Latest / The Unfiltered Engineer / Ep 1: Can AI Take This? feat. Eduardo Aparicio Cardenes

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Ep 1: Can AI Take This? feat. Eduardo Aparicio Cardenes · The Unfiltered Engineer

• Vishakha Motwani: Hello and welcome to the Unfiltered Engineer. My guest today is Eduardo Aparacio Cardenes. Eduardo is a software engineer with over 18 years in front-end development. He's one of the technical leaders shaping the front-end architecture and technical direction across the transactions tribe, which is responsible for all payment experiences at Super and processes more than 300 million euros in deposits each month. He also founded DreamMaker Factory and co-founded Inner Virtuoso and was recognized as one of ADP list's top 10 frontend mentors among a global community of 30,000 plus mentors. And today we are talking about how software engineers' roles has changed and where it's headed. Thanks, Eduardo, for being here. I'm so excited. And thank you for going first. No pressure at all, but ⁓ I would love to have you talk about the software engineering roles. ⁓ but before we begin, my one question to you is ⁓ when we say that we're talking about software engineering roles, right, ⁓ change since when? When you say that, what ⁓ what moment are you comparing against? Eduardo AC: Mm-hmm. Thank you very much for having me today. I am very excited about these particular questions. As a mentor is always difficult to understand what's the reality. As an engineer as well. I will say it never stopped changing. So from when I started my career, ⁓ I even when I was studying, software engineers have been ⁓ a lot of things, but the only thing it hasn't been is being defined. Vishakha Motwani: Yeah. Yeah. I was saying what I just started. Eduardo AC: So evolve over time and change often. There is no things like specific degrees or license that you can acquire that will actually bet to you for actually accessing the market. So everyone is be able to, with a little bit of effort and knowledge, be able to introduce themselves. So so what I see personally over the past two decades is Before it was about delivering specific functionality within the ecosystem. So obviously, for us, at least in Spain, the reality was that Agile wasn't something very common and over time it was basically being adopted. So the goal of Agile, as you know, is to actually deliver value to the customer faster. Before you need to wait a few years to get your operating system next version. Vishakha Motwani: Yeah. Yeah. So the goal of like the goal is to be Eduardo AC: The goal is to get it every day as soon as possible. So that way if something is broken, you will be able to get that. And because of that, the more often we wanted to make changes and make available features and value to the customer, the more our role evolves. So what I say is before a role was a little bit more passive, more static, more oriented into getting the things right the first try, because there is a lot in stake. Vishakha Motwani: Right. So it's that way. Right. What I said is Yeah. Right. So more with Eduardo AC: So more recently in these days the reality is different. The reality is that people are more tolerant to mistakes and they are more opening as long the feedback and the changes there to iterate over time. Vishakha Motwani: A lot different. Yeah. Right. Yeah, that makes sense. So ⁓ you spoke about like one aspect, I feel, but there are so many aspects to being an engineer. But when we talk about change, where where in your mind has what areas have changed? Or where would you see this ⁓ navigating from what time are you observing this change to be able to talk about it in a way that ⁓ tells you that, ⁓ an engineer used to do this, we're talking about one s one specific deliverable, but now there are so many things that go behind the deliverable and even after it, right? So Eduardo AC: That's a very good question. So it's difficult to explain with words, right? It depends on specific the ecosystem that you move on. It's not the same reality for me in Europe that the same reality is for you in America. So every market will move at a different pace. If you are in Silicon Valley, the different reality of expectations will be compared with some other parts in America, the same applies with Europe, right? So so I think the most critical part of a software engineer these days. Vishakha Motwani: Yeah. Yes. Yeah, yeah. Yeah. If you had it as a reality would be compared with that. Yeah. So that's something that you don't want to. Yeah. But Eduardo AC: in my opinion is problem solving and analytical thinking. So that's something that you acquire in most cases with a degree when you study it because it's part of the lectures that you gather it. But sometimes it actually feels to me that we focus a lot on delivering