, a live AI overlay won’t save you in a coding round. The interviewer will ask follow-up questions and probe your reasoning. The overlay won’t answer those follow-ups in a way you can use coherently if you don’t understand the underlying concept.
The people I’ve seen get the most out of live copilots are in a specific situation: they have the skills for the job, they’ve done the prep work, but they perform significantly worse under pressure than in practice. Interview anxiety is real. The BLS Occupational Outlook for software developers projects strong continued hiring through 2032, which means companies are interviewing a lot of people and candidates are going through a lot of interviews. That volume creates real anxiety for a lot of engineers who are genuinely qualified.
For that group, a tool that surfaces a STAR framework prompt or a system design trade-off reminder in the first few seconds of a question can meaningfully reduce cognitive load. That’s not cheating. That’s accommodation for anxiety that would otherwise make someone look less capable than they are.
The prep tool category: honest take
For most engineers, the highest-use interview prep tool is still something like Claude or ChatGPT used properly. Paste in a job description, ask it to generate 10 behavioral questions specific to that role, answer them out loud, paste your answer back, ask for critique. That loop, repeated for 3 or 4 hours, is more useful than any purpose-built prep platform I’ve seen.
Purpose-built prep tools add value if you need structure you can’t impose on yourself, or if you’re preparing for very specific interview types (FAANG system design rounds, for example, where format consistency matters).
I don’t have a strong view on which prep platform is best in 2026. The field is moving fast and I’d rather not pretend I’ve benchmarked all of them recently.
Common mistakes I see in this category
Using AI suggestions as a script rather than a prompt. If you read back AI-generated text verbatim in an interview, interviewers notice. The vocabulary and sentence structure don’t match how you speak, and follow-up questions expose it immediately. The right use is to glance at a key phrase and then answer in your own words.
Skipping prep because you have a live tool. This is backwards. The live tool works better when you’ve already done the work. It’s a memory jog, not a knowledge base.
Picking tools based on marketing rather than actual trial. Most live copilot tools offer a free trial. Use it. Specifically test: does the latency feel acceptable? Does the suggestion appear before you’ve already figured out the answer yourself? Does it work in Google Meet and Zoom without configuration pain?
Craqly in this context
Craqly is a live copilot, not a prep tool. It listens during the interview and surfaces answer suggestions you can see and the interviewer can’t. It’s one of the few tools in this category that’s explicitly designed for the live interview context rather than retrofitted from a transcription or note-taking product. If you’re in the group I described earlier (capable, prepared, anxious under pressure), it’s worth trying the free tier to see if the latency and suggestion quality work for your style.
If you want a prep tool, it’s not the right fit. Use Claude or a dedicated mock-interview platform for that.
What I’d actually do in 2026
Spend the first two weeks of any serious job search doing prep work with a general LLM. No special tool needed. Then, for the live interview stage, try one or two live copilot tools on lower-stakes applications before using them for your top-target companies. The worst outcome is discovering the latency breaks your concentration during an interview you really wanted to nail.
And regardless of what tools you use: one great answer with a specific number in it (“reduced build time from 23 minutes to 7 minutes”) will do more for your chances than any AI overlay. The tools are multipliers, not foundations.