MAJOR SHIFTS HAPPENING - Everything You NEED To Know To Survive In the Tech Industry

This week on Software Sundays, KD breaks down the real power shifts happening in tech right now — from AI companies navigating government pressure, to leaked source code exposing how fast innovation is moving, to OpenAI stepping into media.

We’re not just talking about technology… we’re talking about control, influence, and what it means for builders.

We are entering a phase where technology, government, and media are converging — and builders need to understand not just how to build… but what they are building into.

If you're an engineer, founder, or someone trying to understand where tech is headed — this episode gives you the context you need to move strategically.

CHAPTERS: 
 
00:00 – Welcome Back + What Software Sundays Is About
03:30 – Announcements
07:20 – Anthropic vs Pentagon: What Happened
12:15 – Why Engineers Lost Leverage
14:30 – Layoffs, AI, and Labor Pressure
16:50 – AI as National Infrastructure
18:40 – Ethics vs Reality in Tech Today
20:25 – Anthropic Code Leak Breakdown
22:50 – Why You Can’t “Take Code Back”
26:15 – New Features Revealed (AI Memory Systems)
30:25 – OpenAI Buys TBPN (Media Play)
32:00 – Narrative Control in Tech
35:50 – Media + Power + AI Convergence
38:20 – What Builders Should Pay Attention To
40:35 – Q&A: How Engineers Move Faster
48:20 – What Is an Algorithm? (Simple Explanation)
52:00 – Real-World Algorithms (Social, Economic)
01:00:10 – CTO vs CIO Explained
01:06:40 – Should You Get CISSP?
01:16:30 – Breaking Production: What To Do
01:24:10 – Real Story: Breaking Production
01:28:00 – Mindset Reset: Don’t Give Away Your Power
01:33:10 – Closing Thoughts + Outro
 
#BuildLearnImpact #SoftwareEngineering #AI #TechLeadership #Cybersecurity #BuildInPublic #Leadership #STEM #TechCareers #Entrepreneurship

DISCLAIMER: This is not professional advice. The views expressed are my own or those quoted. Consult your own legal, business, or tax advisors before making decisions based on this episode.

Build Learn Impact is on a mission to help you create wealth, opportunity, and ownership through technology.

