This is a super tough, but incredibly valuable thread. Thank you all for the raw feedback.
I need to be clear: I 100% agree with the core sentiment here. As a candidate, the hiring process is often broken, dehumanising, and feels like a one-way street. Many of you are right when saying a tool like this could be abused.
I'm not trying to automate the human part of hiring. I'm trying to fix the part that's already broken.
The real-world alternative at most companies isn't a friendly 1-hour chat with a senior engineer for every single applicant, that just doesn’t scale.
The alternative is:
1. A harsh, biased CV filter that rejects 95% of applicants in a couple of seconds.
2. A 4-hour take-home exercise that massively wastes your time and is genuinely pointless because anyone can vibe code it.
3. An algorithm test from a platform like HackerRank for which the majority of engineers have to prep many hours.
I built Niju to be less painful than those. It's a 20-minute, practical, "think-aloud" test. The AI's only job is to summarise the data so a human can review it faster, making it more likely they'll widen the funnel and give more people a shot beyond just their CV.
My goal isn't to replace engineers but to stop wasting their time on a broken process, so they can have better, human interviews with the top 20% of candidates.
It's a massive challenge, and this thread, as well as most of the others, show the raw nerve I've hit.
If they do what you said, they will have no way to actually differentiate between candidates so they will waste their time and money on using my platform. Doing screening calls asynchronously doesn't open the floodgates.
To your other replies, again, this is a screening interview. It aims to assess, in a short time, how you approach a day to day coding problem. It's not about specialised technical requirements - for that you jump on a dedicated technical call. Niju is supposed to sit at the beginning of the technical assessment process.
The challenges are designed for an average engineer at the job opening level (junior, mid, senior) to solve in approximately 10 minutes. Furthermore, they are practical day-to-day tasks that should not put pressure just by nature of what's being asked.
For your last point, a review takes on average 5 minutes for a hiring manager. And I think screening more is not inherently a problem. Imagine they turned down the dial on their CV filters and had more applicants do a technical screen - wouldn't that give more applicants an opportunity to shine? In most cases it unfortunately is a numbers game.
Again I want to make it clear that the AI is not driving any decisions, it just summarizes some data points.
The technical screening call typically happens after an initial screening chat with HR or the hiring manager. The tech screening interview comes in after that.
I agree and I would never use AI to properly interview someone.
This is a screening interview. It's at the top of the recruitment funnel. The alternative is seeing fewer candidates (because you can't have engineers do non-stop interviews) or just filtering heavily based on CVs. Neither option is good.
I understand and agree, but this is a technical screening. Typically you would have someone from HR have an initial conversation with the applicant to align. This comes after, if it's a go from both parties.
Furthermore, Niju does not automate the decision. AI is only used to create a transcript, a summary of the interview with, a list of important moments and a set of indicative scores on a number of criteria.
Hey! I think it's quite the opposite, and I'll explain why.
Let me just apply one example. A few years ago I was screening candidates over a 30-minute live coding interview covering pretty day to day stuff. That required a 30 minute investment from the applicant in what is a high-stress situation for many. I can't tell you how many times they seemed very stressed simply because they had to code in a live interview setting knowing someone is actively watching what they are doing.
Now compare that to a 20-minute screening interview where most of that pressure is gone. You can do it whenever you want to.
That is my rationale behind it, thinking both as an applicant and as a hiring manager.
I would never approve the use of async interviews further down the pipeline, but for screening purposes (from a candidate POV) I personally don't have any problems.
In my personal experience, screening software engineers has always put pressure on internal engineering teams. Over the years, I’ve tried different approaches to streamline the process, but nothing has really fixed the problem of investing engineering time into screening.
At the start of the year I went through BetterStack’s recruitment process. Their first stage, an in-house built async screening test, was a revelation for me. I thought this was a fantastic alternative for an early stage in the recruitment pipeline. Back in February, while I was actively hiring at the startup I was working with, I prototyped a solution and trialed it - it was a success.
Fast forward a few months and I’ve now been able to turn the early prototype into a product. Meet Niju.
Niju replaces the traditional screening call with a 20-minute, asynchronous, recorded coding session.
A candidate gets a link, shares their screen, and "thinks aloud" while solving a practical coding challenge (no abstract algorithms).
After 20 minutes, Niju analyses the entire session: the code, the audio, and the thought process. It gives the hiring manager a concise report, transcripts, code playback and the raw footage with the important parts annotated. This means that, on average, a Niju interview takes 5 minutes to review.
* Cheating: Yes, a candidate can use Google. That's the point. I want to see how they solve a problem, not what they've memorised. The screen recording shows their whole process.
* AI: The AI does not produce a "pass/fail" decision. It just summarises the data to help a human make a better, faster, and more consistent decision.
* Stack: As a solo builder, I'm keeping it simple: SvelteKit, DrizzleORM, BullMQ, Postgres, Redis, Azure OpenAI.
The goal is to help busy engineering teams reclaim their time.
You can try the first interview for free.
I’ll be here for a while to answer questions and I'd be honored to get your feedback.
I need to be clear: I 100% agree with the core sentiment here. As a candidate, the hiring process is often broken, dehumanising, and feels like a one-way street. Many of you are right when saying a tool like this could be abused.
I'm not trying to automate the human part of hiring. I'm trying to fix the part that's already broken.
The real-world alternative at most companies isn't a friendly 1-hour chat with a senior engineer for every single applicant, that just doesn’t scale.
The alternative is:
1. A harsh, biased CV filter that rejects 95% of applicants in a couple of seconds.
2. A 4-hour take-home exercise that massively wastes your time and is genuinely pointless because anyone can vibe code it.
3. An algorithm test from a platform like HackerRank for which the majority of engineers have to prep many hours.
I built Niju to be less painful than those. It's a 20-minute, practical, "think-aloud" test. The AI's only job is to summarise the data so a human can review it faster, making it more likely they'll widen the funnel and give more people a shot beyond just their CV.
My goal isn't to replace engineers but to stop wasting their time on a broken process, so they can have better, human interviews with the top 20% of candidates.
It's a massive challenge, and this thread, as well as most of the others, show the raw nerve I've hit.