AI Nonproliferation, U.K Chips Sovereignty & When Bots Outnumber Humans | Software Sundays #32

This week on Software Sundays, KD explores three major shifts shaping the future of technology, society, and power.

We begin with Anthropic’s call for AI non-proliferation and what increased regulation could mean for innovation, competition, and the future of open-source AI. Then we examine the growing push for sovereign AI as governments invest in domestic chips, data centers, energy infrastructure, and national AI capabilities.

We also break down a milestone moment for the internet: bots now generating more traffic than humans. KD explains what this means for trust, influence, social media, AI agents, and the future of online interactions.

In this episode’s Q&A, we cover how to move quickly without making mistakes, budgeting a software engineering salary, the difference between the cloud and a home computer, what it really means to be agile, and why every engineer should be using GitHub.

We close with a reminder that sometimes growth requires changing environments and placing yourself where your goals have the best opportunity to thrive. 

CHAPTERS: 

00:00 Introduction to Software Sundays
02:32 The Call for AI Regulation
04:51 Sovereignty in AI Infrastructure
07:27 The Rise of Bots and AI Agents
09:39 The Importance of Trust in AI
12:23 Navigating the Technology Industry
14:51 Budgeting Your Software Engineering Salary
17:20 Understanding Cloud vs Home Computing
19:42 Agility in Development
22:30 The Role of GitHub in Development
25:01 Mindset for Growth

Build Learn Impact is on a mission to help our community create wealth and opportunity through technology.
 
Join BLI University - https://discord.gg/jpJHGq6kgS

Connect with Build Learn Impact: 
Instagram → https://www.instagram.com/build.learn.impact
Substack → https://buildlearnimpact.substack.com/

Connect with Kevin Dowdy: 
Instagram → https://www.instagram.com/mrkevindowdy
LinkedIn → https://www.linkedin.com/in/kevinldowdy/
YouTube → https://www.youtube.com/@kevinldowdy
Substack → https://substack.com/@kevinldowdy
GitHub → https://github.com/kevindowdy
 
#SoftwareSundays #AI #Anthropic #SovereignAI #ArtificialIntelligence #CloudComputing #GitHub #SoftwareEngineering #TechEducation #DigitalSovereignty #OpenSource #CareerGrowth #Leadership #BuildLearnImpact

