Episode Transcript
[00:00:00] Speaker A: And I think that the novelty that we bring, we are actually looking into cost attribution and better understanding how every dollar you spend within the cloud contributing to your business, better understand what is your customer cost, the future cost, what's the cost of a team, let's say if you have internal childbacks within organization and I think that this is a very important segment that is fairly new.
Organizations transition into the cloud initially it's really very easy and you think hey, I'm in the cloud, it's easy. But then you start getting the bills and it's easy, but it also can be very painful.
[00:00:39] Speaker B: Welcome to AI Advantage where modern leaders decode the future of tech. I'm Solomon Williams, founder of Solonox. So here it's no noise, no hype every week. Sometimes it's just me and sometimes it's the brightest minds in tech breaking down what it really takes to grow smarter with AI and automation. Let's dive in.
Hello, welcome to the show today. So I'm very excited to bring on for a guest that we have is Orit Yaron, she's the VP of engineering for Attribute. Orit, tell us a little bit about yourself and just introduce yourself to the audience.
[00:01:15] Speaker A: Hi someone, thank you for having me. It's a pleasure. I've been working in the tech industry for over 20 years now and leading and building engineering group, usually starting with small and then growing with them. Been working with Toyota which was acquired by RSA and then worked by AMC and been a technology leader for outgrain since startup to IPO in the NASDAQ and as you mentioned these days I'm leading the engineering at Attribute. We are a fairly young startup, we are in the market of finops bringing new technology for understanding cloud cost in related to business metrics without any tagging. Everything is automated based on EBPF technologies. So that's me like in a few seconds.
[00:02:05] Speaker B: So as it's so you know we talked beforehand and it's so interesting on having it, especially utilizing the automation to help with cost perspective in terms of the cloud because it rallies so much with the storage and with all the infrastructures that's having it. How are we able to scale, how are we able to keep it with the cost management side at a good point or roi? So tell me a little bit about like as a BP on that leadership level, what does that day to day look like? Are you always looking on trends that have it? Are you working with the team and having it to like we can find ways to fine tune your automation your workflow and let. I'm so curious on that.
[00:02:41] Speaker A: So as you know in the leadership role of a startup and I think that it's true also in larger organizations, the fact that you are leading the engineering, does it mean that you, you are allowed to be disconnected from the business? At the end of the day the role of engineers within the organization is to bring value to customers and it's not that we can develop whatever we feel like it needs to bring value. So with that in mind, we need to make sure that we have very good understanding of what our customers are looking for. And in some cases we also find a way to bring innovation and educate customers. I think that when you look at the, the finops world and you would see that there are different segments within it, there are finops tools a bit, let's say, I would say legacy, but the ones that are well established already mainly around cost reduction, put it like that.
And I think that the novelty that we bring, we are actually looking into cost attribution and better understanding how every dollar you spend within the cloud contributing to your business, better understand what is your customer cost, the future cost, what's the cost of a team like let's say if you have internal chargebacks within the organization. And I think that this is a very important segment that is fairly new. It's organizations transition into the cloud. So initially it's really very easy and you think hey, I'm in the cloud, it's easy. But then you start getting the bills and you. It's easy, but it also can be very painful.
[00:04:12] Speaker B: Yes.
[00:04:12] Speaker A: Or do you want to make sure that you are accountable for every dollar that you spend and you know how it contributes to your business and who you put accountable for every, every dollar that you spent? Right. And I think that the main thing is to this is one of the core differentiators for us is that we leverage technology in order to do that without any tagging and manual work. And that is a key because I believe that everything that you do manual you can invest a lot of time in doing it and, and then the minute you finish with it, it's starting to be obsolete. So automation is key and to be able to do things automatically is key. And we do it by introducing technology that is based on deep packet inspection that allows us to do everything, all the discovery and everything automatically.
[00:04:57] Speaker B: So I, and I think but what we've touched on is just on exactly with migration work because I've done migration work in the past and when you come up lift and shift all the way over try to look at like okay, what's my month to month? And as you said, one of the most important part which is any with even from all the CSPs is governance is how do we kind of do on the governance side adding in with the tagging, how are we doing it to make sure not on a policy standpoint on security, but also on the cost side. So with how did you. With the emergence of how everything's becoming more automated, it's becoming, you know, templatized to help with it. How does do you feel like, you know, in this age, especially in 2025, with all the AI and automation, has that helped? Is that have your customers really wanted to focus more on it? How has that helped with attributes, you know, vision in providing value for your clients?
