Beyond The Code

Maulik Sailor (00:10)
Hello and welcome to Livestream of Beyond the Code podcast by Notchup.com. I'm Malik Selar, founder and CEO of Notchup.com, which is an AI co-pilot for engineering managers to automate their people ops. Now, one of the key frustrations that I keep hearing from plenty of engineering leaders

is the gap between them and their HR team. Generally, they find ⁓ their frustrations in the way the HR team operates or generally the organizational processes that they have. And I usually speak to many of the engineering managers to know about this frustration well. But today, I'm joined with an incredible guest with many years of HR and talent experience. However, unlike the usual head of people or HR person,

My guest today has also performed many technical roles, like software developer, product management, being a technology consultant and more. I believe it's going to be a great next hour discussing this very topic with none other than, and none, Gio So, if I got that name right. And I may not be able to do all the justice, and hence I would be, it would be great if you can summarize your experience for our audience. And I'm really pleased to be welcoming you and hosting you today.

here that did not post a podcast.

Hernan Chiosso (01:28)
Good, thank you so much, Malik. ⁓ It's my pleasure to be here. ⁓ So I have a kind of an unusual career path for somebody in HR because I started my career as a developer. And as the team started to grow and the company that I was working for needed more people, they started to ask me, can you find another developer? Can you find another designer, a project manager? And then we had a team and we had

we had to manage a team and we had to create policies and we had to create processes and we had to adopt tools. And so that led me into some HR leadership positions but I never lost the technical side of things. So when I decided to step down to that position, I decided to focus on consulting on things that have to do with technology in the space of HR. Things that have to do with

HR technology, product management in HR, and artificial intelligence in HR. So it's going to be an interesting conversation.

Maulik Sailor (02:34)
Yeah, I believe so. know, normally it's very rare to, you know, ⁓ come across a head of people or a head of HR or, you know, talent acquisition managers who happen to have technical or engineering backgrounds. You certainly have a few, but not many, right? And particularly with you having that range of experience from being a developer to being a product manager to also being a product leader, sorry, people leader.

You know, kind of, you know, cause the breadth of what we are going to talk today. ⁓ and in particular with your current, ⁓ you know, set up, believe you are, ⁓ you know, you're currently running productized HR productizing the HR, right? ⁓ you know, newsletter, can you, can you tell us more about that? What's what, what is the aim of that and what are you trying to cover with that?

Hernan Chiosso (03:25)
Sure, sure. I have

my own consulting practice ⁓ called productize HR, where what I try to do is I try to help organizations and particular HR departments ⁓ to innovate by adding the practices and the tools and the processes that I wish I had when I was in HR. I want to share what I learned from my mistakes.

I want to ⁓ help others ⁓ streamline their HR processes and their HR tools. And another thing that I'm doing these days is I am, ⁓ as a volunteer, am a Director of Technology for the National Human Resources Association. ⁓ In a few other volunteer ⁓ roles that I have, this is what I do. I like to build connections and translate HR into ⁓

into technology, technology into HR, HR into product management, product management into HR.

Maulik Sailor (04:29)
Yeah, that's great. know, I believe that will be very exciting. ⁓ But let's take a step back, right? ⁓ Now, the reason why we started NotchUp, it's also along the same lines as in as a product leader, engineering leader, I was facing some of the problems, especially when it comes to building and scaling engineering teams. And I felt that typical HR processes and tools, they were

they were too generic and they lacked certain things that I was looking for. And to solve for those problems, we started doing Notchup and as part of Notchup's growth journey, our primary ICP are engineering leaders. And as I validate our products, validate our assumptions and so on, I come across ⁓ a few statements that generally

the way you build your engineering organization is very different than the way you would build your sales and marketing functions or, you know, operations function or something else, right? and I don't have a lot of expertise with other departments or other, ⁓ functions within a business, but I'm mainly, you know, by, qualifications, I'm an engineer, ⁓ by experience, I'm mostly engineer and a product manager. and I kind of mostly,

hear from one side of the story, right? ⁓ But today I want to hear the other side, especially from you. You have been on both sides, but more recently on other side of the people at DHR and the org. So I want to hear from you. What do you think are the typical friction points that you see between the engineering department and the HR or the people or the operational department?

that you have seen in your experience.

