Transcript

"Humans Are The Problem" - Why AI Is Taking Over The Job Interview | Manouj Gupta

From Founder's Story · Episode page · Watch on YouTube

· 27 min · 4,112 words · 32 timestamped sections

This is the full, timestamped transcript of ""Humans Are The Problem" - Why AI Is Taking Over The Job Interview | Manouj Gupta", an episode of Founder's Story published January 15, 2026 (27 min, about 4,112 words). It mentions 14 people, works and ideas, including AI, Hiring, Manoj, I Jupiter, ACNET.

What this episode is about

The discussion highlights the significant issue of high employee turnover, with nearly half of new hires leaving within two years, attributed to outdated hiring practices that rely on resumes and gut instincts rather than data-driven approaches. Manouj Gupta introduces "I Jupiter," an AI-driven interview agent designed to provide a unified and objective assessment of candidates, emphasizing a necessary mental shift for leaders to embrace technology in hiring rather than merely associating thoroughness with time.

Key takeaways

  • Nearly half of employees quit within two years; perhaps they're just on a scenic route to dissatisfaction.
  • Businesses embrace data-driven decisions everywhere—except when hiring. It's like using GPS to navigate, then deciding to close your eyes.
  • The real hiring crisis isn't speed; it's clarity. Candidates deserve an unbiased, streamlined assessment—no more guessing games.
  • In hiring, humans often err; AI could be the sleep-deprived interviewer's saving grace, minus the coffee breaks.
  • Critics fear AI drains the human touch in hiring, but a more accurate evaluation might just revive the human spirit.

Who speaks in this episode?

What is discussed, and when

  1. – 5:00: Hiring, I Jupiter, Manoj, ACNET
  2. – 10:00: Hiring, Elvis Dan, Clarity, Hiring Managers
  3. – 15:00: Hiring, Clarity, Hiring Managers, 150,000 interviews
  4. – 20:00: Hiring, Clarity, Human Resources, Talent
  5. – 25:00: Resume, Hiring, Clarity, Hiring Managers
  6. – 27:16: Hiring, ACNET, www.acnet.com

Notable quotes from ""Humans Are The Problem" - Why AI Is Taking Over The Job Interview | Manouj Gupta"

  • Contradiction. Businesses were becoming more datadriven everywhere except at the moment when it comes to hiring people.
    about Hiring · at
  • Software making the platforms working with AI agents which we know are the future and I know that's what you're doing with ACNET so Manoj I'm very curious around why you even…
    about ACNET · at
  • About the absence of a unified objective way to understand a candidate end to end. Once we saw that clearly building acnet became less about creating another tool and more about rethinking how the talent should be evaluated.
    about Manoj · at
  • Then the agent gives those questions to the candidates as well and then puts all these things together your resume what has come out of the resume how you have done the…
    about Resume · at
  • Second thing is once the assessment happens suppose once the assessment happens then final decision is to be taken by the hiring managers themselves. It is not that AI has…
    about Hiring Managers · at
  • Interviews meant better decisions. More rounds meant lower risk. That assumption no longer holds. In 2026, quality will come from clarity, not duration.
    about Clarity · at
  • This is what this talent is about and then take that base and take the decision all five stakeholders can then take that base and take the right decision about that candidate. That's.
    about Talent · at
  • Things. I think people will just understand how better they can use the service more and more. And thank you so much for joining us today on Founders Story.
    about Elvis Dan · at

Who and what is mentioned in this episode?

People

  • Manoj — Person · Main guest · 1 mention · first at
    Manoj explains the problem ACNET targets (fragmented, subjective hiring) and describes how their AI agent I Jupiter performs end-to-end evaluation.
  • Elvis Dan — Person · Host · 1 mention · first at
    Dan drives the conversation with practical hiring pain points, skepticism people have about AI in hiring, and questions about resume strategy and 2026 implications.