[00:05:47] Speaker A: So the era of AI, which we are now in the beginning of, I guess is really amazing on one hand that you can do things that you never dreamed of. But on the other hand you see that there is huge amount of spend and it's very difficult to understand who spent it, how and why, especially on AI tool. So I think that it's important to make sure that we have accountability on that as well and not just look at it as one big bucket of AI. That's one thing. I think that when you look at AI and automation, it also is in my role as VP of engineering, it also represents challenges in engineering world. So I think that most people say okay with AI, they expect R and D to perform faster, to increase velocity. And that is true to some extent. But it also brings a lot of challenge. For example, when you look at code ownership for, for us, for example, we're working continuous delivery methodology. So our engineers are responsible for the code from the first line they write until. Not until it's in production, but until it's retired from product. And now when you introduce AI within the development process, the AI develops a lot of code lines. Who is the owner of this code? Who will be responsible when something happens in production to really know what happened? The AI tools also tend to generate a lot of codlines. They mean better. So I don't think that you can look at it as simply fire away, okay, I'll have an AI agent here, I have an AI engine there and I can forget about it for sure. It's. We need to look into and make sure that the engineering force leverage the AI capabilities to do better.
[00:07:26] Speaker B: And I think, and I from that standpoint of having it with AI, because of you said it's become Very abuzz. You know, how do we just implement it? And I think, you know, just from other conversations, like it's how do we add this into the workflow? Also with creating the logic that's going to be coming from the AI agents, but also on what exactly are we, how are we going to be implementing into our workflow? Is there going to be additional technical debt? And I think that's the part of where we have it that we need to kind of facilitate on that. So to that point, I'm curious on having to handle that and with your team and how attribute as a whole, what keeps you working, what stands, what has, how does attributes stand out from the other competitors and so forth else. And like what do you have for your when you're utilizing this AI to help with the cost and that you feel that you bring value to the clients.
[00:08:16] Speaker A: So first of all, we know again automatically without any manual tagging to show exactly which services spend how much money in HAI tool. So for example, if you have service that communicates with OpenAI, we know exactly how much this specific microservice costed with the OpenAI and to have such a granular breakdown of the specific workload that spend money with the different AI tools and on what exactly like what kind of model and so forth. It's really important for companies to be able to improve and make sure that they are working with AI tools in a proficient way and that they allocate the right budget in the right direction.
[00:09:04] Speaker B: Okay, yeah. And, and with that, you know, with what do you see really in the, in the trains of IT with AI as it as we're continuously evolving through with it, what do you think that, you know, industry professionals and other leaders should be aware of that you think that you see insights from on the side with finops and with cost and so forth.
[00:09:24] Speaker A: So I think that like any other amazing tool, not that I think that there is a good enough reference because I don't think there was such an amazing tool in the recent times that came out like the tools that are based on AI. It's important first of all to keep a check on the balance on the cost, okay. It can dramatically grow and then you find out and you're surprised and never nice to be surprised from. Second, I think that especially for engineering people, it's very easy to be distracted by new shiny desktop and you need to make sure that you keep the focus and that you keep your eyes on the ball and make sure that you understand what you are doing. And more than that, you Understand why you are doing that. There is a great book also with that name. Start with why. And I think that that's something that I've been employing with all my engineering teams throughout the years. You always need to understand why you are doing that, why you have a cast, why we are doing what we are doing. And the fact that I'm telling that we need to do that's not a good enough why. If that's the why, don't do it. You need to. And with introduction of new technologies, especially when they are so fascinating on one hand, super easy to use on the other hand can introduce a lot of security issues, a lot of tech debt. As you mentioned, you need to make sure that you're still focused on the value that you bring, not to lose yourself in it.