Transcript

SPEAKER_01 0:00

What's going on, builders? Welcome to Software Sundays, where we help you shape the transformations happening in technology all around you. This place is a place for you to start to learn what's going on in big tech, what's happening from a hardware to the software level, and how that's starting to change and impact how we live our day-to-day lives. So if this is your first time, welcome. It's great to have you. It's been rocking with us for a minute. It's good to see you back. Let's keep it going. Before we start, uh just a few quick announcements. Well, one, welcome back to myself. Uh I hadn't been doing any of the episodes for two weeks on vacation and then just resetting, getting everything back to, and I'll say back to normal and back even better than how we were previously. So we're finally back. It's good to be back. I'm very excited for the next phase of Software Sundays and Build Learn Impact and everything that we're gonna do together to just improve our comp our skills and just be way more competitive inside of this market, especially with all the things that are gonna change and are changing right now. We'll definitely get into that later on. Also, happy Easter. Uh I was talking to my cousin yesterday about Easter and how like it kind of changed today versus when I guess when he was younger, and then even when I was younger, Easter was more, you know, you go to church, you spend time with the family, like it was more uh structured at that point. I wonder, or I'm seeing that today Easter is looking more like uh you know Children's Friends Day, or you just are with the friends, which is nothing wrong with that, but it definitely speaks to some of the changes that are happening culturally all around us. So however you are uh enjoying your Easter, if you put your best foot on to be with your friends or with the family or with the go to church, I hope you are enjoying or you have enjoyed, and it's been a great time for you. I hope you think about the origins to why we even celebrate an Easter and what that means for you if you're religious or if you're not religious, just understanding kind of the history and the symbol symbolicism that has gone into this holiday. And also, big shout out to Baby Kay. Her sixth birthday is in three days, two days. I gotta get better about that. But her birthday is coming up this week. Happy birthday, baby Kay. I uh love to see you growing happily and healthily and becoming the amazing young person that you are, and I just hope you enjoy your day and feel loved and happy and excited. All those things. Uh and some other news. Part of the new phase of BLI is adding some weekly webinars. I want to help propel and improve our mission of making sure that everyone has the resources and opportunities and the skills that they need to excel inside of tech. And with that being said, I want to cover a few specific items that will really help just push all of us to that next level. So when you think about tech, there's a lot that can be involved, just even from an engineering standpoint. You could be involved in cybersecurity, you could be involved in the software development, uh, the product design and development, DevOps, cloud. There's a lot of aspects that could be focused on and that go into making sure an application or a system is successful. We're gonna be spending a few hours every week as a community just talking about those specific areas to make sure that everyone is on the same page about what they need to know and understand and look into in order to help uh drive their own success in those areas. So I'm gonna spend a few weeks on cybersecurity uh just because that is where my mind is currently. That's what my current role is focused on. But we'll also dive into some specific languages and frameworks that will be really helpful to everyone, whether you're building a MVP or you are help looking for an opportunity inside of your current company or some other company that you want to join to see what tools can I use to either make the product more efficient, to make our processes more reliable, and just see how we can do better as technologists and builders. And we'll also dabble a little bit on some entrepreneurial uh topics from just looking for product market fit to setting up your business and all the things that kind of go into before you even have a product or service or a customer. What do you need to think about from a management perspective? We're gonna get into all of those over the next couple of weeks and months. And if there's a specific topic that you really do want to just highlight and stick on for a specific series, definitely drop it in the comments. Let me know, email, text, let me know what we could do, and I'll make sure we are tailoring it for you. Uh, so that being said, let's jump in. Uh but let's do our disclaimer real quick. So, Software Sundays is for informational purposes only, and it is not intended to be professional advice. Uh, the views expressed are my own and may or may not align with the views of Build Learn Impact or their affiliates. The topics that are discussed may or may not apply to your specific situation. So please consult your own business, legal tax, or other advisor before making any decisions based upon the information that you find in this show. Uh, with that being said, if you enjoyed the information, if you are uh getting value from the information, uh please share it. If you're if you find something useful on your own, let us know, and let's all just continue to get better and improve every day. So, first things first, I wanted to just highlight uh that know there's a lot going on in the news right now with Anthropic and how they're being handled and handling the uh situation on that relationship with the Department of War today in Pen the Pentagon and how they were a few weeks ago kind of quote unquote banned from being used, or their software was banned from being used uh for any active missions inside of they tried to make it like a government-wide federal ban, but at least specifically in the Pentagon, which is where the like the issue started. And then the the Supreme Court kind of struck that uh the Supreme Court basically struck that law or that idea, that rule down, basically saying that you can't just turn an American company or you can't try to classify an American company as a foreign threat or some type of uh a risk just because there are some contractual issues or they didn't want to uh roll and play the way you wanted them to play. So that has kind of saved anthropic from the worst fallout that could have possibly happened with that type of classification, but it also highlights some of the risks that are very prevalent for big tech and the people that work inside of these companies and the types of projects that they are working with or working on. So one, this is not the first time that a technology company has had to deal with disagreements from an internal standpoint on how their technology is going to be used. Back in the 2010s, there were thousands of employees in Google that were basically boycotting Google's use of their technology for surveillance and military operations. At the time, the employees of Google had a lot of leverage and it ended up working. They were able to say and put their voices together to say, hey, we do not want to be a part of any type of military or war-specific activities. And they were able, Google was basically not able to go and get those additional contracts that would force them to use their technology for some of those unuse cases that people kind of were like, we're not sure we want to be a part of. So this was back 2010s or mid to late 2010s, and this was a win for the tech employees because they were actually able to operate as the voice of reason to say that, hey, we do not want to, or they were actually able to say that we want to separate the tech innovation that we are driving and leading here from state control and state power. Like we're not trying to just say that everything we build needs to become a weapon for the government. And that was very cool. That was possible at the time. There was a lot of other opportunities for tech. Tech was growing and things were just good. When you're fast forwarding to today, yes, the great thing is that company leaders like Anthropics, uh CEO and founder, had and have similar mindsets where they'll where they're able to say, hey, we don't want to have our technology being used for surveillance, for autonomous uh drones that are actively fighting. Like there are some people in pockets that are still maintaining the moral line between just developing great technology and having that technology used and deployed in less than ideal situations. But the challenge is the employees don't have the same amount of leverage. So while a decade ago, 4,000 Google employees were confident enough to sign their name as a part of this uh boycott against joining Project Maven, today only a few dozen felt confident enough to say, hey, we don't want to have our technology being used, or we don't want to have AI technology that is being developed being used for these types of use cases. And part of that could just be that the technology is a bit more mature, so there's less risk of having uh unfinished AI and autonomous systems powering military operations, which is just a that's just risky and it's almost like a risk that you really don't want to put your name behind because you don't know how these applications will operate in the real world. We've gotten past where AI is much smarter, much more uh effective, and able to be controlled. So that could make people more confident with saying, hey, we don't mind certain applications being used, but it also is possibly caused by the fact that tech employees don't have the same leverage that they once had. Now we are seeing mass layoffs from companies in big tech to financial services companies to every area of the economy having issues, or from the employee standpoint, labor standpoint, having issues keeping people inside of their position. And that is caused by a number of things. AI, over hiring. There's a lot of reasons, like challenges in the economy. There's a lot of reasons that are making it more difficult for people to keep their roles, but it also makes it much more challenging and harder for people to find new roles. So that hiring cycle is definitely starting to expand, also. So it's putting tech employees and tech uh labor markets into a position where they kind of gotta just roll with the trends that they see. And so if you are seeing your leadership is all in on saying we're gonna do this, you don't have as much of an ability to say, I don't want to be a part of this because you know you don't, or you may have a little bit of fear and apprehension that, hey, if I say no, I'm going to have a very difficult chunk time doing the things that I need to do as a regular person. Like if I get fired, laid off, and it becomes harder for me to find a new role. Now I can't pay my mortgage, I can't pay my bills, I have challenges in my family. So there are these types of uh pressures that is being felt from tech employees that has definitely made it much easier for the aggressive standpoint that we're getting from the government to actually take hold. Because, and this is not just from the US uh perspective, every company or every nation in the globe has understood and sees that AI, data centers, and technology are becoming part of their sovereignty, they're becoming part of their sovereign infrastructure and their ability to compete militarily and economically. That's becoming clear. It's almost like having water rights and access to clean water. You can't really improve your nation and your society without having access to these resources. AI and technology is one of those major resources today. And so they, from a government policy standpoint, are being more aggressive about how they use the resources available. And for a lot of countries, your greatest resource is going to be those technology companies that operate and that are formed inside of your country. So if they are creating applications with AI, if they are creating a lot of resources that are being powered by data centers, as a government, all you can do is say, hey, we are going to use this technology to compete in every area that we feel we need to be competitive in. And there's almost no breakers. There's no one that is going to scream and say, hey, we should not be doing it. I won't say there's no one. It's just that there are less people that are available to say we should not be doing this. Just because of all of the different dynamics that are uh just showing in the market today. So I am sure at some point in time we will get back to the point where tech employees and the builders like yourself feel confident enough to say, hey, we do not want to be involved in these types of projects. There was a time where DI was uh very much pushed inside of these organizations. A uh ESG having some type of ethics and uh, you know, not morality, but ethics and risk boards that could look at a application or technology or project and say, hey, this either aligns with our mission, our goals, and our policies, or it does not. And being able to move and engage resources to shift us back into the direction that we need to be shifted into. Right now is just a funny time. I say funny, but it is a different time. But I'm sure we will get back into that uh more progressive, in my opinion, uh standpoint. But that's not where we're