Transcript

SPEAKER_00 0:00

What's going on, my people? Welcome to Software Sundays. I'm your host, KD, and on this series we have high-level conversations about technology and the impact that it has in our community. I want to make sure that you can walk away with the tools that you need in order to grow your income, become an owner, and help shape what happens next in the world. If this is your first time tuning in, you are in the right place. Thank you for being here. And if you've been rocking with us for a minute, it is great to have you back. Welcome back. That being said, quick disclaimer before we get started. Software Sundays is for informational purposes only and is not professional advice. The views expressed on my own are or those of individuals quoted. The topics discussed may or may not impact your specific situation. Please consult your own business, legal, or tax professionals before making any decisions based upon information found in this show. With that being said, the information is right and information is necessary. So let's jump in and get started with the news for this week. So Anthropic has made a call for the non-proliferation of AI, which is a very interesting stance to take, being one of the foremost leading labs developing and innovating in the AI space. They have decided that AI as a technology, as a platform, needs to be regulated more than it is currently being. And they are asking the government, asking companies, asking individuals to understand that even though the great developments and innovation is happening in the space, to understand that the technology is starting to develop faster than people are able to keep up with that change. And that change could be like their mythos model and how quickly it was able to uncover and identify securities, cybersecurity vulnerabilities inside of existing systems and the threat that that unleashes for financial institutions, utility companies, and other like critical infrastructure and even military use cases. So I can definitely understand there is a need for just being aware and mindful of the technology and the impact that it has, but it does seem interesting that they're asking, as a company who's already leading the space, they're seeming to now want to slow down innovation, which will only impact the people that would potentially compete with them more. It doesn't really affect them because they've at this point almost about the IPO worth nearly. I wonder if they're they were at nearly a trillion too. Their last valuation was at least 800 billion, if not 900 billion. But that those types of numbers and the advantages that they have in the space, any type of regulation, any type of stifling of growth and innovation is only going to affect newcomers, and it won't really affect such a powerful and well-developed, well-funded, well-established incumbent. And this is one of the issues with uh regulation because usually regulation doesn't impact the person who has the experience, who has the resources as much as the person who is looking to jump into the space. So there's a risk there. I would not like to see regulation of AI in the technology space turn into something that makes it more difficult for new people, new companies to establish themselves and break out inside of the market. And another thing to consider is the fact that these models, as they're developing, as they're reaching new capabilities, and people are seeing what they can do. One of the other risks to the proliferation of AI is that people start to be impacted in uh less than fair ways or in unequal ways, right? We see that there or there have been claims that some roles and some industries and some people are being more impacted by AI versus others. When you have an unequal and uneven distribution of those effects on the actual society and people inside of the society and the economy as a whole, that can be something that's jarring and more difficult for the overall economy, the overall society, and sometimes overall nations to actually recover from. So there's definitely some risk in AI just going and innovating at the speed that it's currently innovating in. But again, the there is potentially more risk to just allowing these at this point, maybe two big AI model, frontier model companies to just own everything and own the entire share of the market. Because if you think about the other foundational model providers, I think XAI, GROC will be an example. Gemini is also one. So Gemini, I would say, has a good chance to compete with Claude and even, or won't say Claude, but Anthropic and OpenAI's models. I don't think XAI or GROC were on that level, but even still, they were potentially competitors in the space. And then we do have some open source models that are not competing in terms of intelligence and capability, but they aren't competing in terms of accessibility, cost, and they can still get the work done for a lot of use cases. So there is some opportunity there, even Lama and those models. So we still want to have open source models. I think regulation could potentially make that more difficult to continue to develop those open source models and those competitors that competitors that don't exist inside of these big technology firms. And that's not okay. And some other news the UK government has decided to buy AI chips primarily from British tech firms. And this is another stage, another stake inside of sovereign AI and the infrastructure that is designed to power. Right? When we look at AI and the things, the inputs that are required to make AI work as a service, as part of all of the products that exist inside of your market. You need energy, you need access to abundant energy, what that energy comes from, or where that energy comes from. Some companies or some countries are a little, I would say on different sides on what that means, right? China is comfortable getting all of the power that they need from coal, or primarily from coal. Other countries are looking for more clean sources of energy to help power these uh data centers and their these uh power plants and their economy as a whole. Uh so you need energy, you need chips, right? So that means access to some of the most powerful chips available. So that could be NVIDIA's chips, that could be Cerebrus, their chips. They recently IPO'd with a new design, or I would say even a new like platform for how they're building AI chips, and then even potentially Google's TPUs and how those could be used to help train new models in the future. And I think Amazon has their own flavor of these high-level chips. So you need the chips, and then you need those chips inside and that energy accessible inside of these data centers. So that means access to land, uh networking, all of these inputs. But a lot of these inputs, when you get to the highest level, to the most critical level and the most critical components, uh, even thinking about uh the access to rare earth metal minerals, these things are primarily owned by very specific regions, by very specific countries. And that type of dependency from one country to another is not something that most governments are going to be comfortable with. So it makes sense that the UK and even Europe, uh, I mentioned a few weeks ago there were some investments being made into France to help get their data center