Hernan Chiosso (06:26)
I think the particular when you're talking about connecting the priorities of engineering and HR, one of the biggest friction points is we need somebody to start on Monday. ⁓ The engineering team says, I need a developer ⁓ to start on Monday. And there's always a need for process.

⁓ Sometimes it depends on tools. Sometimes it depends on how agile the process is. But also sometimes it depends on ⁓ just ⁓ physical time to find a talent, to contact that talent, interview, and ⁓ do all the stages of evaluation to ensure that that talent is aligned ⁓ with what the organization needs.

So I find that to be one friction point in the times of hiding somebody. The other one has to do with the, and this is in my experience, is a definition of, maybe it has a little bit to do with the space where I was, is that.

there's a sometimes there's not enough clarity on how many people are needed exactly. ⁓ How, what level of expertise on what tools. ⁓ If we know that ⁓ if you say one JavaScript developer, it's not the same as saying one Node.js developer, one Angular developer, one.

whatever other ⁓ JavaScript frameworks exist. ⁓ sometimes reaching that level of definition and alignment between the hiring manager ⁓ on the engineering side and the HR team can also be a point of friction.

Maulik Sailor (08:37)
Yeah, you know, it's quite interesting you say that. ⁓ You know your first point about the time that OK, they want the new talent to join or start immediately or coming Monday. You know, interestingly, that was our initial proposition when we first started ⁓ as Notchup. So previously before calling ourselves as Notchup, we used to be called ourselves as codemunc.ai and the whole problem statement was exactly what you said that

Generally, engineering leaders want to have like a zero downtime. When they want to get more manpower, they want to have that manpower fairly immediately. But generally, as you described, the process and just the availability in the market could take a period of time before you have somebody in place, right? ⁓ And we actually started struggling for that today. How do you solve for that problem?

We started building, you know, one way to solve for that is basically building liquidity in the market. Can you at least have a liquid pool of talent? You know, you can't have a global pool, but at least for a few skillset and a few locations, can you have a big enough talent pool for you to be able to tap into a certain talents as and when you need to. However, as we started exploring that more and as we started scaling that proposition.

⁓ We came across the second problem that you literally just mentioned that, okay, oftentimes they don't know what kind of talents that they are looking for. ⁓ Very precisely, as you said, they will say, I want a JavaScript developer or a full stack developer, but not really defining what does it mean? You ⁓ could say a Node.js developer, but okay, what more? Node.js with certain experience, certain behavior, domain expertise. ⁓

⁓ and so on. And generally you have your job specs basically designed to capture all of that. But again, what we found in our experience is that oftentimes ⁓ the hiring manager will give you a job spec, but during the interview or after the first round of screening with the initial sets of candidate will almost certainly end up going back and revising that expectations or the job spec. Have you come across something like that?

Hernan Chiosso (10:52)
Mm-hmm.

Yeah, yeah, there's some instances where an interesting interview with a candidate that was not exactly what the origin of requested for trigger another conversation of saying, maybe what we need is something else, ⁓ which from a perspective of the recruiter can sometimes be frustrating because if you have spent time building a pipeline of candidates in

with one profile and then the hiring manager says, ⁓ but maybe we need something else. That could be ⁓ a blessing or a curse. It may be a blessing if you happen to stumble in with those candidates, but it could be a curse if that's not the profile that you were searching for. So you need to basically restart your search.

Maulik Sailor (11:48)
Yeah, and that takes more time. So again, like you wanted to fill something in within a week or two. And now after initial screening, you're restarting the whole process again. And then it will extend another two, three weeks. Right. And then the candidate may not be available immediately. You may have a notice for years to be sold. You there may be an onboarding process. Right. So what should have been like a, like a one week turnaround suddenly is like two or four months done around. Right. ⁓ yeah.