at right now. But it is good to see that there are still companies and leaders that are aware of the impacts that the systems that we build will have in real society, how our technology and our innovations will actually impact real lives all across the country and all across the globe, really. And speaking of anthropic, uh flawed source code recently got leaked. Uh this was announced to be a purely human error. It was no type of AI coding issues that did it. Uh human and human user and process error allowed the source code and the mappings to specific files and directories to be uncovered and shared as a part of a node TypeScript package. And with that, people on the internet developers were able to identify exactly what code and what processes and capabilities have been designed into clawed code and similar products. The interesting part about this is how quickly the code was identified and uh disseminated across the internet. Within hours, there were thousands of copies of the code shared and uh cloned into different websites, uh repositories, and just it got out of hand very quickly where there's no longer a single target you can go with a cease and desist letter to say, hey, get rid of the code, shut it down, stop, you know, reaching. Can't even do that at this point because there's too many people that have it, which is one of the benefits of open source, right? And decentralization. But probably not if you are an enterprise company that was trying to uh keep your code folks and proprietary and secret. So this was a very large challenge for Anthropic because at this point there's not much that they can do to kind of get the code back. A significant portion of it is now public, and that is and that could have a significant impact on how they in the future uh compete in the market. That that doesn't mean that just because people have the code that they can actually go reproduce it in production, right? They don't have the same uh talent available on the team, they don't have all the accompanying uh pipelines and infrastructure and capital that will be required to actually, you know, recreate the magic of clawed code and all of the other clawed uh products that Encropic currently has. So it's not like an end of their company as a whole, but it definitely highlights some of the risks that we're seeing from having AI accelerating the release of code and the release of new features without there being a without there being an additional training of resources and team members to make sure that the processes that we're all running, that the systems that we use to deploy, to run, to test our code, like those haven't been upgraded to From a security perspective, to match the speed of innovation and development that is almost required at any company using AI today. So it definitely highlights some of those issues and the gap and how dangerous that can be in the long run. Like today, there wasn't any leak of any customer or user data. But the more you you deploy, the more cycles that you're going through without having those types of controls in place, the more likely it is for there to be some type of risk to actual user data or privacy uh breaches. So it's definitely something from a leadership standpoint. I'm sure they're gonna go back into the process, and they already have, uh, to figure out what is what was the root cause. Figure out what they could have done differently from a system perspective and a process perspective to make sure that something like this never happens again. Because that's really all you can do. You can only learn from the situation and make sure that you do better next time. But when we're dealing with AI, when we're dealing with uh high speed, which is one of the hallmarks and the uh the edges that startups have, then you start realizing how important and how necessary it was to have all the controls that you usually see in an enterprise or some other established uh company, that it has to operate under more regulations or just under more load and has more people to dedicate to these systems and these resources or these processes. But some of the very interesting parts about the code that was leaked was that we got a firsthand look into some of the new features that are going to be available in Cloud Code over the next few weeks or months, maybe depending on how their roadmap was going to go. Uh, one of those being Kairos, which is an always-on agent that kind of runs in the background of Cloud Code to keep the context and the memories and all of the uh literally all of the context that your agent knows about you and your organization or your team or whatever it is that you're doing, all of that context was going to be managed offline by this Kairos auto system. Or this Kairos system, and they had another name for the like auto dream or something like that. Basically, it was going to be the way your Claude could merge duplicate memories, uh, eliminate contradictions, and otherwise remove information that would negatively impact your ability to use Claude's code to its most uh effective use. So that agent hasn't been enabled yet, but it's something that we should hope to expect over the next couple of months, especially when you think about the importance of context for any AI system right now. At the end of the day, all of the models are definitely converging on their ability to do the thing, whether it's write code, whether it is think or generate some type of text or image, whatever it is. These models, whether they are closed sources or open source, they are starting to not have significant differences in their inside of their actual abilities or the actual actual intelligence and what they can actually do. So the additional features that you add with these models is are going to become way more important moving forward. It becomes important to see how is your product using a managing context, how is your product uh making sure it's using data efficiently so that you aren't unnecessarily running into or you aren't running into context issues earlier than what is needed. So that's a future feature coming out. Uh there's also some other uh there's also some other features that were in the code but that haven't been turned on, such as somebody uh persona that would basically comment on your code or your uh your text as you work. And that could be used to boost engagement for cloud code. And another feature, an undisclosed coder mode, where cloud code could be uh deployed on a public repository and make commits and changes to that repository without being without it being publicized that cloud was actually working on that code base. So not totally sure what all of these features are going to be used for, but it's definitely worth keeping in mind and keeping an eye on as we start to see the models continue to get better and new features get released. In some technology and media news, uh OpenAI buys tech industry talk show TBPN. If you're not familiar, TBPN is a daily talk show that is very much tech focused. They talk about uh VCs and capital, they talk about uh different titans in the tech industry from Jeff Bezos to the interviews with uh thinking right now, I just faced out crazy. Elon Musk, uh who we at the Meta CEO. Uh like they talk about these types of folks or talk to and interview these folks and talk about different things that are happening from a tech industry perspective that could affect companies from a much higher level. So it's very interesting that this purchase has gone through. Uh recently, I guess we're all kind of aware that OpenAI seems to be going public soon, uh, probably later in 2026, uh, potentially into 2027. Uh, but they're definitely making moves to make a public offering. And they're raising money, they're making sure that they are looking competitive to other companies like Anthropic, so that when they do go public, everything is how it needs to be. And they have started shutting down uh distractions, what so they call them, uh like Sora, their video generation, uh social media app. But I guess they felt, or the leaders there at OpenAI felt that making the bet for technology media was still worth doing. It wasn't far enough outside of their uh their current activities to say, hey, we can't, it does it makes it still makes sense to spend some money here so that we can help control the narrative that is being spoken about our products and some of the innovations that we are leading inside of the market. So it's not only about OpenAI kind of just purchasing a talk show, they are literally integrating the narrative for their technology into the company itself, right? If if this independent or formerly independent talk show would have spoken about OpenAI or Chat GPT or any of their efforts over the last couple of months, they would have been speaking from a third-party perspective. They are not involved, they may know a few of the people that work at the company, but there is no legal uh ownership, there's no sense of control that those companies that they are speaking about actually has over this news outlet. But once you purchase the company, now even if you say it's an independent entity, it's no longer going to be as independent as it was before. Now, everything that this company says actually affects the parent company. So for better or worse, that does open up risks and the chance that the things that need to be said from an AI perspective, from a from the perspective of how is AI affecting the economy or the environment or society, those things that need to be said may not be said. What happens when there is a story that, or not even when there's a story, if there is an advancement or some significant change in the story about how AI is impacting labor and the labor participation of not just college graduates, but also uh people that are in roles that are just getting automated. What happens when there's no longer an outlet that is independent enough to have those real conversations and ask those questions that need to be asked? So this is great from a brand marketing and growth perspective for a company like OpenAI. They get to not only lead the innovation, but they get to lead the conversation that is happening around their innovation, which is super helpful. And they get access to the audience that TBPN has curated that is already interested in tech and the products that OpenAI has been building. But it definitely is worth keeping in mind from a community standpoint that there's a risk when companies that are leading and shaping institutions and public policy and regulation, when they have a significant media engine behind them that can directly influence the conversations that are had around their activities. And it's more important than ever that people in our community understand that these are the types of things that are happening. That when you look at these news broadcasting companies and look at the ownership stamp structure and see that the same people that are owning the news, the whether it's a uh you know a traditional New York Times or Fox, like broadcasting company or like a text-based newspaper, those same companies are being owned and controlled by the same companies that they are supposed to be providing independent and truthful stories and takes on. What happens when that's not happening? And how much are you aware that it is not happening? That they're not as independent as they are supposed to be, or that you had thought that they were going to be. So it's very important for us to not only go into these rooms and make sure that our voices are being heard and that the truth is being shed to light, or that the light is being shed on the truth, but we also need to make sure that we are creating those same rooms ourselves to make sure that there is always a space for our voice to be spoken and to speak light to truth. So very interesting, very much worth keeping an eye on as we go over the next couple of years and see how we already know media is changing, but what exactly does that change look like when media and state power and technology are starting to converge and aggregate and centralize around very tightly knitted uh groups of people? So let's do our best to be aware and mindful of these uh interactions and identify opportunities for us to compete with those uh parties, however they choose to operate. So uh let me know what your take is, though. Do you think I am uh looking at the wrong thing? Am I in the wrong direction? Uh what do you think happens when the tech big tech starts to become more and more involved with media, or when media starts to become more and more involved with the government and public policy and uh just state-backed plans. For your thoughts, drop them in the comments. Uh, make sure if you are enjoying the conversation, uh like, comment, and subscribe. Let me know what you think, and let's continue to have great conversations and go very deep into how this world is working. Because it's working, whether you know about it or not, or whether it's working in your favor or not. Also, all right, so we're gonna jump into our questions for this week. Uh, as always, thank you for uh sharing your questions and sharing your ideas. If you have a question that you want to know us to cover, if you have an idea that you're like, I am thinking about this, but I'm not totally sure uh where I should kind of focus on it from. Uh, send in your question in the chat, the comments on Instagram, LinkedIn, YouTube, you know where we at. Uh, and we will do our best to respond as quickly as possible and in the best way as possible.

