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Founder's Story
The Hiring Disaster: Why 50% of Your Employees Will Quit (And How to Fix It) | Ep. 298 with Manouj Gupta Founder of ACHNET
00:27:24
In this episode of Founder’s Story, Daniel Robbins sits down with Manoj Gupta, Founder and CEO of ACHNET, to explore why modern hiring is fundamentally broken and how AI agents are changing the way companies select talent. Manoj reveals why nearly half of new hires leave within two years, how resumes, interviews, and gut instinct create costly mis-hires, and how ACHNET’s AI agent iJupiter unifies evaluation into a single, objective workflow. The conversation dives into the future of AI-led hiring, the role humans still play in final decisions, and why clarity—not speed—is the key to building stronger teams in 2026 and beyond.
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- [00:02]
A
Member week is here for Pros at Lowe's get up to 40% off hundreds of items from tools and paint to kitchen and bath and more, just in time to stock up for this year's jobs. Plus earn five times the points on an eligible purchase shop. Member deals in store and online from January 8th through the 14th. Still not a member? Join for free today. Lowe's we help you save Point Boosters subject to exclusions and more Terms apply. Loyalty programs subject to terms and conditions. Visit lowe's.com terms for details subject to.
- [00:29]
B
Change if you're the purchasing manager at a manufacturing plant, you know having a trusted partner makes all the difference. That's why, hands down, you count on Grainger for auto reordering. With on time restocks, your team will have the cut resistant gloves they need at the start of their shift and you can end your day knowing they've got safety well in hand. Call 1-800-GRAINGER, click grainger.com or just stop by Granger for the ones who get it done. So Manoj, 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 and I know that's what you're doing with ActNet. 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.
- [01:44]
C
Yeah, okay, great question Dan, and thank you for asking me and appreciate you speaking to me today. So Dan, here is the thing. For years 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, driven on resumes, fragmented interviews, gut instinct, and so forth. What stood out to me was this contradiction. Businesses were becoming more data driven everywhere except at the moment when it comes to hiring people or selecting the right people. Resume said one story, and interviews said another story and assessments were done from a different systems. And altogether the leadership was expected to stitch all these things together under 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 how the talent should be evaluated and what we can do so that the hiring managers can take a decision with clarity. That's what made me think about creating this platform.
- [03:58]
B
So in my experience, I found a lot of managers 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 I, 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?
- [04:48]
C
Okay, so we have got, we have created an AI agent underlying AI agent called I Jupiter, which is our main engine, software engine, which is AI agent, if you may. And the way 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 agent state, that definition of that role goes through all the resumes. And look from the context perspective what the manager is looking for. Hiring manager is looking for searches through the resumes, finds out, ranks them, what is the best resumes they have. It finds out based on the role, then it sends out, it takes the interview or conducts the interviews on on behalf of the manager. Hiring manager like me and you are talking the agent also come online in terms of avatar and it interviews the candidate and then it assesses the person, whether that person is fitting into the role. So this is all AI being assessed, 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 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 the technical assessments and then ranks those candidates. So and it gives the hiring manager a good report which tells them what are the positives of the candidates and what are the. If there are any negatives, then it mentions a few things there so that manager can now can take the decisions clearly on the candidate. So that's how it works.
- [07:19]
B
I needed this. When I used to hire in corporate, I would do so many interviews that I'm not even kidding. I fallen asleep in interviews before and I felt like 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. And 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 in the hiring process and what you're doing?
- [08:08]
C
Again, one important thing which we have to understand is AI is not or the engine which we have got is we have made sure that it is not biased. 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, 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 has been taking 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 to select the candidates rather than 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 take the decision. So human is not out of the picture. Final interview we still expect. Just let's say I get 500 resumes 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.
- [09:57]
B
As a founder, I'm thinking a lot about my goals for 2026. We want to hit a million subscribers on YouTube. We want to hit revenue milestones that we never have done. In order to do that, I need to build the right team and I need to make sure I surround myself with people who are great at what they do. Because here's the truth. Finding the right people is very hard. It's like when you're hiring. How do you even know who's qualified for the role on your team? That is where ZipRecruiter comes in. ZipRecruiter makes it easy to find top talent fast. Their matching technology works quickly to connect you with people who are a great fit. So you don't waste time or money. You can even see how many qualified candidates are in your area right away. No wonder ZipRecruiter is the number one rated hiring site based on G2. And right now you can try ZipRecruiter for free. Let ZipRecruiter help you find the best people for all your roles. 4 out of 5 employers who post on ZipRecruiter get a qualified candidate within the first day. See for yourself. Go to this exclusive web address to try ZipRecruiter for free. ZipRecruiter.com audio Again, that's ZipRecruiter.com audio ZipRecruiter the smartest way to hire taking the.