coding and be able to exercise the outcomes that we expect from a particular defined set of rules in a very queer matter, right? Vishakha Motwani: Yeah. So when we have time to make one. Eduardo AC: So when we are trying to deliver something on an interview, for example, the people assessing our knowledge is particularly focused on a series of signals, which is delivery speed, that there is liability of be able to execute on the particulars. And the most important part is that they have in their mind something very subtle on how the implementation will look like at the end. And sometimes we ended up being biased for that outcome. Vishakha Motwani: Yeah, sometimes you understand what the work Eduardo AC: into what the skills of the candidate is showing to us. So it's very difficult today in the market that this changing with AI so drastically to understand what's the new reality. And this is something that will come in the follow-up years. But I will strongly think that something have remained constant from when I started to actually my professional career to actually what's a reality today is that two elements. Problem solving, analytical thinking on how effectively to apply it to the reality. Vishakha Motwani: Yeah. Right. ⁓ absolutely. I couldn't agree more. But I love that you pointed out what has remained constant because Whether or not you bring in new tools and AI I would consider as another tool, this part remains the same. So if you were to speak in terms of AI, it's how do you think beyond problem solving and analytical thinking, how has the role evolved for you personally and maybe the people around you? And even if it's like European market, I think there will be some similarities. That we'll see across the globe, I feel like. Eduardo AC: I think this is a very tricky question. ⁓ my reality is still evolving, so it's not well defined. So we started last year on adopting AI and people still learning. There are things that they're talking about agentic workflows, that they are talking about how to create agents to simplify your work, how to build skills, MCPs, and so on and so on to make your reality faster. My day to day doesn't align with that reality today. Vishakha Motwani: Yeah, yeah. Yeah. Yeah. Yes. Yeah. Yeah. Eduardo AC: I would like to continue exploring that reality, but my focus is always on delivery. So I focus on what's necessary for us to achieve the goals that product roadmap have when we are trying to complete to complete the the deliveries, right? And in that reality, one of the things that is get tricky is how to organize the understanding of the problems that Vishakha Motwani: Yeah. Yeah. Yeah. Yeah. And yet that's very good. Yeah, I think. Eduardo AC: specifically products trying to solve and how to materialize those things into executable work. Because sometimes you need to share with your colleagues, we need to build this and AI can build it very quickly. So now the question is no that you can achieve that goal in a short amount of time, is what's the end result of that code that you are generating and what's the end goal of the value that you're delivering to the customers. Vishakha Motwani: Yeah. So now all the Yeah. Yeah. Yeah. we ask you something. Eduardo AC: Because something, at least in my ecosystem, is we cannot afford failure. We live within the payment ecosystems. And if we actually fail on making ⁓ the payments available because we release something that is not okay, we might lose millions of transactions. Just to give you context, we process one point four million transactions, maybe more every day, and these are representing around nine million euros, which means Vishakha Motwani: Yeah. Yes. Yeah. If you are just nothing to use with a counter signal. Yeah. Eduardo AC: If you are thirty minutes window, you lose hundreds of thousands of euros in just thirty minutes window. So you need to be very careful how you plan your work around the quality. Sometimes AI can enable you to do that. You can use the new techniques called hardness to enable you to have a better and stronger workflow, but the reality is still your judgment, still your decision and you're still accountable for the outcome of that delivery. Vishakha Motwani: Yeah. ⁓ absolutely. When you when you've talked about like the payment system and you cannot afford failure, but there are like ⁓ in my opinion there are still some areas ⁓ of software development where you can afford failure. However, what I want to go back to is the idea of like Eduardo AC: Mm-hmm. Vishakha Motwani: What happens after deliverables are deliver delivered? And even with AI, we talked about how the role has changed. One of the things that you pointed very subtly that you want to get to it faster, right? Like the timing, the expectations have changed. But what about after it? Do you see that these