Hernan Chiosso (11:50)
Mm-hmm.

Maulik Sailor (12:18)
we have seen, we have seen that we have seen a lot of hiring managers do that. I mean, I, I have an example where a particular hiring manager we've been talking to, ⁓ actually currently we have an hiring manager that has been trying to recruit for a particular role for about a year. And this has just simply not able to find that. And, ⁓ like having to wait, you know, and I can have a view that

you will never get the perfect candidate that you're looking for. You'll always need to compromise something somewhere. So what are you willing to compromise? Are you willing to compromise based on the years of experience or the seniority? Are you willing to compromise on certain technical skillset because those could be learned once on the job? Are you willing to compromise around, you know,

Hernan Chiosso (12:50)
Mm-hmm.

Maulik Sailor (13:12)
aspirations or ambitions of the candidate because that's long term and may not be relevant for your immediate needs. These are all the decisions or the reality check that the hiring managers need to do, but they don't really do that. And at the end, the process kind of drags on and on over and over.

Hernan Chiosso (13:32)
Yeah. And another thing that I've seen happen on occasions is that when the teams are hiding for, ⁓ they need immediate help with talent, they need another developer, three developers to start next week. ⁓ What hiring managers sometimes don't take into account is a process of ⁓ onboarding this new talent into the team where they're going to be working. And what happens is that

⁓ the team that is working on the project, they are too busy with their own deliverables and they don't have time to onboard the new talent that is brought in. So sometimes there's an urgent requirement that, yeah, we need this person to start on Monday, but then that person is ⁓ just waiting for a week or two until somebody from the team really spends the time that they need to really start producing in that team.

Maulik Sailor (14:30)
You

Hernan Chiosso (14:31)
So

that sometimes can be a paradox. ⁓ Yes, you need that person right away, but you don't have the time to onboard them, so you don't get them right away.

Maulik Sailor (14:39)
Yeah, so it could be a problem. You know, again, it reminds me of another one of my experience where a particular organization that I was working with ⁓ that that average turnaround time of onboarding a new permanent employee was 27 days. Right, so when you start for 27 days, you may not even have not even your login or a laptop ready, right? ⁓ So OK, fair enough. I think there's a lot of.

Hernan Chiosso (15:05)
Mm-hmm.

Maulik Sailor (15:09)
friction points that we can talk about. But you know what, I want to take a pause there and want to ask, have you, in your experience, maybe in your personal experience or any other company or organization that you know, why they do this really well? know, ⁓ the engineering and the HR or the people ops really works very well together. The employee experience is very good. The hiring manager experience is very good. You know, have you come across anything like that?

Hernan Chiosso (15:39)
Well, I think that... ⁓

I don't want to brag, but I have to say that at the company that I was at, we had been able to get to a point where we had, with many of the teams, we were able to build a nice rhythm of collaboration. So that sometimes it requires an onboarding to that relationship as well.

Right. So at some point, one of the things that we ⁓ implemented was an intake form and an intake interview where the recruiter is basically asking all the questions at once of the hiring manager to ensure that all the plan for the hiding and for the onboarding is done ⁓ before we even start talking to the candidates. ⁓ We would ⁓ like stockpile ⁓

Maulik Sailor (16:16)
Hmm.

Hmm.

Hernan Chiosso (16:39)
the equipment and have the software installing the equipment and we would always carry ⁓ a stock of ⁓ that equipment so that we could ship it. The minute that we got a confirmation that the person was starting, we would be able to ship it and that way we would get it on time. So I think that ⁓ when you are, my examples of situations where it worked was when, ⁓

It didn't happen by accident. It happened by building that rhythm of collaboration so that you can make it happen right. ⁓ Sometimes the biggest struggles have been with ⁓ teams that were not hiding so often. And so they were not used to the requirements of the hiding process and the expectations. ⁓

you had to work on setting all the expectations with those ⁓ managers. So I think that what has happened, what has worked well was ⁓ when there was this great conversation between the hiring manager on the engineering side and the recruiting team.