developments going. Basically, these countries want to make sure that they are not solely dependent on China and the US for their AI, for their intelligence in the next wave of that found those foundational models. And this is a good thing. This is an attempt to make sure that the culture of that country is not at the whims and at the under the control of the countries that have access to the technology or that are providing that service. If you think about AI and what it can do for your community, for your country, for your cities, it can help accelerate the direction of wherever you guys are going because it more easily brings that information from like the historical information as well as pulling together different knowledge sources to help make stronger decisions in the real time, in real-time situations. But it also is something that can help shape and that will likely shape the minds of the people that are using it. If we're thinking about AI being used in education or AI being used in decision making for healthcare, as we get to seeing these applications deployed more diversely and in more industries, more sectors, because you don't want to have your financial institutions reliant on an external company's models in order to help service the country, the customers inside of your country. So that sovereignty is something we're gonna start seeing a lot more of. I think we already have been seeing a lot more conversation about it, but a lot of these investments, a lot of these decisions take years to actually manifest, right? You can't make a data center in a few weeks, although I think everyone wishes that they could. There's a lot of uh conversations that need to be had, there's a lot of capital that needs to be developed or pulled together before those uh before you can even break ground in a lot of these situations. So it's not a very quick decision, but it's something that we know it's incredibly important and it will continue to be important as we go into the future. And even thinking about uh the fact that the companies that exist inside of the UK that are, I'll say, leading or that are considered important to the AI revolution, there aren't too many companies in Europe. A lot of that innovation is again led by the US. So it makes sense that just as a country, you want to help invest into your own people. You want to help put some capital into hiring the people in your country to make these decisions or to stay in your country, right? A lot of companies will be like they'll start inside of wherever wherever their home country is, but when they start looking for more significant levels of capital and more more talented employees, they end up having to migrate their company and their business to different countries just because that's where the opportunity is. Think about most of the VC capital and where that comes from, and like globally, a lot of that comes from the US, a lot of that comes from out of these Silicon Valley firms, and you know, there are some hubs where you can get access to the capital and the funding that you need, but also the talent. That's not always decentralized, that will sometimes and oftentimes be available in some very specific places. And then some other news, bots have now passed human traffic in terms of the amount of bots versus humans surfing the web, which is incredibly interesting. And it really speaks to where we're going as a society. If you think about how long it took for the amount of the human population that we have today to actually reach the internet, the internet started at least 30 years ago now, or I say the internet started, the internet became accessible about 30 years ago. And it took about these 30 years, I would say even 20 years, really COVID is what it shifted and accelerated a lot more, but it took about 20 years before the internet became more mainstream globally, before more people started having access to in the internet, high bandwidth connections and even smartphones that they could actually surf the web, access these services more easily. We're seeing now, as long as it took for the this amount of human users to get on the web, we're seeing in less than three years, AI agents, right, these assistants for humans now surpassing the amount or surpassing the amount in terms of actual requests, but also the speed. It didn't take nearly as long for these bots to start really proliferating and growing their presence on the internet. And we're only going to see that acceleration continue. We're only going to see more bots doing things on the internet for humans and on behalf of humans. The interesting part is who are these humans that they're working for, right? All software, I mention it all the time, software is just a tool to advance the goals of the people who develop them. When we're looking at bots that are operating on the internet, that are operating in a space and an environment that also can touch other humans, if you think about social media. If you think about social media is like a major aspect, but if you think about the applications that are going to be accessible through the internet, if you think IoT, if you think vehicles, when we get to that point, a lot of the services and products that we rely on and the things that we will become incredibly reliant on are going to be accessible through the internet. If you have agents and bots also being able to access those resources through the internet, that means that there's a potential for a significant amount of control to be exerted by these bots onto the resources that we consider important. And that's not something I feel like people have thought a lot about. And then even from a social media aspect, if you think about the impact that social media has on people, on teenagers, we've seen a bunch of recent lawsuits from several countries, several states inside of the US, and even outside of the US, basically uh won't say waging war, but having very stark disagreements with big tech and social media platforms on how and what is fair for the usage of their platforms. What age is it appropriate for a child to be accessing YouTube, Instagram, and these platforms? What should what controls should be in place when they're accessing them? Like these conversations are important because the minds of our people are being shaped by these platforms and the technology. The stories that you see, the comments that you have access to, the people that you get connected to. You can get connected to somebody that's in your neighborhood, but you can also connect with someone from halfway around the world and see what they're into, see what they're building, see what they're working on. And that can have positive and negative effects, right? You can have a positive effect when you're talking about positive knowledge being shared. When we're talking about engineering, when we're talking about philosophy that is about human development, uh, maybe even, you know, education, how do you educate yourself, finances, like that is all great. But you can also have some really negative things. You can have a drama being shared and widespread on the internet, you can have conflict being something that's shared, especially when we're talking about policies and and these political races, and even for some like certain sports entertainment and that type of disagreement