changes are kind of bringing a bringing in a little more technical debt or somewhere along the way that we're doing things faster, so doing it fast sometimes also has its own cons. Eduardo AC: Agree. So this is where it becomes challenging, right? So this is where we talk about this harness that is being massively adopted within the industry as a term, and is how we can keep the technical debt in check to actually guarantee that the outcomes that we have doesn't actually become unmanageable. The reality is that this is no new. So ⁓ in every engineer thing I work for Vishakha Motwani: Yeah. Mm-hmm. Yeah. Yeah, one thing is that this is what we have to cover. Yes. I mean so this is also but I think there was Eduardo AC: ⁓ the reality is that there is always accumulated technical debt. And it's up to the specific leadership thing to prioritize certain time to allocate it to always have that on check. So this is not something AI have introduced because allow us to do the things faster. It's something that always been present. And I think there was ⁓ I have to look it up, but there was a saying that ⁓ around 20% Vishakha Motwani: Uh-huh. Yeah. Yeah. Yeah, absolutely. And Eduardo AC: is what we accumulate after every quarter and if nothing has been checked at the end of ⁓ around a year you actually will have ⁓ too much technical debt and it not always the case but why me it gives you like an understanding that if things are no care they deteriorate to a point that cannot be repaired and you need to replace it for something new. Vishakha Motwani: ⁓ like y you these are this is again one more thing that's constant that's been ⁓ with you for the time that you've been in the industry, right? So if you were to talk about in day-to-day for yourself, how would you think the role has evolved for you? And in terms of like, I bet there is leadership aspect to your role, but there's also like the technical aspect to your role. So Besides delivering faster, not only how has your role changed, but the people you work with, ⁓ how has your expectations been different from the past here? Eduardo AC: Mm-hmm. That's a very good question. ⁓ so how I will formulate this is ⁓ AI have accelerated the pace at what we work on. So initially when we started adopting AI, and my colleagues started adopting AI, so what happened is it was a very fast increase on the number of pull requests and code reviews that were required because you produce more. Vishakha Motwani: Yeah. Yeah. Eduardo AC: And as an outcome of that, the reality was that it actually increased the amount of workload that we need to do to review that code. And the reality is that we need to challenge that from the senior point of view into the more unions on this strategy, which is now you not own the code that you produce. So you own the outcome of that code. Which means that from the technical perspective, your role has shifted from Vishakha Motwani: Mm. Yeah. Eduardo AC: Just writing the code that is best and you actually make mistakes along the way to understand how you build that systems and make sure that the code you produce align with the guidelines of the project. That can be achieved in multiple ways. One way is you invest the time of reviewing your own codes produced by the AI assistants and make sure that the code aligns with what you know and what you think is best. The second one is to build tools to support you on that journey and do that for you. Vishakha Motwani: Yeah. Yeah. The second what? Eduardo AC: So it depends on how mature you are in the level of automations, that specific responsibility will be evolving. Generally, over time will evolve into more of a product engineer role where you need to understand the business outcomes to be able to transfer that information to the ⁓ systems to build those journeys and to build those features and to build those outcomes. So now instead of be someone that is be able to translate ⁓ Vishakha Motwani: Yeah, yeah. Yeah. Eduardo AC: Hard requirement spreadsheet on a ticket, you need to become holistically and understanding, you need to have a holistic understanding of the product and what the product values that you're bringing with every change. Which means that now you instead of being accountable for your code to be clean, to follow the code guidelines, et cetera, et cetera, you're now responsible what's the business impact, what's the specific customer value, and Vishakha Motwani: Yeah, we need to be called. Yeah. Yeah. Yeah. Eduardo AC: this aligns with the deliverable that product wants within the ecosystem. Vishakha Motwani: Yeah. Would you say that like ⁓ with with the past comment about how the role has evolved or how the expectations have changed, I think there was still there was still a piece about ⁓ getting domain knowledge for every engineer to be able to understand what they