- [11:09]
C
Interviews can be done within the single day. Obviously if scheduling can be done with a single day and interviews can be taken in the single day as well, then comes the technical assessment can also be done the 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 those rankings and call those people. Instead of 500 people now call, they can call three or four people or 10 people for their final interview and take the decision. So that's the help hiring manager is getting here. And what used to happen before is If I get 500 resumes, then the recruiters get involved. Recruiters will. Nobody goes through 500 resumes. Who has got time to go through 500 resumes? 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 they might be used into some other places where they can be fit.
- [12:38]
B
Man, I love that I that's a great way to look at it. And 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 remember applying to roles so many years ago and, 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're working with technology.
- [13:36]
A
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- [14:05]
B
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- [15:05]
C
Yeah, I think convincing once they have, once they understand the vision and once they have seen taken the demo I think convincing has not been very difficult for us. They can clearly see the value and once they started seeing the reports which have come out 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, 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 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 the AI will do all the job for you. So once we, and when the report comes out, they themselves say that or the questions when they ask in the interview for the candidates, they themselves are saying, the customer themselves say that. Some of the times we don't even think about the questions, we miss out on the questions which are the very relevant because we are against time or we are, you know, so these are some of the things which AI is able to help them with and the clarity which they get it about the candidate is something which, which they have liked it. So, 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, they are, they are, they are happy that they can get some candidates which, which might have, they might have lost otherwise.
- [17:35]
B
So now that you've done so many, what do you have any data that you can publicly share around, you know, maybe impacts on this or maybe even, you know, the interviews that it's done. Any, any data that would be interesting around either the person, the interviewee or on the corporate side like is, what's the outcomes from this?
- [17:58]
C
Yeah, I mean 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 to show or we are showing them the data which we have trained our agent on and that's how they are able to take the decision on us.
- [18:20]
B
So there was, there was always a phrase that people used to tell me 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 people from human resources C suite to business leaders, how can they leverage this now currently without the compromise?
- [19:07]
C
Yeah. So Dan, the biggest shift leaders need to make is mental, not technology.
- [19:15]
B
Okay?
- [19:16]
C
That is important. For decades we have equated thoroughness 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 resumes, 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 good, good looks like up front. 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'll let the system do the job 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 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. So that's something which is going to take. And finally, speed and quality should no longer be treated as trade offs, right? With AI led structured evaluation, organization can move faster because they can, they are evaluating better. That's what I feel.
- [21:26]
B
I love that you can get more resumes, 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. 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?
- [22:31]
C
So I think few things. One is right now the process is, the evaluation process is all broken. I feel audit is not there. It is there, but it's look very differently. For example, you send a resume. Their 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 is a system which is going to take the various evaluation. I think all this will go away. I feel what will happen if you look at maybe in couple of years or four years or five years, whatever we may say that hiring managers will be self served. What you need, you just input that data. And after that everything will be all, you know, touch free or touchless. The AI agents will work behind the scene. They will get you the candidates, the best candidates available 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 faster, quicker. At the same time it will be more clearer that the person you have hired is the right person for your job. That's how I think. So it will become more touchless. If you may. Right now we have got so many people involved even for one hire, right? So that will shrink or that will cut down.
- [24:26]
B
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 Strength Finders, 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 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 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.
- [25:35]
C
Yeah, I think Dan, great question. 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're 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 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, the 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. 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 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're good at what they do and they are, you know, the data is there. I don't see any reason AI not, you know, selecting them or putting them in front of the hiring manager. I think that is very important.
- [27:42]
B
No, thank you for sharing that. 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, 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, they're a corporation, they need to use the service. How can they do so.
- [28:21]
C
So they can go to www.acnet.com and they can fill in the request that they want to have their demo of the platform. That's how the, that is the right way to get in touch with us as of now.
- [28:37]
B
Well, my nose, Gupta. I mean you gotta come back when you've hit like 10 million or 50 million data points, come back. I would love to hear more and share. What are you seeing? I think the interesting part too will be that so 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. 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.
- [29:17]
C
Thank you. Thank you, Dan.
- [29:18]
B
Thank you.
- [29:19]
C
I appreciate for having me here.
- [29:26]
B
If you like the show, please take a moment to rate, review and subscribe. It really does help the show to grow.
- [29:33]
C
Thank you for listening.