SPEAKER_00 37:10

What tools and techniques do high-performing engineers use to increase their speed and efficiency?

SPEAKER_01 37:15

So think about this from the perspective that high-performing engineers are not just paid to write code. You're paid to solve a problem, and that problem may involve or can potentially be solved using some type of code or some type of software. But you should focus on creating systems that can automate repetitive work, that can compress feedback loops into tighter timelines and make decisions that reduce the stress of a manual person or human having to make that same decision. So, from a tool and technique perspective, make sure that you, as an engineer, have access to tools that help you think strategically about how you go about solving these problems. So, having some type of task management tool, whether that could be a JIRA, that could be a clickup or a notion. You need to have some type of resource or tool available to say, these are the tasks that I need to get done. And this is the information and the knowledge that I have about that task. So you want to have some tool there. Like I said, I use clickup as my task management tool or my task management system. I'll say it's tool more so than system. My system is that I move things from to do to completed throughout the week based on the uh my completion of them. And I have different uh categories in there. But basically, you want to have some type of tool in place for yourself that you can rely on and fall back on between shifts. And whether that shift is before or after lunch, uh before or after the weekend, or whenever you start working and getting back into your flow, you want to be able to jump back in and know that you have all of the context that was picked up from the last session that you worked on, so that you can continue to uh finish off on that task. A lot of the time, that's where uh developers and engineers and professionals just mess up. There's a gap between what they remember doing and what they still need to do. And so they end up redoing things that they already did, which waste time, waste cycles, and just doesn't allow them to be their most efficient self. So have those tools. Also, when you think about your ideas and the way that all of us think, if you were just to meditate and just try to hold on to what your thoughts are, you might realize that your thoughts almost never have a structure to them. So you have to be the one to give structure to thoughts and ideas. And that could look like visualizing ideas with graphs, diagrams, or maps. So have access to and become familiar with a tool like draw.io, like a mirror. Uh, if you're familiar and comfortable and have access to Microsoft Office, use Visio. You want to have something that can help you uh map some of the ideas that you have from just the from merely words. Words aren't enough to effectively capture the real worlds that developers and engineers are having to are having to operate and build for. You have to have additional tools and systems in place to actually make it easier for you to make those decisions and see what you're looking at more effectively and accurately. So make sure you have that inside of your toolkit and also rely on reusable assets and systems and processing. You don't want to be doing something new every day, right? If this is something that you have been doing or that you need to continue doing, and you expect to be doing for a few weeks or months or even years. You should have some type of system documented, process documented to help you go through those required steps as easily as you can, as quickly as you can. And have that resource be alive, right? You want to be able to update it as you go through it every time because things change it, change. You might uh get a new update for this week that you just need to kind of tweak inside of your process. So you want to need to make sure your process is editable. You want to make sure it's shareable so that you can pass any resources and knowledge to someone else that is coming to either support you or coming to do the work for you so that you can actually delegate and get time to focus on more important tasks for yourself. So focus on building systems that allow you to do repetitive work without having to learn it all over again or having to memorize how to do it. You don't need to memorize everything that you do if you write it down. Why use that? Why use all of your important mental resources to memorize some steps that you could write down? It doesn't make sense. You're not a computer, you're not a database. There are actual tools and systems that are always going to be more effective at recalling information than your mind. Use your mind to be creative, use your mind to make decisions that a computer would never think to make. Because the truth is, great builders understand that our job is not just to do the thing. Our job is to understand why the thing is happening and become more efficient with the resources that we have available so that at some point we can even remove ourselves entirely from the process and still get the same, if not better, results without the same amount of effort and energy use. So if you want to increase your speed and efficiency, learn how to drive and manage the system. Don't just be Become part of the system.