are implementing. Is it is it helping the company grow? Is it helping ⁓ the customers get to what they want? But again, all of it across the board. Would you say that that has just generally become more and more like the quantity of it has increased? So, in that case, ⁓ you talked a little bit about having tools to to achieve your systems, to build those systems. But would you have any ⁓ suggestions or some examples where you would say that we can maintain the good quality even with the quantity? ⁓ Any recommendations that you would have? Eduardo AC: I know like the most proficient on technical workflows for a gentic workflows specifically, but in general the role hasn't changed that much since we start adopting compilers and we start adopting all this kind of reality. So what happened is it's gonna be a transition phase where we know that we are more efficient writing assembled codes, which is the one that is low level instructions on on the code base. Vishakha Motwani: ⁓ huh. Yeah. So how can I Yeah. Yeah. Eduardo AC: ⁓ but over time what happened is compel compilers adopted more complexity, they start to be able to produce the same amount of information faster and over time becomes even more efficient because they are become specialized on that domain and be able to transfer that knowledge on the compiler between one system and another. So it means that you write the language on C and you don't need to know if it runs on Apple Vishakha Motwani: Yeah. Yeah. Yeah. Yeah. Eduardo AC: with the processors or you run on another architecture, it doesn't really matter because that's the specialized knowledge. So I think the same will happen with AI. So when we think about AI, we need to understand not how AI be able to deliver the value, but how we can leverage AI to get the most efficient output. And and I explicit about output because it's not the outcome of the reality, it's just the output that the AI is producing. Vishakha Motwani: Yeah. Yeah. So I think the sample model good Yeah. Right. Eduardo AC: So you have to refine that output to get to a level of standard that you are satisfied with that on your code base. And everyone will mature in a different state. So in a way we are transitioning ourselves from Vishakha Motwani: And everyone would have to do that. So it's and where we are. Eduardo AC: Before we were writing ESLin rules, we write Pretia rules, we write TypeScript rules through the code types. Now we transfer that into the AI. We transfer that knowledge that we have into how we can leverage AI or leverage AI effectively to basically transfer that knowledge that we have with ourselves to transfer the outputs in the best or most effective way possible. And I see very much the role shift shifting to be cost efficient and specifically on the role. So we go from produce a lot of value to be very effective on the value we produce. Because it's very likely that the price of the token, even if they get cheaper, it will actually require more tokens because the models are more complex. So it's unclear to know what the future is. We're gonna look Vishakha Motwani: Yeah. Yeah. You know yeah, yeah. Yeah. Yeah. Yeah. Yeah. Eduardo AC: Two years from now. But what's clear is AI form or adoption is still present in our reality and we need to live with it. We need to write that rejected like back in the day with the compilers. We need to adopt that reality. And how we differentiate ourselves from that reality is how we use the tools at our disposal. Vishakha Motwani: Yeah. We go back. Yeah. Now it's a Eduardo AC: to actually accomplish those goals and goes back to the initial two points at talk. So if you know how to do problem solving and you know how to do analytical thinking, we go back into the starting square, which is now you start a new journey, and the new journey is how I can get the AI with a very few tokens to get the output I'm looking for on the product I am. And it will become ⁓ the role of a software engineer in the short term Vishakha Motwani: Yes. Yeah. ⁓ Eduardo AC: how to connect the code quality that you're looking for on your system and the confidence that you're trying to build to deliver the features that product wants with the tooling to be most cost effective. And when you look those things together, it's no more than another problem that you need to solve. Vishakha Motwani: ⁓ my gosh, couldn't agree more. ⁓ Eduardo, just before we ⁓ continue the recording, ⁓ your video is paused on my end. I don't know if that's the same thing, but Eduardo AC: N no no my end, so Vishakha Motwani: Okay. ⁓ let me That's okay. I think the as long as it's uploading from your end, that should be fine. So the other piece, ⁓ we come back to this ⁓ idea of transitioning, right? Transitioning our knowledge to AI and making the systems or AI better to deliver the good quality with