Maulik Sailor (17:51)
Okay. So from that experience and that learning, you know, do you any modern AI tools that you may be aware of, tools or processes, right? That can actually play a role here and help improve the overall, you know, people ops or their employee and boarding or recruitment or any aspects of, you know, people management within the, within the organizations.

Hernan Chiosso (18:21)
Yeah, definitely all steps ⁓ of recruitment and of HR input in general can be augmented with the use of artificial intelligence, whether it is as something that helps you staying in touch with all the candidates and keeping a warm relationship with all the candidates by keeping communications ⁓ flowing. could be something that ⁓

summarizes the insights from the interviews and creates that this is something that ⁓ particularly I've seen recruiters struggle a lot with. it's taking the transcriptions, transcribing their notes from the interviews into the applicant tracking system so that they are visible to everybody. And sometimes there's a latency to that process.

And that adds more duration to the process. Then there's things that artificial intelligence that can be used to assess the technical capabilities of candidates. ⁓ there's, can use AI to understand the, ⁓ to predict the needs that you may have of talent. So you can get ahead of that. ⁓ There's, you can use, ⁓

AI for onboarding by having not a full AI driven onboarding because I believe that there's a human component that needs to exist. Same thing with hiding. There's a need for a human component, ⁓ but some of the activities can be ⁓ done through an AI tutor. ⁓ And the other thing is during the onboarding process,

⁓ the new employee will probably have many questions because it's a new job, it's a new company, it's a new team, ⁓ sometimes it's a new role, and they have many questions. And they want somebody to be able to answer to those questions with a quick turnaround, ideally an instant turnaround. with people, that's not always possible.

But with AI, if you have an onboarding. ⁓

new employee body that can provide orientation on some of the basic things that everybody has questions on, that can create a better experience for the new hire.

Maulik Sailor (21:06)
Okay. I think I've got quite a few questions over there, right? ⁓ First, let's talk about typically AI stuff that is happening around us, right? Now AI, you know, there's genuinely good AI, you know, very creative, you know, particularly, and really, really creative, you know, the rag and everything else. But at the same time, you have the traditional bots and the automation system and a lot of them are now, you know, ⁓ repackaging as AI agents, right? ⁓

Hernan Chiosso (21:35)
Mm-hmm.

Maulik Sailor (21:36)
So what, what do you think, how can generally AI genuinely can make humans or the actual people work more effectively, you know, augmenting versus automation, you know, help them augment their work that they are doing to produce more than what they used to be doing or automating, you know, get rid of the repetitive manual workflows that they may be used to doing it over and over. Right.

⁓ What do you think? Where is the appetite right now in the industry?

Hernan Chiosso (22:13)
Well, think there, ⁓ one tool that is used when you're designing the ⁓ candidate or the employee experience ⁓ is ⁓ to understand what are the moments that matter. What are the key moments in the relationship? What is important for the company to be, for the employer to be present ⁓ in some way? And so these are things like in the first day of ⁓

first day of employment, the welcome to the team, somebody gets promoted into a new role, somebody becomes a manager, ⁓ becomes a parent for the first time, somebody takes their first vacation, somebody, ⁓ like anything that there are moments that can ⁓ make or break the relationship, those are moments where you need to have more human presence. But ⁓

for you to be able to have the human presence, those humans need to be free, need to be available. And sometimes they are wrapped up in things that are very bureaucratic in nature, things that are very administrative in nature, and they don't have, and they can be automated. So I think that the main value of automation is freeing up humans to be able to work on the moments that matter. In that, ⁓

creates a better experience for the candidates or for the employees.