[00:10:46] Speaker B: Yeah, I think this, what you point out is really just really understanding the. The why aspect of really diving deep and discovering what will this solution bring and what you know, thinking forward terms of like how can we prepare and so forth. So I think as an engineer that that's key. Instead of kind of doing into the. You get so tunnel vision sometimes as an engineer you want to get everything done. So with that. Because of how you've mentioned with all of these new components is very shiny. You know, you look at outcomes, this is. You hear on the. The marketing side, this is what it can do and you're like, wow. And you do a testing and it looks good and then later on there's security or how do we implement this in. So do you feel that's a challenge as coming forward with it in terms of the market? Do you feel like that is something that.
That you kind of look towards each time whenever new tools come out? Or do you like to stay focused on the. How do you stay focused on the foundational steps with this AI trend? Does that make sense on the question?
[00:11:41] Speaker A: So I think yeah, I think that at the end of the day you need to make sure the value is what is grounding you to basically crown. And you need to make sure that you understand this right. I need it good. I think that it's super good for testing stuff like that. Like there are a lot of mundane tasks that you can get rid of which are is great. Like you can spend your time where you bring more value. And I think that's the key and that's very gentle about to find where is your value and where you spend your time versus where you offload stuff that you're doing. Another challenge that didn't mention and I think that it's worth mentioning is also around the recruiting process. What kind of talent do you recruit in the area, in this area now. And I think there are a lot of questions like would you recruit now someone in the job interview says I'm not using AI because I think the AI are stupid. And I better. Would you recruit someone that is saying I'm developing only with AI and when you look at the code you. You realize that there are really only AI generated code and there was no real value of the human. So again, I took two very extreme examples. But I think that the whole recruiting process is now becoming different and is impacted by type of talent that you recruit, the level of expertise they. You know. My daughter, she's now starting to think about what she should learn in university.
She has background in computer science. Naturally he told her, hey, I think that go and study now software engineering. Not sure it's the best thing to do because at the end of the day, unless you are super interested in the internals of things like in five years time being just a software developer, I guess it's not the main thing. Like it's not. It's not going to be the main value that you bring to the table.
[00:13:28] Speaker B: It's amazing on just how much it has changed and so forth else in the next years of now. Exactly. As you've mentioned before. And I'll get to that point of how you recruit and so forth else in terms of, you know, do I. Because sometimes you kind of hear especially oh I don't want to use AI because that makes me think that I don't know what I'm talking about or. But also thinking of it as a tool to help you assist with your, your processes. So it's just with that thought on the recruiting stage, what is it that you really look for? I know you get in two different extreme examples. But you know, for people coming in and you know, people wanting to learn, wants to get further into the space of tech because very much especially after Covid the pandemic, you know, everything has shifted over to the cloud. That's, that's expedited it. Right. And so on this thought path from if you were to give, you know, some other people that are maybe entry level looking forward, some like you're like your daughter's kind of working in. Should we go into the software side or should look over what are some. Do you think they should focus more on the outcomes, the thoughts of what you mentioned, the whys or do you think they should focus more on the foundational steps of it.
[00:14:37] Speaker A: So I think that me personally, I probably wouldn't recruit someone that is has a statement of I'm not using AI. I think when you have such powerful tools available to you to decide not to use it because I don't know why, I think that it's not a positive way of looking at things. Right. So I do think that it's important for people to not necessarily just in engineering, but in every walk know how to leverage the AI capabilities in your advance. People say it a lot and I strongly believe it. I don't think that AI will replace software engineers. I think that AI will replace software engineers that are not using AI at all. Because at the end of the day the combination of the AI and the human mind will be the, the winning factor. So I would say to my daughter and to everyone else that is out there, first of all, master the abilities and the techniques on how to use AI and how to leverage AI in your advantage in every field that you work in. On the other hand, don't state the AI or the feedback that you get from the AI the output as granted. You need to be very cautious and make sure that you do your own research and ask for the sources in order to understand what you are doing. And even if you're using for example code writing, go over the stand what's happening in the code, understand maybe it gave you a very good direction but maybe you can now take that and do the increment of making it better and that's where your leverage is as a human.