the quantity. Eduardo AC: ⁓ Vishakha Motwani: But between this transition, like I think every change, every change brought about in an organization, whether it's your people change, whether it's your tooling change, everything goes through this transition phase. And like you said, that we are still in that transition phase. What is your ⁓ how would how would you recommend an engineer or any professional to go about a change? Or what has been your experience to adopt a change that you know is for the better, right? ⁓ there are some changes that you're still experimenting, but how do you be open to this kind of change and transition? Because these transitions aren't like, ⁓ you have it one day and then the next day you don't have it. ⁓ it takes time to go through that process. So how do you keep your mind open and evolve through this process? Eduardo AC: That's a very good question. ⁓ I will say to be fully transparent, I still uncertain what is the gonna be the future looking like. and the reality is an organizations have to support how the role evolves. So one of the things I see a lot is is lagging behind the interview process, the Vishakha Motwani: Yeah, yeah. Yeah. Eduardo AC: The reality of your day-to-day job and your expectations with how AI ⁓ is being adopted. So it's being one of those things that AI wanted to be massively adopted by the company, but at the same time you don't change the specific expectations that you have as an engineer. Because one of the biggest fears that every engineer will face is: if I do the skills, if I do the hardness, if I do all of this, what's the guarantee of me? Vishakha Motwani: Yeah. Yeah. Yeah. At the same time, but you can see. Eduardo AC: having me paying a high salary versus someone that will be able to get the same output without the knowledge. So how we split ourselves between that uniqueness, that differentiate ourselves on the problem solving versus someone else that doesn't have that knowledge by half that context I be able to solve. And this is an uncertainty that we need to deal with it and that's the reality. Vishakha Motwani: Celery. Yeah. Yeah. Why is it specifically? Eduardo AC: So, what I will say to the engineers out there that will watch this is try to understand what the organization expects from you. What's the specific reality that the organization enables? And have an open conversation. I know that this is the role and this is the expectation. You are expecting me to produce a good output of the code I delivering and to do it in a fast way. Vishakha Motwani: Yeah. Eduardo AC: Because AI is taking care of most of the workload. So if that's the case, so what's my role within the organization and what's my reality within that organization? And this is something it's not for always for you to solve on your own, but to find out from the organization point of view what they expect from you, what's the direction that they want you to take. I don't know if companies these days have that clarity. Vishakha Motwani: Yeah. Right. Yeah. Eduardo AC: And I hope they're actually looking into this specifically. But something I saw very frequent on job descriptions, job people titles, and so on, is people are adding this expectation of being very proficient on AI, workflows, agencies, staff, and so on. So if we're gonna start measuring people when we are interviewing people for those roles. Vishakha Motwani: Yeah. Eduardo AC: So what's the expectation for the people inside of it? Why those people have to be proficient on something that is only two years old or three years old on the reality of our day to day? Even if I have to speculate, last year it wasn't as much as this year. So h how do you spend someone to be proficient within just a single year, right? Vishakha Motwani: Yeah. Yeah. No, yeah. Absolutely. Yeah. But that's also the piece, right? Like the new the new things, even within AI they're coming in so fast. So ⁓ sometimes people are just working with one thing and they continue working with that. Maybe that's what they call proficiency. But the other part about connecting the two things where we talked about making AI better to help it understand the domain knowledge, the systems that you're working with, and also this transition phase where it becomes smarter to deliver the quality of code that we wanted to deliver between these two pieces. Eduardo AC: Mm-hmm. Vishakha Motwani: We I I think we've been in the space for a little bit to be able to give that knowledge to AI. But what about the other way? Like as the time progresses, there will be a time when people wouldn't probably have this context. So at that time, how does that phase work where where will people get this knowledge from if AI already has it? Like anybody new coming in the org or any company switches, job switches. So do is is do you think that that would