SPEAKER_00 44:01

How would you define an algorithm?

SPEAKER_01 44:03

So, this was a very interesting question that I heard from a family member uh over the weekend. And we were actually talking about the algorithm for uh like the metas and I say metas, but the Instagrams and the Facebooks and just social media as a whole, and even from a music business standpoint. But from a technical that uh from a technical perspective, the definition of an algorithm is a finite and well-defined sequence of steps or instructions that are designed to solve a specific problem or perform a specific computation. Basically, the algorithm is the series of steps that allow you to get from X to Y if you're thinking from algebraically, right? Everything inside of that f of x is the algorithm. All of the steps inside of that function is the algorithm, and that algorithm could be as simple as x plus one or x divided by two or plus three. It could be very simple, but when we're thinking about real-world algorithms that we kind of live in, those algorithms are usually more not difficult and maybe not even more complex, but they definitely involve more inputs, right? Because it's not just the one X, you might have everything from B to T as your input, and you may have steps one through 197 as your function, as your algorithm, as your series of steps to get to your final output of Y. And you could even have Y, Z, C as an Y and Z as the output of that specific function. And so that's why the concept of an algorithm can become uh difficult to grasp and understand. But for us builders, it is important to understand that if you break down an algorithm to its most system uh simplest and basic form, it is really just about taking the input and getting an output and understanding that the everything in between is your algorithm. Your algorithm in college, when you're going through your uh what class were we in? Uh computer algorithms, but also like data structures and and like when you're going through sorting algorithms, understanding that quick sort, that is a specific type of algorithm, uh merge sort, bubble sort, these are all algorithms. The if you ever have completed a leap code assignment when and you're calculating the number of uh what's the word andromedoms? Um, that's not the right word. I'm trying to think of an example like of a question I did recently. Let's say you are calculating the number of or the longest string or the longest substring inside of a string, or you could make it as complicated as you want, but whatever the goal is of the function that you are writing, that is the goal. But the code, the different steps of the function that you write, that is the algorithm. That is how we get to our expected and wanted output. And you need to understand that is not like every algorithm is not going to be new, every algorithm is not going to be digitized. Some algorithms have existed for centuries. Like, honestly, if you think about the uh I would say society and the way we kind of act, the fact that we all grow and desire to have children at some point, or you know, most people desire to have children at some point to reproduce, to pair up, reproduce, and all these things. That's an algorithm. That is a rule that happens because there is a function within all of us that is driving us toward things. These algorithms create systems that we kind of fall into and stay inside of, whether we are aware of them or not. The new algorithms are TikTok, keeping you on TikTok and scrolling for eight hours a day and keeping you engaged on their platform so that they can have whatever the outcome is that they want from your engagement. Some algorithms are labor participation. If you want 100% labor participation, there are certain things that the federal government, Federal Reserve, and these other institutions do to ensure greater labor participation. Some of that is in allowing consumerism or uh pushing consumerism to make sure that everyone feels like they need to get this and that so that it drives them to continue to work. And the different inputs could include uh, you know, labor cost and you know, minimum wage and taxes and all the other things. These are different inputs that affect the output that you want. And the most important thing to understand about real-world algorithms is that every algorithm has a goal, it has an output, it has an intended output, and you can usually test if and how close the actual result is to the expected result. And if you feel like the expected result is not as good as you want it to be, then you can actually adjust and change the algorithm to more effectively hit your expected result. So that is why different platforms become more addictive to some users, and that is why uh sometimes the algorithm not breaks, but it may have been overly adjusted to reach some type of outcome, and it worked, it did what it was supposed to do. But now that it reached that, maybe some other variable inside of the environment changed that made that expected and target outcome no longer the outcome that we really want to push, or the outcome that we really need anymore, right? We're looking at that with Facebook today, and there was a lot of energy and effort that went into making their applications more addictive. But now they are being sued for becoming such an addictive tool and knowingly making addictive tools. So they will have to readjust the algorithm, they will have to put in guardrails to make sure the algorithm cannot affect certain people, um, specifically minors, the same way they affect adults or people above the age of maturity. Whether that means they're adults or not, I don't know. Uh it could just be people inside of adult bodies. But the point is an algorithm is data-driven. The point is an algorithm is to understand an algorithm doesn't mean you have to be super clever. You just need to be aware that there are some decisions that are being made by some particular party in order for, especially usually the party that owns the algorithm, whether it's the owners of TikTok, the owners of Instagram, the owners of YouTube, they have a goal that they are targeting. The algorithm, the platform, the app, the system, very much synonyms for each other, are designed to help that owner reach their goal, understand what type of decisions are being made from an outside perspective to see, okay, this is what they are focusing on today. You can just jump in and follow the algorithm. And you can be very successful by just uh reverse engineering the inputs and the outputs to see if you want that same output. That's one way. But if you and I would even say that sometimes the algorithm is designed to not let you carve your own path inside of it, or at least on this particular platform, right? If you want to go do something different that goes against our algorithm, you can do it. You just can't do it here. Everything about this algorithm, algorithm is designed to do it this way. And so if you are trying to operate against traffic or go against the flow of the current, you're going to have a very difficult challenge ahead of you. But that's really just all my thoughts that I had about an algorithm. It's really just I wanted to just highlight how the algorithm or the definition of an algorithm is not complex, but the algorithm itself can become as complicated as it needs to be in order to get the expected results. And so just keep that in mind.