[00:16:09] Speaker B: I think so and I fully agree that there needs to be because you get so caught up on oh automation this is automated, it's going to save on cost. But then I full firmly believe there is, there needs to be a symbiosis of marriage between the human and on the automation working together. Not so much of just AI in terms of just saving on cost but how does it blend and you need to have both to make it whole. So with that with everything that you met is great on having it on, on the wise looking, doing your due diligence with the AI. I want to you know, ask about a little bit on attributes, on the culture and what you strive to have with your team and so forth. So can you tell me a little bit about just as we've gone on, you know, after Covid, you know people are more focused on more of a work life balance on the code of attribute with you being a startup and you have this big vision. So like how do you nurture that team. Tell me a little bit about, tell us about really the, the culture of attribute. How does that work?
[00:17:05] Speaker A: So I think culture is key. Okay. And culture will beat technology every day. At the end of the day, startup and work life balance. It sounds like it's two contradicting things, but not necessarily. When you work in a startup, yeah, you need to be able to run fast, you need to be fit. If we take this.
But it doesn't mean that you need to run a sprint all the time. At the end of the day, you'll burn out. So even within the startup, we are making a lot of effort make sure that we balance our sprints. And there are times where we need to give 200 run fast. Not necessarily. It's important for everyone to see how money are sweating while we're running, but run fast achievable. But we, we understand that we cannot give 200% all the time because it's important to have that balance. We are giving a lot of focus on trusting our team members. It will sit on pure engineering stuff. We don't have qa. Our engineers are responsible to QA their own stuff possible to decide if they are good enough to go into production. They're responsible to push it into production and they're responsible to fix it if it breaks. Okay. In order to do that, we have a very good immune system, which is actually our monitoring alerting system that allows us to alert on every issue before it becomes a significant issue. And this is the balance between giving a lot of control to our engineers and allowing them to run very fast because it's all in their domain. Like they are responsible. You don't need to wait for someone else. But on the other hand, protect our production and make sure that we meet our SLAs and make sure that we have the right stability and not cause any production issue. That's one thing. But you will also see it in the fact that we have, for example, flexible vacation policy. We trust our employees to take as much vacation as they need, but also to make sure that they balance it with the needs of the company. And we believe that when you trust your people to work, it will produce result much higher than management any other form of managing the tiny gory details of things.
[00:19:18] Speaker B: And I think, and I love that because it makes them feel, not only does it have them be responsible, but when you, when the team members feel that they're trusted, they, they pour more into it. They, they, they trust their leader as a bet because they're, you're trusting them with it and with you having to say it's interesting how you, you take out the qa, you just focus on the dev and then the, the the production environment, it also brings a level of ownership for them to be able to like this is what I built out from start finished and if there's any changes they feel more responsible on that. So I think with.
[00:19:51] Speaker A: Sorry, it's also related to the, to what we started our conversation with the connection to the business because we make sure that we are very transparent and they know customers start coming in what we need to make sure in order to seal the deal. And if we need extra effort they have very why we act for this exit poll. And I think that the fact that we trust them also allows us to.
[00:20:14] Speaker B: Be very transparent and I think that's transparency always goes so much better and that provides on that. So with that with your team that you've established the culture you've established, you know them having ownership of any you've established on what to look what do you what would you like to see actually the next year? What is the goal that you have in mind for the next six months to the next year?
[00:20:35] Speaker A: So naturally conquer the world, right? And it's not happening. We have very few business metrics that we want to make in regards for hitting the numbers at the end of the day numbers, they don't lie. We don't measure ourselves if we are successful or not by the number of employees. I think that those days pass. We measure ourselves by the business success. Those are the KPIs and the metrics that we make sure that we track. We make sure that we are able to hit the goals that we've set. And from there it's like a waterfall. Like this is what defines the, the pace that we are doing and to.
[00:21:08] Speaker B: That on that side with the view that you have, do you see like any challenges with that that you're thinking that you, you as a team have to brainstorm on to overcome those with the, the goals that you have in mind for the company as a whole? I know on the BP side of engineering it might be on the technical but of course it's growth and so forth. So I'm curious to hear your thoughts.