how it would look like that we learn from it to understand the context? Because even then you might have so many ways inside your premium transactions, but to be able to know the whole system, that's another skill that you need to develop, right? Eduardo AC: Mm-hmm. If I understand correctly, is how we're gonna learn in the future and gather the necessary knowledge for the new generations to be able to deliver value that is expected from them, right? So the reality is ⁓ we haven't changed that much, right? So if you think about it, I don't know your own experience, but when I was starting ⁓ study on a school, Vishakha Motwani: Yes. I think so, yeah, yeah. Mm. Eduardo AC: There were these ⁓ electronic CDs of called Encarta, which it was an encyclopedia to actually allow us to get the knowledge, right? And what people were telling us on as school teachers were telling, don't look at the encyclopedia Encarta because otherwise we know you copy. So so the question here is the way we learn is generally by copying. Vishakha Motwani: Okay. ⁓ it's a problem. ⁓ okay. Yeah. Why don't we find that? Yeah. Eduardo AC: what's the reality and from there we actually build our own skills by have that analytical thinking to give that clear perspective. Well you provide this this gets me 80% of the way there, how do I get the last 20%? And and this ⁓ it's difficult to forecast but the reality is the way we teach people have to change. Vishakha Motwani: Yeah. Eduardo AC: And one of the main drivers with technology adoption is curiosity and passion. So the question here is it's very convenient AI comparing with in the past for us to get the outcomes we want without putting much effort. So then the drivers on the future would be people that are very curious and very passionate about learning something rather than someone that just wanted to do it because it's their job. Vishakha Motwani: Yeah, yeah. Eduardo AC: And this will be a massive change in my opinion on how we understand things. And I see this every day for the past twenty years on the industry that there is two types of people, in my opinion. Those people that are then to have a salary and those people that are then to be passionate about what they are building. It doesn't matter if you use coding as a tool or you use AI as a tool. The goal is you are curious about what your business does, you're trying to actually solve a problem that is Vishakha Motwani: Yeah. Mm-hmm. Yeah, yeah. Eduardo AC: Interesting, mysterious, and so on. And the tool is just evolved along that to enable that landscape. The problem right now that I see, and this is something that is ⁓ probably other people will know more about it, is that you will be able to deliver more with that passion that you did before, which means that you will be able to actually deliver more output comparing with the wider audience. So now how we measure. Vishakha Motwani: Yeah, means that we're back to the Eduardo AC: The value of an individual versus what's the output of the AI it is, right? Because the best model you use, probably the faster you deliver that outcome. How will you measure an engineer on an interview when it's about token efficiency or how it's about token workflows or how to harness the power of AI to accomplish that goal? I think people still stack today on it's all about making sure that you are able to build that firm correctly. Vishakha Motwani: Yeah. Eduardo AC: But that is long gone. No even for people before it was necessary because you have component libraries, you have UI tooling, you have libraries that like Read Hooks forms or ⁓ Read Query or Tan Stack that allow you to do that that before it was very convoluted and it takes us a lot of time to build. This day is just introduce a library, put a couple of lines and you're done. Vishakha Motwani: Yeah. Yeah. Yeah. I I would also be curious to understand from you, like what is your perspective? Like why do you think that was anyway put in there put in place in the first place? Like What was the reason do you think? I think problem solving still is there somewhere within that, but it's ⁓ there is also more of how much do you know? How much do you know how to write that code? But what what is your perspective on sure, things haven't changed, but why was it there in the first place? Eduardo AC: I think in general you need to think about why they are in there in the first place, right? You wanted to differentiate the good candidates from everyone else, right? So I don't know if you read about it, but it's a book called Cracking Your Code Interview. So it's the green book as I call it. And these have a lot of knowledge. But the most important piece there of information is Vishakha Motwani: Yeah, yeah. Yes. Yeah, yeah. Yeah. Eduardo AC: The way interviews were handled was specifically how the big corporations have