Maulik Sailor (23:48)
So out of all of that, what you're saying that ⁓ the human aspect of the people management should be more retained by the humans, but the other things could be better done by AI or some kind of automation tools.

Hernan Chiosso (24:06)
Right,

there's lots of things that happen in the background. ⁓ Like when you're saying, am, I don't know, I'm publishing a job posting for a new position that just opened. It's not just one action, right? There's other actions that lead into that. ⁓ Sometimes it's a matter of, for example, saying, okay, what's...

Maulik Sailor (24:23)
Mm.

Mm.

Hernan Chiosso (24:36)
How much should we pay for that position? Right? And so if you have as a human to go and do that research prior to doing the job posting, it takes time. It means that it's not just the physical action of going into the applicant tracking system and entering one job position. You have to do some research before you post that. And that is one research that

If AI can do it for you, it saves you time and leaves you more time to do the thing that you need to do fast. That in this case is publishing the job posting. And it frees up ⁓ your time. the other thing, the other example that I gave, ⁓ if you need to spend ⁓ time transcribing ⁓ your notes from your phone calls with candidates.

and sharing that with a team so that team can understand how was the experience of talking to this candidate. Well, if you could do that with AI, say you're using a tool ⁓ for meeting ⁓ transcriptions and that pushes into the applicant tracking system, suddenly the recruiter doesn't have to worry about that. Yes, they can check that the transcription is accurate and things like that.

but they don't have to worry about that. And they can spend more time talking to candidates, which is what matters.

Maulik Sailor (26:10)
So what do you think, you know, so right now, like, ⁓ you know, so in a typical engineering team, have, you know, you're fairly well-defined job roles. ⁓ you know, front-end engineer, backend engineer, full-time engineer, know, that works in the QA and all those things. Right. And similarly in the HR or people team, you also have roles. Some of the roles are fairly well-defined, like, know, talent acquisition manager, ⁓ you know, policies manager.

or culture manager and stuff like that, right? ⁓ What do you think? You know, how the HR will evolve with assuming that there's a high level of intelligence and automation available through AI?

Hernan Chiosso (26:56)
Well, I think that just like most white-collar jobs, ⁓ HR is going to evolve to the point of, ⁓ in the direction of reducing the amount of repetitive, predictable tasks that can be automated. So if somebody's job was to, I don't know,

setting, set up employees on the different systems of the organization. Well, that more and more can be done automatically and profile based and through automations and through AI. So if that's what, is that the main reason for that job to exist, that job may not exist in the longterm, right? So there's gonna be a...

What I always say when talking about how AI is transforming jobs in general, it's not necessarily that the jobs will disappear, but they gonna become more efficient and you're gonna need less of that. One clear example that I use for that is if you go to a supermarket in the US today, there's more and more ⁓ self-checkout cashiers, right?

So in the past, you used to have maybe 10 cashiers that ⁓ were human cashiers. And when you had a peak hour at the supermarket, you would have all those ⁓ cash registers with somebody. Now you have a handful of those, and you have maybe one person supervising six self-service ⁓ checkouts.

checkout points. So, because now it's the customer that is doing the scanning of the products. Now it's the sensors that are detecting, have you put everything in the, have you ⁓ checked in all the products? ⁓ There's reminders, you can pay with ⁓ a credit card, so you don't need somebody to give you back change.

So ⁓ you need less humans there. And you can have one human that is looking at six ⁓ checkout ⁓ cash registers. And they are ⁓ helping when somebody gets stopped.

Maulik Sailor (29:35)
Yeah.

Hernan Chiosso (29:36)
So that's how things evolved. maybe what you did, you were used to have six, now you have one.