SPEAKER_00 54:14

What are the key differences between a CTO and a CIO?

SPEAKER_01 54:18

So one of the main differences is that I was gonna say, I was gonna say that I'm not either. Well, I'd say one of their similarities is that I'm not either. But at some point in the future, I will be a CTO, definitely leaning more along the lines of a CTO versus a CIO at this point, uh, but we'll see as the opportunities kind of present themselves and where my interests kind of shift over time. Think about the CTO as the person responsible for owning the technology that is customer-facing. They are concerned with making sure that the product or service that the business is creating is, and that product or service can actually involve multiple different components from databases to applications and APIs to third-party uh APIs and systems. Those questions and considerations are all kind of led and guided by the CTO because they are focused on the technology that is external facing, versus the CIO owns the technology and the systems that are more internally facing. So instead of saying this is the database that we need for our operations to uh deliver our products or services, the CIO is going to say this is the database that we need in order to meet our finance requirements or the requirements from the finance team or the HR team or the customer service team or the security and risk team or the compliance team, whatever the team might be internally, they are listening to those stakeholders to say, all right, what technologies allow us to meet your business requirements more effectively, versus the CTO is trying to help drive growth for the business from a customer standpoint. So your CTO is asking, how do we win in the market? While your CIO is saying, how do we keep running the business effectively without any type of downtime from a you know regulatory standpoint? I'm not gonna say regulatory, but like governance. It could be even internal governance, but making sure that those internal business processes don't go down, even well, neither not the product nor the internal services should go down. But you can technically have your operational database that serves your customers be more available and more accurate than the back office systems and processes that are kind of there for tax reporting, accounting, uh compliance with you know HR or employment laws. Like those are two different systems that work parallelly, or they work in parallel, but they don't necessarily have to have the same functional requirements or meet the same functional requirements. So that's something to keep in mind. If you're in a product-led company, which most startups and SaaS companies are, you're really just trying to you're building your applications and your MVPs and your versions of your product or service so that you can grow the business and grow the customers or of that business. You're more than likely going to need and put your attention into the CTO because that CTO is going to make sure that everything we build is directly aligned with getting more customers or getting more usage out of our existing customers, which is all good for the business from a revenue standpoint. More mature organizations are going to look at the CIO to make sure that we can continue to operate even when we start moving into different domains. Even when we start dealing with customers outside of our initial uh environment, whether you're going from the US to the UK and Europe, or you know, start starting to process the data from other partners that bring you into some other type of regulatory requirement. That is where your CIO is going to shine and their skills are going to be the most impactful. But I will be a CIO or a CTO in the next 10 years. I just wanted to highlight that. That's one of my that's been one of my goals for the last at least five years. And I'm still learning and meeting CIOs and CTOs and really seeing more about what they do and what they actually deliver inside of the companies that they work in. But as I continue to grow and develop my skills, I'm very much aware that I don't always want to be an engineer. I want to understand and be very much involved in the strategic direction of the business. And as an individual contributor, as an engineer, you don't always have that same access. So that's why I'm shooting for chief executive uh leadership position. Because I will manage the teams that I work with.

SPEAKER_00 59:52

What are the benefits of pursuing a CISSP certification?