Books & papers

  • StrengthsFinder — Book · Referenced framework · 1 mention
    Dan references StrengthsFinder to emphasize placing people into roles aligned with strengths, aligning with the episode’s theme of better fit and reduced mis-hires.
    It reminds me of... strengthinders the book.

Companies & orgs

  • ACNET — Company · Core product/company discussed · 2 mentions · first at
    ACNET is the company building the unified AI-driven hiring evaluation platform, positioned as a solution to inconsistent and biased/fragmented hiring workflows.

Products & tech

  • AI — Product · Core topic · 34 mentions
    AI is presented as the mechanism to standardize and scale candidate evaluation, reducing inconsistency, time pressure, and missed talent in hiring.
    We have created an AI agent... called I Jupiter.
  • I Jupiter — Product · Core product/engine · 2 mentions · first at
    I Jupiter is ACNET’s AI agent that conducts interviews, administers assessments, synthesizes signals, and produces ranked reports for hiring managers.
    Way to understand a candidate end to end. We have created an AI agent underlying AI agent called I Jupiter and it interviews the candidate. Then it assesses the person whether…

Concepts & topics

  • Hiring — Concept · Core topic · 21 mentions · first at
    The episode centers on fixing hiring outcomes by replacing fragmented, subjective processes with unified, consistent evaluation and clearer role definitions.
  • Clarity — Concept · Key principle · 6 mentions · first at
    Clarity is described as the prerequisite input (role definition, what 'good' looks like) that enables AI to evaluate consistently and improves decision quality.
  • Hiring Managers — Concept · Primary user/stakeholder · 4 mentions · first at
    Hiring managers are positioned as the decision owners who must define role clarity and use AI reports to make final decisions rather than delegating judgment entirely to AI.
  • Resume — Concept · Key artifact in hiring workflow · 5 mentions · first at
    Resumes are described as incomplete and often 'fluffy' signals; ACNET uses AI to interpret resumes in context and combine them with interviews and assessments.
  • Talent — Concept · Outcome focus · 3 mentions · first at
    Talent is framed as being missed by traditional screening limits; AI enables evaluating far more applicants and finding better fits.
  • Human Resources — Concept · Stakeholder domain · 2 mentions · first at
    HR leadership (including CHRO) is referenced as needing to change evaluation philosophy and adopt structured, AI-enabled processes.
    CHRO needs to move away from evaluation by accumulation.

Places & events

  • 150,000 interviews — Event · Training/validation milestone · 1 mention · first at
    Manoj cites 150,000 interviews conducted before launch as evidence that the AI is trained across industries and can produce credible evaluation reports.
    And what we have done is we have run our we have taken about 150,000 interviews before we have launched the product right so our AI is very well trained in u in how to evaluate people within the different industries. So when we go to the.

Sponsors

  • www.acnet.com — Company · Call-to-action / sponsor-like mention · 1 mention · first at
    The website is provided as the primary way for corporations to request a demo and engage ACNET’s service.
    So they can go to www.acnet.com acnet.com and they can fill in the request that they want to have the demo of the platform. That's how the that is.

Full transcript with timestamps

about 40 to 50% people leave their jobs in one or two years after they have joined the company is a big disaster. What stood out to me was this contradiction. Businesses were becoming more datadriven everywhere except at the moment when it comes to hiring people. So gap which we were looking wasn't about hiring faster or slower. It was about the absence of a unified objective way to understand a candidate end to end. We have created an AI agent underlying AI agent called I Jupiter and it interviews the candidate. Then it assesses the person whether that person is fitting into the role. The biggest shift leaders need to make is mental not technology. For decades we have equated uh thoroughess with time. That assumption no longer holds.

So Manoj uh AI and hiring this is so newsworthy right now. you have a lot of different opinions and thoughts and I'm glad to have you on because I want to talk to somebody who's building the software making the platforms working with AI agents which we know are the future and I know that's what you're doing with ACNET so Manoj I'm very curious around why you even started this company what was the spark what happened whether it's in your business or what you saw with other businesses that made you say this is something I need to start and I need to start it now.