Maulik Sailor (29:44)
Yeah, but you know what? Actually, you know that's an interesting example you give right now for argument sake. ⁓ You know. I think the work is not produced in that particular scenario you previously that checking out taking a product, scanning the barcode and putting it in the in the packaging was done by the cashier. Now we stand by the customer, right? So the work has been transformed.

from, I mean, the role has changed, but the work is still being done, right? Compared to, you know, the Amazon checkout experience where you could literally just walk out without even having to scan because you would have intelligent sensors, which will detect as you pick up the product from the self, right? Which is basically effectively saving the net amount of work done, right? But that has not been very successful either because

you know, for various other problems, right? So here is an example where a lot of automations and lot of technology may not actually be very good in terms of ⁓ productivity or the output that has been produced, right? And may not be even a better experience from the end user point of view, because now they are doing more work compared to the KC, right? ⁓ So.

Within this, right? with this whole AI and automation world where you have ⁓ the tools and the humans that play together, like previously humans were operating the tools. Now we can debate that the tools can then operate independently. can make their own, they're intelligent enough to make their own decisions ⁓ and take corrective actions, right? Without over very minimal human input.

Hernan Chiosso (31:28)
Mm-hmm.

Maulik Sailor (31:39)
So with that, what do you think, what decisions, now again, I want to go back to the generally the people side of the things, what kind of decisions do you think should never be given to AI, at least in the current state, should not be given to the AI and are better done by humans in the loop, right? And in a situation where some of the tasks are done by the AI or AI is evaluating, for example,

Hernan Chiosso (31:47)
Mm-hmm.

Maulik Sailor (32:08)
⁓ Telephone screening, right? So now we can easily do telephone screening, right? Do you think in those situations, AI should be more transparent to the end user or the end user should know that they are actually dealing with ⁓ an automation system or not a human, a real person that they are talking to? What are your views around that?

Hernan Chiosso (32:30)
my, this is my personal perspective, and I think that ⁓ users should always be aware if they are talking to AI. I think that ⁓ not doing it that way is, a, not only has a potential risk of, there's, that it's AI giving, being given too much decision power.

and too much autonomy to make decisions that affect the life of an employee or of a candidate. The other reason why I think it's important that the ⁓ employee or candidate knows is because it's a modicum of respect, of consideration. ⁓ I think that ⁓ if you are...

If you are trying to somebody into thinking that they are talking to a human, you're not building, you're not starting the relationship on a solid foundation. I think ⁓ that the right path would be to say, you're going to be talking to an AI. By default, you're going to be talking to an AI.

Then you can make a decision as a candidate or as an employee, do I want to talk to an AI or do I want to talk to a person? But to assign somebody to be talking to AI without telling them and kind of like trying to hide the fact.

To me, that doesn't build trust. And I think that's essential. That's essential for people to be able to collaborate with technology, to be able to trust it.

Maulik Sailor (34:25)
So how would you build a trust?

Hernan Chiosso (34:28)
Well, ⁓ first of all is by telling the truth, right? By delivering on your promises. If you promise that you're going to have a human talking to the person, you need to have a human talking to the person. It's part of what you promise. if I, as a candidate, I cannot trust you in that basic promise, how can I trust you in everything else? Right? So I think that would be ⁓ the first step to do what you said you would do.

Maulik Sailor (34:32)
Mm.

Hernan Chiosso (34:58)
Another one has to do with transparency and explaining the reason why you're doing it. For example, in some situation, you may be able to say by having you talk to AI, you are able to get more faster resolution to your question. I'm going to give you one example.

⁓ Let's say that you have ⁓ an HR bot that helps employees with onboarding or with basic... ⁓

employee support questions, right? So it can be at first, it may feel like, you're not considering me important enough to talk to a human, right? You're not giving me a human. I'm worthless to you. You're giving me ⁓ an AI. Now,

Let's change the situation. Let's say that that employee has a question on a Sunday evening and they have a question because they are not feeling well and they need to know something about their health insurance.

they're going to be thankful to have an AI that can respond to them on Sunday evening because no HR are going to be working on that Sunday evening. So suddenly ⁓ that ability ⁓ to respond fast becomes a convenience that you appreciate and you are more willing to trust because of that. ⁓

⁓ building trust based on the convenience.