that can be that can grow on the internet. Let's say you have those same people accessing the internet, but now instead of having to deal with only humans who are trying to impact them and who are trying to influence them, now they're dealing with AI agents who are also attempting to interact with them and all not even attempting, are also interacting with them, also producing new information and producing content that can help shape their mind and drive their decision making. And then the most difficult or most challenging part about that is that you might have a hundred AI agents that are all developed by one single person or one single organization, all now impacting a million users at a time. So the amount of influence that very small teams can have across the minds of very large groups is going to be something that we see especially as more of these agents go online. It's also very important to understand that with the rise of these bots on the internet, it's going to be incredibly important to understand what is true and what's not. That's not something I think that people are totally familiar and willing to accept at this moment because again, we we've already gotten to the point where people don't exactly know what's real online. We've already gotten to the point where people are having really strong emotional reactions to things that they consider to be AI created and things that they think were AI generated. And it's not totally clear which is which sometimes. So the major thing that I really feel like I want to just drive home for a moment is that trust in the AI supply chain is really becoming more valuable. It's becoming more valuable from a hardware infrastructure space. We're thinking about countries taking a firmer grants grasp on their AI infrastructure from energy to trips, but it's also becoming incredibly important to understand that AI supply chain is starting to impact actual people on the internet and actual minds because these bots are becoming more widespread and use. So if you want to go deeper into any of these topics that we discussed, uh please join BLI University. Every week we're having high-level conversations about these challenges and the changes that are happening. And we're discussing in rooms with other builders how to actually take control of the opportunity that these changes create, but also how to drive some of that innovation inside of your own community and otherwise. So definitely join today, and we look forward to discussing more with you in the future. Let's jump into our QA section for this week. Again, the QA is primarily designed to make sure that you have all of the information possible in order to help enter the technology industry confidently and with everything you need to really hit the ground running. So, first question how do you move quickly without making mistakes? So, this is incredibly important right now. I mentioned it previously that AI is starting to accelerate a lot of the development, right? It's starting to increase the expectations that teams have for individual contributors and developers. But it's incredibly important to emphasize that you don't want just speed. Because if you're just going for speed, there is a high likelihood and high potential for mistakes. So we have to understand that as developers, how do we move quickly without sacrificing delivery quality or introducing errors that will more negatively impact our teams in the future or our users? So one of the major strategies I use when I want to move quickly without making mistakes is to rely on checklists. And you can think of a checklist as a series of steps that you can use in order to accomplish some goal. And you have a start all the way to the end. And these checklists, some other words, uh names for them could be SOPs or standard operating procedures and run books, guidebooks, like basically something that a professional or a member of your team can rely on when they're in a high pressure situation or when they're in a situation where they have to just move. But if you think about checklists and procedures and how important they are, think about pilots and how they rely on pre-flight checklists before they ever take off. They want to make sure that when they are operating this very useful but dangerous uh machine, this dangerous vehicle, that they have done everything in their power to ensure the safety of the people that they are responsible for once they take off and up until they land. Surgeons, they consult a checklist before they start start any operating days. And that helps to save lives. So when you're trying to think about how to create a plan to complete any task quickly and as safely as possible, you have to spend as much time as possible up front developing this checklist. Spend as much time as possible after you develop that checklist to review the checklist to make sure that everything in that makes sense, the order of operations makes sense, and that everything is included, that there were no steps that are skipped. Because any steps that are skipped, that anytime you're relying on the memory of a person in those high pressure, high pressure scenarios, there's a very high likelihood that a mistake can be made. And mistakes inside of engineering, mistakes inside of healthcare, mistakes inside of uh flights can be incredibly dangerous and negatively impact human lives. Right. So we we want to avoid that as much as possible. As an engineer, you want to make sure that you understand what the process is. And then anytime you have that checklist, you can look at the checklist and then Go from there, decide what we can automate in here. What can we remove the human, not necessarily the human element, but what can we remove the human risk of mistakes inside of this system? But you can only do that after you've documented it, after you've written down that checklist and that process to understand, hey, this is what we need a human in the loop to do. We need a human's decision and accountable on. And these are the things that we can actually give to some software to manage and make sure that there are no mistakes here to double check, right? That's something that you can only look at once you assess an active checklist. So, and another great thing about checklists is that it can allow you from a practice standpoint to actually go through more reps. When you're going through a checklist and you know that, hey, this is what I need to do, step one, two, three, four, and so on. You can actually build more confidence in yourself and your abilities because you have repetition inside of these steps and inside of these operations. It can help you understand and perfect the right combination of steps and techniques needed for you to actually see measurable gains and measurable performance increases inside of your, you know, whatever it is that you do, whether you are a QA tester, whether you are a SRE or site reliability engineer, or whether you're a standard suite, right? If you're just building and you're going through your SDLC process, having that defined procedure and that defined checklist in front of you before you make any type of commit, before you release any of your code into production. All of that is going to help make you a better developer over time because you know that you have the inform the instructions