Yeah. Okay. Great question, Dan and thank you for asking me and appreciate you speaking to me uh today. Um so Dan, here is the thing. For years um I've seen the companies invest heavily in sourcing, branding and pipelining. But when it comes to actual evaluating people, the process had not evolved. decisions were pretty much made uh driven on réumés uh fragmented interviews, gut instinct and so forth. What stood out to me was this contradiction. Businesses were becoming more datadriven everywhere except u at the moment when it comes to hiring people or selecting the right people.

resumeumage said one story and uh interviews said another story and assessments uh were done from a different systems and all together the leadership was expected to stitch all these things together under a time pressure. So I thought that how about we try to create something which is one unified platform which can do all these things together and give the executives a clear view into the person whom they're trying to hire. So the gap which we were looking wasn't about hiring faster or slower. It was about the absence of a unified objective way to understand a candidate end to end. Once we saw that clearly building acnet became less about creating another tool and more about rethinking uh how the talent should be evaluated and how what we can do so that the hiring managers can take a decision with uh with clarity that's what made me uh think about uh creating this platform

so in my experience I found a lot of managers ers aren't really taught like how to effectively hire. And what I've seen for many years was that people are placed in the incorrect positions like you mentioned. People put someone in a position that is not really to their strength and then what happens in the end they have to be fired when it in my opinion it wasn't always their fault. I'm very interested though in how you're leveraging AI agents to help in this process and when did you realize though that like what I'm saying that humans sometimes are the bottleneck and it's not the technology. So what are you specifically doing with AI agents to solve this and how do these AI agents work? Okay. So we have got we have created an AI agent underlying AI agent called I Jupiter uh which is uh our main uh engine uh software engine which is AI agent if you may and u the way uh it looks is we ask the hiring manager to

define what role they are hiring for. That clarity has to come from the manager. Now once that role has been defined after that AI agents take that uh uh uh definition of that role goes through all the résumés and look from the context perspective what the manager is looking for hiring manager is looking for searches through the résumés finds out ranks them what is the best rums they have uh it finds out based on the role Then it sends out it takes the interview or conducts the interviews on uh on behalf of the manager hiring manager.

They're like me and you are talking the agent also come uh online in terms of a avatar and it interviews the candidate and then it assesses the person whether uh that person is fitting into the role. So this is all AI uh being assess doing the assessment of the of the candidate and then if for the required if the company also wants them to give some technical assessments like uh engineering drawings to do some engineering drawings or write some code then the agent gives those questions to the candidates as well and then puts all these things together your resume what has come out of the resume how you have done the interview and how you have done uh the technical assessments and then ranks those candidates. So and it gives uh the hiring manager a good report which tells them what are the what are the positives of the candidates and what are the if there are any negatives then it uh mentions a few things there so

that uh manager can now can take uh the decisions clearly on the candidate. So that's how it works.

I needed this when I used to hire in corporate. I would do so many interviews that I'm not even kidding, I've fallen asleep in interviews before and I felt like I I couldn't always be consistent because of what was happening in the day, how I was feeling. There was a lot of factors that obviously as humans that we have that AI does not. So, I feel like I didn't always give a consistent interview with every single person. This to me is huge. Now, some people, if I mention this, they freak out when you talk about AI and hiring because I think they just don't understand it, right? Or they think, oh, it removes a human touch.

What do you think that they get wrong about thinking this way when it comes to AI and the hiring process and what you're doing? Then one important thing which we have to understand is AI is not uh or the engine which we have got is we have made sure that it is not bias. So everybody who comes onto the platform is being put on the same level no matter what. So that is the first thing. Second thing is uh once the assessment happens suppose once the assessment happens then final decision is to be taken by the hiring managers themselves. It is not that AI has taken a decision and given it to hire hiring manager or it has been taken the decision and companies are going to hire. No, we want hiring managers still to look at the decisions coming out from the AI agent and so that it is more of a tool for them uh to to select the candidates rather than uh you know blindly accepting whatever AI is saying.