SPEAKER_01 59:56

So, first of all, the CISSP is not for everyone because there are a lot of prerequisites, including you have to have at least five years of hands-on professional experience in one of the eight domains that they are focusing on. And that's before you can even get the cert. And if you pass the test, you still cannot get the cert unless you have those years of experience. Additionally, the eight domains that it requires you to understand and know, and the depth that you need to understand for those eight domains is significant enough that you're not going to just be able to get that in just a few weeks. I'll take that back. It'll be very difficult to get that in a few weeks, although that, although you can't. But the main benefit for pursuing the cert is that when you start learning about the topics in those eight domains, you will start to understand the fundamentals of security and cybersecurity, and how that security is designed to work inside of all organizations, not just enterprises, not just startups who are less likely to have uh defined or well-defined processes for how they do security and compliance, i.e., anthropic releasing all of their code. Um but having that understanding of this is why we do MFA, having the understanding of this is why we need tight access controls on our buckets or our um APIs themselves. The topics that you learn about while studying the CISSP give you those or give you enough context to be able to say, oh, this is why we're doing this. Because I've mentioned it before. Most of the technologies that we use have cybersecurity regulations and features. But they have features that allow you to comply with all of the cybersecurity regulations that exist. You just have to be able and willing and knowledgeable enough to turn them on and use them in the most appropriate way. Most people don't have those skills or don't even uh have the awareness to say, let me turn this on. So that's the first thing. If you study the topics, you will at least have the awareness to say, this is when we need to turn this feature on or switch this button to this or do XYZ. You will have those types of answers ready and available in your mind. But it also teaches you to go beyond from an engineering perspective, just beyond what you know in code. Because the systems that we build are more than just the cloud and some type of programming language or framework that you fell in love with. You understand that when you have to operate in the real world, there are real world consequences to making a mistake. There are real world resources or resource limitations that you just have to be understanding about. You have to understand that you may not have infinite team members available to actually implement some of the controls that you need. So you need to be more creative about pulling in the right tools and systems so that you can still meet your requirements without having the same amount of budgets or team members available. So that helps you think beyond just, oh, I'm here to write code. No, you're not here to write code, you're here to solve a problem, and some of the most difficult problems to solve are tied up in regulatory requirements that are just a pain, a pain to comply with. Like, if you ever look at what you need to do to comply with PCI or GDPR uh laws, they suck. The things you have to do to actually do it, it sucks. And that's its own problem from a like uh part of the problem, and I'm on a little bit of a tangent, is that yes, these laws make it more the laws help protect consumers, but they make it almost more, they make it significantly more difficult for new entrants and and to actually compete inside of a market. So not only do you have to come up with product market fit from your CTO perspective, you have to have somebody on the ground that understands how to make sure we don't get fired because we're processing data in a less than legal, because it's at this point you're dealing with legal consequences if you're processing real personal information. So that becomes a hassle, and most engineers are are really not aware just how much their work actually contributes to the ability for this company to last and grow into different markets in their country or outside of their country. So definitely something to keep in mind uh as you develop and as you mature as an engineer and as a professional. And another benefit is that the CISSP is widely associated with management and leadership because of the very high standards that IC Squared helps to uh just uh create. So if you get this certification, it signals that you are not just someone who Is here to play, like just to hear the play around. You're not just here to write code and go home. You are here in a person who is capable and able to make a strategic decision that can help really affect and drive the long-term direction of the organization. And that's not something that most and that's not a distinction that most engineers get. Most engineers are considered to be like just code monkeys. Like we are there to click buttons and pull levers, right? You might think about the engineer as any other blue-collar job, right? Any any plumber or uh carpenter, we're for the most part looked at, you're just here to do a job to fix this thing. But they don't always call us into the conversation to say, should we be doing this? Does this make sense now? Is this in line with our policy, our mission, our goals? That's not always something that is in that is uh thought about when you think about an engineer. But having these types of certifications, whether from a CISSP standpoint or even a cloud cert, uh it allows you to be looked at as more of an architect versus just a worker on the front line. And there's nothing wrong with being a worker on the front line. I personally enjoy just coding and just cranking out systems and diagrams. I like that part. The process-heavy uh part of just doing the work. But there's enough tools available now with AI that the work can get done very easily. Now we really do need people that understand why we're doing this work, why it's important, and why it needs to be at the forefront of our mind, the strategy behind what's happening. So think about the CISSP not as a cert to learn, to build, or to have. It's really a cert that allows you to think like a security leader and make decisions that are best for the organization from a business standpoint. And there's nothing wrong with having that information and expertise available to you because become more valuable. And don't we all want to be more valuable? Get me?

SPEAKER_00 1:08:39

What are the benefits of what are three best practices to remember if you cause an issue in production?