[00:21:27] Speaker A: So there is always the thought of how you can do more with less. I think that it's even more important when you are a startup to begin with, you have less resources or you're trying to be more efficient with your resources. Very much related to the AI conversation that we just had to see what, how we can do more with less. And by doing more with less, necessarily looking into cutting cost, I am looking into maybe bringing new technology in order to allow us to do more without cutting the cost. And I think that at the end of the day culture that we discussed and the technology, they must go hand in hand. Because if you don't have the right tools in place, you cannot expect your engineers to have the accountability. If you not necessarily engineers, but also your sales team, they also have accountability. But if you don't have the right tools to make the KPI and the metrics visible, how can they be accountable? You need the mixture of the culture and the right tooling in play. And the nice thing about technology is that it always moves forward. So I always say that when I'm looking to bring bring people on board, first I look for people that know more than I do because if they know less, then we don't need them. Right, we know it. But we also look for people that have the motivation and have the CPU to learn new stuff because the fact that they know something very well today, but they have no motivation in learning new things. And not just learning, but also sharing their knowledge with their teammates, they may be useless in a couple of months time. And in the pace that technology moves now, it's really a couple of months time. So the most important thing is to make sure that we understand how we challenge ourselves all the time to achieve more by leveraging the technology better, leveraging new technology and keep learning and develop and evolving ourselves.
[00:23:14] Speaker B: And I think that's excellent point because I think on, because we have to really look at it from here at Solanac, sometimes even with the past clients we've worked with is like we focus on the growth partnership of it, of utilizing the AI to help them grow. But on that side it's continuously thinking of how can we look to on outcomes, how are continuously evolving and learning since we're partnering with them. Especially on, like you said, from startups to small to medium enterprises, you know, as myself, like how do I look to on the outcome, where do they want to get to in those next steps? So if it's, you know, 30% increase in verified leads on their generation, I'm getting new leads for the business. You know how we have to look at that on cost savings, like okay, we need to how do we shift on the costs or analyzing the calls to be able sales calls or anything else or for B2B. So I think to your point, even in technology, all the way over across business as a Whole it's continuously moving forward and having to, you know, what, what are the steps to keep on moving and thinking forward. But also to your point on how do we provide value, what is the outcome is what are we doing as a whole to help ship forward? Whether that's with enabling our team and helping with taking away of the debt, as you've mentioned, and helping provide a better ecosystem to get more quicker and more efficient work or if it's from. From on the business like getting those leads and the marketing and anything else. So I love that you know that you really put on a point to that. So with that I would say if you had a magic wand, if, if you could, you know, make a change, what would you automate or what would you use AI if you, if you could make it better in attribute as a whole on the side, I think.
[00:24:53] Speaker A: Think that I would really love to automate or to. It's not really automated but really to have AI that is able to tell us things about feelings. I think that as humans there is a lot of decisions that we make that are based on feeling. Even if we don't think that, even if we think that we are very data oriented, even if we are very analytic, there are a lot of things that are with feelings behind it. And I think that if we were able to understand that better, the whole world will look better. I think there would be peace across the world and a lot of ego would put aside. So that would be really awesome. But I think we were a bit far from that.
I would be happy to have like small AI robots make sure that my house is clean, the groceries in the fridge and maybe even do the laundry and the dryer working completely without any assistance of me.
[00:25:49] Speaker B: I think that's what we all do is like we don't have to. They have to pay for anything happens with it. We can use a robot to take care of the repair fee or the contractor that help with that. But I love that point of what you said because it's such a unique perspective because with the engineering side think always so lot you think, you know, analytical, you think logically, but taking the fact out of it and putting more of a feeling, more of an intuition based into it to utilize that. I think that's a great, you know, blend of that forcing and having it where the human element because that's where the emotional capacity of it, the you know, whatever you want to call it on just the intuition, the spiritual, whichever you want to kind of have it. I think that's an interesting perspective and that will help with so many other issues that are going on with the world and help better hold. So I love that. So you know, where can you know our audience learn more about your journey or as the the company as a whole on the company's journey as they as they rise above and get to as they scale as you continue to scale.
[00:26:46] Speaker A: So the easiest way to find me is over LinkedIn and you found me there. I usually make sure to answer everyone that dms me so feel free.
[00:26:56] Speaker B: I love it. Well, thank you so much for having on the show. You know, you've been, you've been a pleasure and I really look forward. I think our audience is really going to take in and want to follow your journey of actually and yourself as well. So tune in next time and we'll if we'll catch you next time on the next episode. Thanks everyone.
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