So we expect that hiring manager to go through the reports all the reports which have been given and then um take the decision. So human human is not out of the picture. Final interview we still expect just let's say I get 500 résumés for a job or 500 candidates apply. Now how much time it will take for us to evaluate 500 people at one go. It's not possible. With the AI agent, we can evaluate and take the interviews whatever the process we want to fit in. Whether we want to go through the resumes that can be done within hours taking the interviews can be done within a single day. Obviously, if uh scheduling can be done with a single day u and interviews can be taken in the single day as well.

Then comes the technical assessment can also be done with a single day. So 500 candidates can all be evaluated probably in a day or two and the reports can be generated and then the ranking can come out and then the hiring managers can look at that those rankings and call those people instead of 500 people now they can call three or four people or 10 people for the for the job interview for the final interview and take the selection uh take the decision. So that's the help hiring manager is getting here. And what I used to happen before is if I get 500 rumés then the recruiters get involved. Recruiters will nobody goes through 500 rums. Who has got time to go through 500 rums? You will take maybe 10 or 20 or 30 and give it to the hiring manager to take it forward. What about those 450 people who were in the line? They are not looked at. Now it's a level playing field and everybody can be evaluated properly. So

it's a good thing for everybody. If there's a people who are the right fit, they will get the job. If the people are not the right fit, then um they might be used into some other places where they can be fit.

Man, I love that. I I that's a great way to look at it. And that I mean yeah you normally that's why it's so hard to get many jobs I think because you saw you know some roles there could be thousands of people that are applying. I I remember applying to roles so many years ago and just seeing it would show you like you know 3,000 people applied to this position. I'm thinking like there's no way that I will ever get this job, right? It's so hard to get into the system. So, the fact that you're basically like cloning yourself and you can have AI go through all of those 3,000 in a day or two days and then you can really evaluate. I think this is great for companies because I think they can find more talent. you can find more talent, talent that you may not have found before when you're the fact that you you you know you're working with uh you know technology that for a lot of corporations and enterprise I'm sure uh

they've never used before and this is something so new and anytime you know you're selling a service to I think a corporation or enterprise that is new there's always challenges with that. So what do what what for you has been the hardest part convincing these companies that you know using ACNET using these AI agents and and how much this can benefit their organization. Yeah, I think um uh convincing uh once they have once they understand um the vision and once they have seen um uh the taken the demo, I think convincing has not been uh very difficult for us. they can clearly see the value and once they started seeing the reports which have come out and we uh and what we have done is we have uh run our uh we have taken about uh 150,000 interviews before we have launched the product uh right so our AI is very well trained in u in how to evaluate people within the different industries. So when we go to the

companies and when we show them the report and we give them open open field, you come in, you tell us what you're looking for, they just have to say like we want to hire for let's say um aviation engineer, let's say you just say that the AI will draw the whole job description for you. Then you can look at the job description and tweak it the way you want to tweak it. You can add to it and put your context what actually you are looking for in the candidate and after that uh the AI will do all the job for you. So once we and the when the report comes out they themselves say that or the questions when they ask the in the interview for the candidates they themselves are uh saying the the customer themselves say that some of the times we don't even think about the questions or we miss out on the questions which are the very relevant because we are against time or we are uh you know so these are some of the things

which AI is able to help them with and the clarity which they get it uh about the candidate is something which uh which uh they have liked it. So uh you know as we are rolling out we are seeing more and more customers are opening to it because they can see the value and because it's not biased they are um they are they are they are happy that they can get some candidates which uh which might have they might have lost otherwise. So now that you've done so many what do you have any data that you can publicly share around uh you know maybe impacts on this or maybe even uh you know the interviews that it's done any any data that would be interesting around either the person be the interviewee or on the corporate side like is what's the outcomes from this?