formulated their processes. They have a lot of stage and they have a series of skills to be assessed. So as a reality is that was the place people wanted to go, which means that they have a very high bar of expectations. And the reality is people saw that the smart people were gathering there. Vishakha Motwani: Mm-hmm. Yeah. Yes. Yeah. Yes. Eduardo AC: And they were actually working on places like Google or Amazon delivering a lot of important stuff that enable the company to grow effectively. So because they show that reality to the community, the community star adopting a similar process of validating that information to make sure that they assess the candidate fairly, but most importantly get a good good candidate that be able to deliver the value. So historically, if I start Vishakha Motwani: Mm-hmm. Yeah. Yeah. So because Right. Yeah. Yeah. Eduardo AC: talking about my initial interviews in UK, it was about algorithmic coding, right? So how you will be able to do a short algorithm, how to use the different strategies, how to be able to ⁓ order a list in in the most effective way, and you have to write that algorithm, right? So this A is about how you build the UI components and how you build the interactions to get the output that you want from the customer. Vishakha Motwani: Yes. Yeah. Yeah. Yeah. Yeah. Eduardo AC: Right. So you you wanted to actually understand that reality and you use the forms and all these visual elements. ⁓ with AI is probably about how you get to the output that you're looking for. Like what's the reasoning behind those decisions? What specific prongs you put into the AI, why you decide to go these directions, how you will be able to do it more effectively. Maybe you have your own skills being predefined, so what those skills represent. Vishakha Motwani: Yeah. Yeah. Yeah. Maybe not. Eduardo AC: And so on and so on. Vishakha Motwani: Yeah, absolutely. I think that's ⁓ it again comes back to the idea of we learn from copying and it's not a bad thing. It's just that you have to evolve with the system with the world around you. But thank you so much for speaking about this today. However, I'd like to summarize like this is how I'm thinking about our conversation today. One being you s problem solving skills and analytical skills. they are constant, they have been constant across the role. The last piece is if you were to grow, it still comes back to the idea of curiosity and having the passion to deliver and not getting ⁓ discouraged by by the tools that are being brought in by your organizations or you yourself, right? They're making you ⁓ more efficient and your curiosity is what is going to stay within your role, right? ⁓ but I would like to end this conversation and I'll I I'm going to ask these three questions to every guest of mine. So ⁓ my first question to you is if someone remembers only one thing from our conversation, what would you like that to be? Eduardo AC: I would say I want people to take away that a tooling enable us but as well can constrain us. So think carefully ⁓ how you use the tooling for your own benefit and rather focus on a particular tooling to get you the outcomes you want, focus on how you solve those problems and be able to use that analytical thinking to deliver those outcomes that you are very much in need for, right? Vishakha Motwani: Mm-hmm. That's very beautifully ⁓ put together with problem solving and analytical skills. Like eventually that's what gets you to your next level, to your best version, right? ⁓ second question that I have is what's a book, ⁓ show or a podcast that you'd recommend ⁓ you recommend engineers or you listen yourself that that has given you some insight or brings you back to a new different perspective. Eduardo AC: You mean besides this one? Vishakha Motwani: ⁓ thank you. ⁓ Eduardo AC: I don't watch that many podcasts as I would like to because most of the postcasts are quite length. ⁓ but I generally what I do is I take ⁓ a lot of time on reading newsletters and reading from those newsletters and learning from them. So if I have to recommend to people, there is basically the React newsletter from Sebastian's that actually every time shares what's actually new on the React ecosystem. Vishakha Motwani: Yeah. Mm-hmm. We can. Okay. That was where I'm going to forty cows. Yeah. Yeah. Eduardo AC: ⁓ there is actually one very interesting from Dan Neseu, if I pronounce correctly. He has as well another podcast. I watch a few of the talks and he's talking to very important people on the industry with different topics. And and I will say f the last one from me is Never Split the Difference. It's a very good book. It's the book I have on this one on the left. So this particular book. Vishakha Motwani: Yeah. Yes. Okay, okay. So Eduardo AC: is not about engineering, but it's about how to communicate to