Maulik Sailor (36:57)
Cool. So, you know, there are a lot of things we talked about, right? So starting with like the friction between the engineering and the HR, like, you know, how the different expect, like, you know, the expectations are completely different or the process are very different than what the expectations are. We talked about some AI tools or where the AI can play a bigger role. You know, we talked about, you know, the change definition of HR.

⁓ when this new age of AI and as well as the importance of building trust within this environment, right? If you were to take it all back together, right? What do you think would be an ideal process look for look like for you, you know, from, you know, ⁓ if you can flip it around both sides, like, you know, from

the hiding manager's point of view, and let's stick within the engineering org, and also from the other side of the HR manager or people manager point of view, and then have the third view of the candidate, right? And so if you were to marry all three together, what does an ideal AI-led experience look like to you? Maybe it's possible today, maybe it's possible in the near future.

What is it?

Hernan Chiosso (38:29)
⁓ If we are talking, are we talking about hiding in particular or any other processes of

Maulik Sailor (38:38)
Anything else, right? other? Maybe it's just planning, just resource planning. Maybe it's upscaling. Maybe it's hiding and fighting. Fighting is an important part of people management, right? ⁓ Let's pick any one and see what does a great experience look like.

Hernan Chiosso (38:59)
Yeah, think that ⁓ kind of like what I ⁓ hinted at ⁓ before, you need to understand what are the moments that matter, where you need to have a human, and what are the moments that you can outsource to AI to free up time so that you can deliver a human, you can put a human in charge of the moments that matter. ⁓ The other one, ⁓

particularly with the case of technology, is that HR, I always ⁓ argue that HR is one of the departments in the organization that creates more data points. Because ⁓ you have ⁓ all the data points from the interview process every time that an employee asks for a request.

Every time that you pay a payroll, that you have run a payroll, every time that an employee uses ⁓ the benefits, every time that the performance ⁓ is evaluated, every time that a compensation is reviewed or adjusted, every time that somebody is promoted, all those are data points that are being created ⁓ that today

In many cases, ⁓ HR doesn't have time to assess all those data points because the information is spread across many different systems, maybe because ⁓ you just don't have physical time to be able to assess that. For example, let's say that you do a ⁓

⁓ an employee survey to understand something about the culture of the organization or the engagement within the organization. You need to design that survey. You need to deliver that survey. You need to, ⁓ in some cases, chase people down so that they complete the survey. And then once you have the results, you need to analyze those results and generate conclusions ⁓ out of that. ⁓

technology can help you do those kinds of things in a more efficient way. Like it can send you, it can ⁓ help you create, instead of doing ⁓ one large survey that takes an hour to complete that you'd run once a year, you can do poll surveys that you run ⁓ every week and you rotate the people ⁓ that are receiving that survey. ⁓

Maulik Sailor (41:48)
Thank

Hernan Chiosso (41:55)
Having humans coordinate that takes a lot of human power. But AI can do that with literally no effort. So if you need to do sentiment analysis on those responses, you can get a lot of information, or sometimes you can actually get information from ⁓ not a survey, but...

actually from interactions. I have, ⁓ I know somebody who is a startup founder who recently got her product got acquired by a larger company. And what that product does is ⁓ you basically invite that into a ⁓ one-on-one between the manager and the employee. And it can extract insights

based on the conversation. And it can ⁓ coach the manager on how they are delivering the message.

So those are all things that ⁓ are helping the process become more efficient and become not only more efficient, but also more effective because sometimes there's many things that you just don't do because you don't have the time. And I think that the value of technology in this case is enabling you to do a more complete process each time and not just scratching the surface.

Maulik Sailor (43:32)
That's pretty good insight, right, Anand? And, you know, I also believe that a lot of job roles in the typical organizations, right, they are defined to create impact, but in reality, a lot of their time is spent in admin, in paperwork, in, you know,

Hernan Chiosso (43:56)
Mm-hmm.