Yeah, I mean uh we can we have got the data to share. I mean every customer which comes in they want to see the data and we are giving them the data u to uh to show or we are showing them the data uh which we have trained our AI agent on and um that's how they are able to take the decision on us. So there was there was always a phrase that people used to tell me um when I had to do a lot of hiring. It was you know hire fast. And I think the reason is because we you know the hiring process takes a while. You're always so busy as as a business leader and you need to get people in because if they're not in you can't really your company doesn't function. So at the same time when you hire fast as a human you can unfortunately compromise the quality which I think is the amazing part of leveraging AI. So how do you see now in 2026 these uh people from human resources seuite to business leaders how can they leverage

this now currently without the compromise? Yeah. So then the biggest shift leaders need to make is mental not technology. Okay. That is important. For decades we have equated uh thoroughess with time. More interviews meant better decisions. More rounds meant lower risk. That assumption no longer holds. In 2026, quality will come from clarity, not duration. CHRO needs to move away from evaluation by accumulation. Collecting more resumeumés, more interviews, more opinions and towards evaluation by and more towards evaluate.

They have to go more towards evaluation by design. That means defining what goods good looks like upfront that is important and letting systems evaluate consistently against that definition. So if the clarity is there what exactly they are looking for and you just feed that in there and I let the system do the job the or AI agents do the job from there. Another critical shift is ownership. Hiring decisions can no longer sit across five stakeholders with no single source of truth. You know, I mean, everybody is taking their own decisions.

Everybody is coming with their own uh inputs and so forth. Leaders need a unified view that allows them to decide. So, if the system is there right, I mean it can give you one clear indication. this is what this talent is about and then take that base and take the decision all five stakeholders can then take that base and take the right decision about that candidate. That's something which is going to take and finally speed and quality should no longer be treated as tradeoffs right with AIEL structured evaluation organization can move faster because they can they are evaluating better that's what I feel

I love that you can get more resumes the the more the better and you can have the AI do more where it's kind of the opposite as humans, right? Like you didn't want to have 300 people apply to a job because you could never get through that. You want like 20 people so you know you can get through 20 people. Uh I'm very fascinated with AI agents just in general. I mean the things I hear about AI agents like I have a marketing agent now I have a hiring agent. I have, you know, this agent that a sales agent and there's so many great things from a business perspective. I think this technology is going to completely transform everything that we do. How do you see like what's the picture? If you could paint me a picture like five years from now, three years from now, maybe five is too long, right? Because things change so fast. Three years from now, what do you think in this process of business is going to be automated? like

what does the world look like then? So I think few things um one is right now the process is um the evaluation process is all broken I I feel or it is not there it is there but it's look very different for example you send a resume the recruiters will take the resume and then they will read the resume and then somebody else will go for the interview maybe they will take the interview somebody else goes for the interview then there's a system which is going to take the various evaluation I think all this will go away I feel uh what will happen uh if you look at maybe uh in couple of years or four years or five years whatever we may say um that uh hiring managers will be self-s served what you need you just input that data and after that everything will be all you know touchfree or touchless the AI agents will work behind the scene they will get you the candidates the best candidates available uh based on what is the

clarity you have provided to them and it will sort out from so many candidates and give you few people which you can look at them and take a decision. So your decision will be uh faster, quicker at the same time it will be uh it will be more clearer that the person you have hired is the right person uh for your job. That's how I think. So it will become more touchless if if you may. Right now we have got so many people involved even for one one hire right. So that will shrink or that will cut down I feel

well for a hiring perspective I hope that what you said is true around less people and being involved. It's like less minutia and I think more people will be hired better for their job and it just reminds me of like strengthinders the book like I am so big on wanting to put people in the place that really fits to their strength instead of hiring people for the wrong job because I personally have been fired more than one time and I always felt it was because I was not really hired for the right role and you know which I think this can eliminate a a lot of that. Final question here because I I think this is going to be really big right now. People want to understand if I am filling out a resume, they're filling out a resume almost for AI. I hear this in the news all the time.