SPEAKER_01 1:08:45

So your first job is not to understand the issue. Your first job is to make sure you stop the bleeding. You want to make sure that whatever the problem is that you caused can be stopped and that you can quickly resume normal operations. And that could be rolling back the deployment to the previous working version. That could be disabling the feature so that it no longer affects users and production. Or that could be rerouting the traffic. So again, you're no longer having people and processes that are using that uh defective change or that defective version of the workflow that you may have updated. So that's the first thing. Fix the problem and get things back to working the way they're supposed to work. Um you have to think about the production system as being a live system that actually puts you at risk of losing money, losing trust, or pretty much that, losing money or trust. And no one can afford to lose either when you're doing real business. So debug later, figure out how to get back to normal now. Uh, you should always have some type of way of logging the issues inside of your applications that are running. So if you made a change today and there are some problems, there should be logs that said and that complained that this is the problem that we're experiencing. Those logs should be stored. And so when you do have the system back online and everything is running the way it's supposed to run, then you can always go back to those logs to see and troubleshoot kind of what went wrong during that time. And so, again, this is always after you get business working the way it's supposed to work again. Another thing you need to do is notify any stakeholders. Notify your team members. You can notify your customers depending on how long you think the issue is going to last. If it's going to last even more than 15 minutes, or depending on the, I won't even say give it a time, like a hard time, depending on the amount of risk that is associated with the incorrect data that your system is providing, or if it's just not online. If this is one thing, if the if your system is just giving errors, and you can just you know users know, hey, this is just not working. That's one error that you can cause inside of production. But one of the scariest errors, the worst types of errors, is when it works, but it just is inaccurate because people are still trusting that data and operating as if it does work, which is not good. So during those situations, you have to make sure that people know that they should not be using the outputs of your system. And that might be you having to shut it down yourself, or that could be you sending out notifications to say, do not trust what you see here, or whatever it may be, however you word that uh message to the users. But figuring out the stakeholders that need to be updated and providing regular updates to them is also going to be key. You want to make sure that you're not hiding the problem. You don't want to just have a problem running and you know it's a problem, and someone has to come to you to see if something is running. As much as possible, be as direct and upfront about that because when you don't share that information is when people start to not trust you or your company or your team or whatever it is that you are providing to them. And then once you have gotten things back to normal and you have notified people in the organization that this thing is happening, then you figure out what went wrong. Now is your time to go through the logs. Now is your time to uh validate kind of what went wrong with that you didn't test or you didn't didn't prepare for. And this means going through those logs. This means uh reviewing the code changes that you made and seeing where what about the logic, what what in your logic missed that test case or that uh edge case that ended up causing issues today. This is your time to go through that. And if you're doing it with a team or if you're doing it on the behalf of someone else who made the actual change. This is not the time to blame or point fingers or say this is who did something wrong. This is the time to figure out what the problem was because it's not about focusing on the individual who made the mistake. It's about making sure that you can improve the system so that mistakes no longer affect the system or break the system. Right? You want to make sure that you are creating more resilient systems. And the only way to know if a system is resilient is to see if it breaks. So that's literally the only way. You don't know if the car will withstand a crash unless you go crash that car. Now, that don't mean you put real customers and users at risk to go crash the car or go try something, but you have to be aware and willing to break some of the things that you are building. And once they break, you figure out how to do better next time. Um, the very interesting part about this is I actually broke production this week for some of our security governance functions at the organization that I'm working with. And it wasn't for too long, and it wasn't significant enough that we could not fix it within a few minutes, but it was enough that it caused some downstream issues for some of the reporting that was being done. Good news, I was aware that it happened, right? I got the notification, I was able to see, okay, these downstream systems are starting to complain. And at first, it didn't just the system, the workflow that I released worked successfully. But the output that I had created looked just a bit different than what these downstream systems had expected. And so they started to break. So that's something you have to keep in mind. So you have to be able to monitor not just what you change, but also have monitoring in place of other systems that may be affected by the change that you made. Because again, my system never gave any errors, or the workflow that I updated didn't give the errors. Um like I said, I focused on rolling back my change, and rolling back for me was turning off the flow that I enabled and re-enabling the old flow that was in place with the working um updates, and then re-triggering the pipeline to move the data where it needs to get to, and then refreshing those downstream systems so they knew to start pointing at this new data, new being, the data that had gone through the process that worked, not the process that I broke. Right? So once that was done and everything was back online, I then was able to go through the logs and see, okay, this was the difference between my output and the original output. Now I knew what the cause was. Then it took me a few days to actually go through what the solution would be so that we could actually keep the benefits of the system that I or the enhancements that I added, as well as not breaking things downstream. Because I could have updated all of these downstream systems to work with the updated contract that my new enhancement had kind of created, but that would require me to make multiple changes to downstream systems, which when you're the person that also owns those systems, you don't want to do because that just makes more work for yourself. And I didn't, well, I didn't want to do it because it would have just made more work for myself. So I had to look at some alternatives. And luckily, the output wasn't the most important part, or the output that changed for those systems wasn't the most important part about the enhancements that I made. So I was able to actually keep both or update my automation to keep both of those, like the original output, as well as the secondary output that my enhancement was designed to create, which is really just a diff. I wanted to add a way to track changes to the data that we were tracking that we had been uh reporting on, because that we didn't have a way of doing that previously. So I was able to make those changes. They're currently running in the test environment again uh for this week. So I will check back in tomorrow and just monitor if it works the way it's supposed to work. But with fall things work as expected, I will be moving them back into production later on this week. But at least I know and have a way of fixing things when they break. Because that's all you need to do. You know, you build fast, you break fast, and you fix it. That's what you can do. All right, folks. So that's all we had for today and this week for questions. Uh quick, just uh reset before we jump out. I want to make sure that everyone understands that your anger and your negative emotions are not caused by other people. I recently started reading the book, Don't Believe Everything That You Think. And I'm a few chapters in, but I've already gotten more emphasis on the fact that there are sometimes elements and forces at work around us that are doing things. Those forces can be individuals, institutions, groups, or they can be forces like the moon, the sun. The healthiest way I've noticed to deal with those forces doing things or impacting and influencing things that can make my life more difficult is to just treat them as things that just happened. Imagine they're all coincidences, right? Don't assume that anyone in particular is to blame, even if someone is particular in particular, is to blame. Or someone did it, right? Because at some point, maybe the thing that made them do it was something else that was just a coincidence, right? So it's really not useful or helpful to you and I to get upset or get sad or feel negatively about something that, you know, we not only do we not have any control over, but at the end of the day, they might not even have had any control over it. So there's no point wasting cycles of your day upset because of inconveniences that you find yourself responding to. And so when I think about not allowing those coincidences and these factors that just forces to happen in life to derail my day or how I feel about my day or myself or anything else going on in my life, it in my opinion allows you to take back some of the power that you have given to these forces.

unknown 1:21:08

Right?

SPEAKER_01 1:21:08

When you put too much energy into what this or them or they did, and you say, This is why I'm feeling like this, or this is why I can't do this, or this made me mad when they did this, you've given them too much power. And it might be true, they might have really affected and hampered your ability to do something. Yes, but what are you gonna do about it? Because they already did it, they already did what they were gonna do. Now it's up to you to do what you gotta do. And if you over here complaining and upset because you got it hard now, you're gonna find yourself very upset when it only gets harder because now you done gave them your power and you you waiting on them to change when it's up to you to change what needs to be changed for you. So, my advice to you, if I'm giving any type of advice right now, is to be very mindful about where you shift the blame for the events and the activities that happen in your life. And be mindful about even if it if it's even worth giving blame for anything. Because most of the time, it's not. Most of the time, just be a it's enough to be aware that the situation is what it is. It's enough to look at reality the way it is and say this is what reality is. You don't have to be mad at anyone, you don't have to be mad at yourself, people next door, people that did it, quote unquote. Just be aware. That awareness is enough for you to, if you are mindful, to go solve the problem. And once you come up with a solution, it doesn't matter what reality was, because you have decided to make the outcome that you want, and you have the power to do that. So don't give nobody your power. Don't think that you have to wait for them to fix what they broke. Take what's broken and go do what you gotta do with it, and it's gonna turn out the way you need it to be. So hope what we've talked about this week has been helpful. I hope you can go into your current week with a spirit of strength and excitement and ready to build the next thing. Ready to build something wonderful and amazing for you, your people, and your community, and have fun doing it. So, with that being said, happy software Sundays. I hope you all are great. Stay great, stay blessed, and I will check you out later.