Maulik Sailor (43:58)
carry picking or ticking the boxes, right? You box ticking exercise as we call. ⁓ And basically reducing down the productivity, overall productivity of the organization and the individual, right? But some of these activities are essential. You you can't not do it. You you have to do certain things, right? ⁓ So although you may feel it's time-wasting, but you got to do it. Like, you know, the pulse survey that you mentioned. ⁓

And I kind of totally agree with you that with all the level of AI and intelligence available around us. In my opinion, every single aspect ⁓ of running a business or even running your personal life, right? Needs to be re-think in how you would do that with AI. Right? So before internet, communication was pretty much

offline, know, letters and sending a post and fax machines or stuff like that. But with the advent of internet, especially with ⁓ 3G and 4G, you know, that's completely changed the paradigm. You know, now we can't really think of waiting for a message for months. In the past, that used to be the case, right? And once you remove that barrier and the reality that, okay, I need two people in

Hernan Chiosso (45:19)
Mm-hmm.

Maulik Sailor (45:26)
in the other end or extreme end of the world can actually communicate in real time, not only text, but also audio and video changes that paradigm. And now we take it for given that, that's given, you know? So you have to build on top of that. And I think with this whole new age of AI revolution that we are currently living in with AI and intelligence, you know, reasoning capabilities.

research capabilities, analytical capabilities are so much baked in into every single tool that we use that now we have to take that intelligence or capabilities as given and we have to build on top of that. So now we no longer restrained by human having to do the thinking. The machines can do the thinking, which in some ways could be scary, but could also be quite beneficial. ⁓

Hernan Chiosso (46:05)
Mm-hmm.

Maulik Sailor (46:22)
to the times that we live in. ⁓ Cool, just mindful of the time. I'm sure we can carry on for many hours. And I think instead of doing this remotely, if we were in person, I'm pretty sure we would have spent the entire day talking about a lot of different things. ⁓ So given the time, we are almost coming to an hour. I would like to just... ⁓

Hernan Chiosso (46:32)
Mm-hmm.

Maulik Sailor (46:51)
say thank you to you to having make this time, setting a wonderful experience and thoughts with us and with our audience. ⁓ And I'm really pleased that we got to speak about all these topics today because this is literally what we are also thinking on a continuous basis, day in, day out at NotchUp and the audience that we work with. But I'm really pleased that you could make it today.

Hernan Chiosso (47:19)
thank you so much for inviting me. was a great conversation.

Maulik Sailor (47:22)
Yeah, no problem at all. It's our pleasure. ⁓ So all right, folks, everybody who has been listening in, thanks a lot ⁓ for joining in today. We're going to wrap it up, but this recording will be available online on YouTube or Spotify. We'll also be uploading an edited version shortly after so that you get all the notes and the transcript as well. And you can listen on a podcast setting as well.

Uh, so thank you all for joining in today. Correct. know, you know what I mean? I, I, I've been looking to leverage some AI podcasting too. Uh, you know, there plenty of them out there now, but did I was like, okay, do I want to maintain like a, like a human touch in this one? Uh, and at this moment I'm like, okay, this is not really a big, uh, tool for us to do. You know, I really enjoy doing this. think my team really enjoys.

Hernan Chiosso (47:56)
See another way that AI can help you.

Maulik Sailor (48:21)
hosting this podcast. So I think we enjoy doing it and hence we want to continue doing it manually for the time being. Let's see how we change, but at least for the time being, you we want to keep it more human, as you say. So anyway, folks, if you want to listen to more such roundtables and podcasts, then please subscribe to our YouTube and Spotify channels or alternatively subscribe to our newsletter. And if you're a tech talent.

looking to accelerate, achieve your career goals, then do sign up as a talent on notshab.com slash talent. And if you are an employer looking to deploy an AI co-pilot to design your engineering org, automate some of the manual workflows and free up your engineering capabilities, then do sign up as an employer on notshab.com. Thanks, folks. Thanks a lot for today.

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