People are like, I I fill out my resume for AI, knowing AI is kind of the first step. Does it really matter or is there like one or two things that people should be doing when they're filling out a resume or filling out for a job?

Yeah, I think um Dan, great question. Uh you know, let's let's let's look at why why people get into the wrong buckets within the company. Let's first talk about that. People want to get the job because they want to live their life. They want to earn money and so forth, right? Now why they are not happy is because what they're doing they got the job but what they're doing is not the right fit for them. That's that's the reality. And what happens is once they get the job the managers find out they also find out that they are not they they leave themselves and the manager later on finds out that you know they are not the right fit. What is more important is rather than AI writing a resume for them, they AI can write the resume. I mean you can get the grammatical mistakes out of it. But I think what is more important is one should be honest what they can they are good at and they should try to sell themselves for what

they can do better and that's what is more important for for uh that will come very helpful in the evaluation when they are going through the evaluation what people don't do is that they write the resume but they put lot of fluff in there. What is more important is that put the responsibilities and what are the success stories which they have which are behind them and put some data around the success stories which they have and let then the AI do its own job and I'm sure if they are um they are good at what they do and they they are you know that data is there I I I don't see any reason AI not uh you know selecting them or put putting them in front of the hiring manager.

I think that is very important. No, thank you for sharing that. I I've been thinking about this. I keep reading about it. So, I was excited to get someone like yourself on to really dive into these things. I love all things AI, good, bad, amazing, ugly. I mean, there's so many incredible things. we can solve so many problems and I hope we we try and use AI for good more than we use AI not for good in the future. That's my hope and obviously people like yourself building these type of companies. So if people want to get in touch with you uh they're a corporation they need to use the service how can they do so?

So they can uh go to www.acnet.com acnet.com um and they they can uh fill in the request that they want to have the demo of the platform. That's how the that is the right way to uh get in touch with us uh as of now.

Well, my nose is gooped up. I mean I can you got to come back when you've when you've hit like 10 million or 50 million uh you know data points come back. I I would love to hear more and share what are you seeing. I think the interesting part too will be that. So how you know how many people get hired and then how long do those people stay versus when just a human does it and AI wasn't involved. I think there's going to be so many interesting points in 2026. Love to have you back on to talk through these things. Um I think I think people will just understand how better they can use the service more and more. And thank you so much for joining us today on Founders Story.

Thank you. Thank you Dan. Thank you. Appreciate for having me here.

Questions about this episode

Who speaks in ""Humans Are The Problem" - Why AI Is Taking Over The Job Interview | Manouj Gupta"?

Dan (Guest), Manouj Gupta (Guest).

What is ""Humans Are The Problem" - Why AI Is Taking Over The Job Interview | Manouj Gupta" about?

The discussion highlights the significant issue of high employee turnover, with nearly half of new hires leaving within two years, attributed to outdated hiring practices that rely on resumes and gut instincts rather than data-driven approaches. Manouj Gupta introduces "I Jupiter," an AI-driven interview agent designed to provide a unified and objective assessment of candidates, emphasizing a…

What is mentioned in this Founder's Story episode?

14 people, works and ideas are mentioned, including AI, Hiring, Manoj, I Jupiter, ACNET, Elvis Dan. Each one on this page links to its own page with every episode that mentions it.

How long is ""Humans Are The Problem" - Why AI Is Taking Over The Job Interview | Manouj Gupta"?

The episode runs 27 min; the transcript is about 4,112 words in 32 timestamped sections.

More from Founder's Story

About this transcript: the episode's spoken words as captioned on YouTube, split into timestamped sections. Reclip.Me locates every person, work and idea in the text, keeps the time it is first named, and quotes the words around it verbatim. Last updated January 24, 2026.