others to effectively deliver the negotiations or success on the negotiation, on the conversation. And the reason because these skills become very important is because these days you don't solve problems alone. You are as part of a community. So the fact that you'll be able to first understand the reality of others. Vishakha Motwani: I don't want all this. Mm-hmm. ⁓ Yeah. Yeah. Eduardo AC: And second, be able to acknowledge and provide insights on others' people's value is very powerful. So I very recommend this book from Chris Boss at called Never Split the Difference. And I can recommend others ones if you're interested in the eighty twenty rule, the power of laws, if you are talking about you wanted to become a manager, the elegant puzzle, so on and so on and so on, right? Vishakha Motwani: Yeah. Yeah. Yes. Yeah. Okay, so ⁓ I I think here, we've met a few times, so you know like what ⁓ as an engineer, as a senior engineer, ⁓ what do you think is the one one book that I could read today that would give me the most benefit or most bring in the most positive impact on my ⁓ day to day career? Eduardo AC: That's a very good question. ⁓ I will still hold if you haven't read Never Split the Difference, read that one. Because ⁓ a senior person has to be able to communicate effectively and most importantly have to be able to lead outcomes from others' people, right? And this is a negotiation skill that is a required one. And if you're talking about the technical part and you are looking into the IC role like a staff engineer, I very recommend the staff engineer path. Vishakha Motwani: Okay. Okay. Yeah. Absolutely. Yeah. Yeah. Yeah. Okay, yeah, I've heard that from you. I've seen your post. ⁓ it's on my Amazon list, so Eduardo AC: So that I know. So but that's why I say for me, I will say I lean more to the soft skills as a senior member, because the hard skill will start losing value over time with a new reality. So focus on how you be able to engage with others and be able to get the outcomes that you're looking for as the first step to become from senior to staff, principal. Or if that's not your thing, then as a manager will actually be a very powerful. So there is no Vishakha Motwani: Yeah. Mm. Reality, yeah. Yeah. Yeah. Yeah. Yeah. Yes. Absolutely. I do think that negotiation is one of those things where like you're constantly doing it, even in your everyday life outside of your career, but that's also a word that weighs heavy for me in terms of there is a there is a part about Eduardo AC: lose a scenario whatever paths you choose to grow. Vishakha Motwani: I want to win this negotiation, but there is also a part about like we want to have a win-win situation, right? So ⁓ to me like that I'm definitely going to put that on my list of readings and that would be something that I know I will benefit from. At least it'll take out the anxiety from that word of negotiation, which is again it's it's another conversation, right? So ⁓ and the last one that I have for you, what do you do to decompress like when your laptop is off? How do you disconnect from the day and kind of give time for yourself? Eduardo AC: I have three ways of doing it at the moment. One is complaining. I think it's very good and healthy to bent out how you feel about things. You just need to find the right forum for you. If you don't have family and friends that be able to support you on that because everyone has their own luggage, yes, these days you can use ChatGPT to bent out and I'm sure they will tell you you're right. So that's a good thing to feel. And Vishakha Motwani: Yeah. Yeah. Yeah. Yeah. Yeah, yeah. Yeah. Yeah. Eduardo AC: The second thing is actually go out. That's particularly when it's a good weather, go to the gym, socialize with others, get to meet those friends, sometimes to bend, sometimes just to have that catch up. These days with technology we tend to say sit in the couch and watch a T V series, which is fine, which is the third option. But the reality is ⁓ that option will actually kind of become a void and you will feel a little bit more empty each time. Vishakha Motwani: Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Eduardo AC: So aim for that ⁓ social aspect that as human beings we require and sometimes AI will be able to fulfill that even if it's funny. ⁓ because the reality is you wanted to vent out first phase, then you wanted to enjoy your friends and your friends doesn't want it to enjoy you back if you are venting out all the time. So so it's a win win scenario that you're looking for. Vishakha Motwani: Definitely. Mm-hmm. Mm-hmm. And sometimes the product. Yeah. Yeah. Yeah. Yeah. Absolutely. Okay. Thank you so much, Edward, for going first. This was everything I hoped it would be. And ⁓ this was the Unfiltered Engineer. See you in the next one. Eduardo AC: Thank you very much.