The purpose of a screening is not to determine competence, it is to determine whether recruit and company want to work together, which cannot be automated.
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.
I'm more a syadmin type than a developer, but still get hit with online "testing" requests sometimes: a couple SQL tests for some support position, a couple psychological tests, etc. These are now a hard line for me. Why? Maybe I misunderstand...but my time is valuable, too. If HR or the hiring manager wants to reach out for a round 1 interview and then tell me a week later I'm one of your top candidates, and would I please take some online testing to continue the process, fine. But not the other way around.
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.
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.
Do you realize that your product will only lead to more time being wasted on the side of the applicants, who are already the weaker party? How do you justify that?
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.
whatsakandr|3 months ago
radug14|3 months ago
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.
The decision is always with the human.
doctor_radium|3 months ago
radug14|3 months ago
radug14|3 months ago
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.
Radu
abtinf|3 months ago
radug14|3 months ago
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.
t_mann|3 months ago
radug14|3 months ago
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.
Why do you think this leads to more wasted time?