that you need, the steps, and you know you've gone through those steps in the most reasonable capacity. How should I budget my software engineering salary? So I have found that the technology industry is going to give you some of the fastest and most lucrative opportunities compared to most other industries, most other roles. But with that great power comes very great responsibility. You have to understand that the income that you're getting is one, it's because the work that you're doing is incredibly important. But you also have to understand that the income that you're getting is an opportunity for you to help change your life and the lives of those people in those missions that you care about. And an incredibly important decision that everyone needs to make, no matter what your income level is, no matter what you do for work, is to make an intelligent budget. And a budget is not just a plan for how you're gonna not spend a lot of money. Your budget is how you're going to allocate the resources that you have available before you actually get those resources. You never want to decide how to land the plane after you're already up in the air. You want to have all of that already planned and all of that already prepared before you see and before you need it, right? And when I say budget, I'm saying understanding, you know, how much money you're going to allocate this much for your housing, how much you're going to allocate for transportation, uh, your medical expenses if you have those student loans, and that's like your expenses. But you also need to have a plan for how you're going to invest into your future self. So that could be setting up your retirement account and budgeting something amount, some amount there every month. Budgeting for your emergency fund, which is incredibly important, right? There are people that are still looking for jobs months later, months later after being laid off. If you haven't budgeted for that type of emergency, budgeted for not having the income that you needed, you're going to be challenging yourself in order to kind of make ends meet in the meantime. And that's not a challenge that, you know, you don't want to be stressed out while looking for a job. You want to be able to do that confidently, do that with a little bit of patience and peace in yourself. But having that budget and having that plan to know that, hey, I need to have a safety nest for myself and that little nest egg for myself to make sure that I'm not inside of an unstable position later on. That's going to be incredibly important. Even just understanding how much you may want to donate, how much you're going to give to your community. That's something that you want to plan for. You don't want to just say yes or say no to every ask or every request that comes in. You want to be able to confidently give to the people and give to the missions and the organizations that are important to you. And the only way to do that is to plan it, write it down. And that plan could look like an Excel sheet. That plan could look like a piece of paper with some notes on how you want to just donate. Or that could be some other tool or app that you just rely on. It really doesn't matter as long as you have a consistent way of doing this. And this is incredibly important for high earners because a significantly disproportionate amount of high earners, people earning over $100,000 a year, are living paycheck to paycheck, which would seem weird, right? The more money you have, the more likely it would be that you can make all of your ends meet and save money. But in reality, that's not the case. Most of the time, when people make large amounts of money, they spend just as much money on things that are not probably in their best interest over the long term. And especially when you're seeing uh significant uh you know salary raises. If you're not budgeting, if you're not planning how you're gonna allocate that new salary, if you're not understanding how much you were spending from your last paycheck, every new dollar you make is going to get caught up in the same system, the same habits that you already have been using. So that budget, that plan will help make you feel some of those salary increases a little bit more than you would if you're just spending money with no plan and no system in place. Um when I budget for myself, I have a monthly don't I say the budgeting for me is a I won't say it's complicated, but it did take some months and years to protect to perfect. My spending, I spend normally for most things. I'm not really an excessive spender, so I don't have to really put significant upper limits on how I'm spending. I buy my groceries, my transportation, like I have to get to work, I have to go where I'm going, right? I don't really go out too often to restaurants, but I do also have like a limit on how often I'm going to get Uber Eats, things like that. Right. I'm not eating out and getting Uber Eats every day. I'm buying groceries and cooking so I can have leftovers. I am putting a little bit of money aside for my investment account. And I do that using different tools. I have a tool I use called Credit Karma, which is an app that really tracks all of your spending, but it also tracks all of your account balances and even your like it helps you track your debt and your net worth. I use that mostly for the expense tracking so I can know how much I spent in a particular category and I can categorize my transactions over a course of a month. And then every month at the beginning of the month or technically at the end of the month, right? I actually look back at all of the transactions from the last month and say, all right, and I'll say I'll record what I actually spent in that particular category so I can keep track of where my money is going over time and over months. Credit Karma only saves the most recent six months of data. I think in five years is going to be incredibly important and helpful for me to know how I spent my money over the last five years and what effects that actually has in my life five years from now. But I also add on another thing in there. I track my inside of the Excel tracker that I use for the monthly reviews. I also track how much I'm going to allocate or how much I'm going to invest for the next month. So I am calculating what my cash flow was for that month. So I know what was actually left over and deciding from that excess, from that leftover, how am I going to donate? How am I going to invest into my savings, into my different investment vehicles, right? Those investments are coming from knowing how much I have left over. So there's a few steps in there. And part of that is also with me, I can use a credit card to make sure all of my expenses are on one place versus having a bunch of different accounts with different expenses. So definitely at some point when you're getting, maybe you might spend that first check, how you wanted to spend it with a little more emotion. But at some point, become aware of your spending and how that will affect your life and your opportunities over the future. What is the difference between the cloud and a home computer? So when you think of a home computer in a professional standpoint, think of on-prem. Think about a computer that you have full access to from the physical perspective, all up until the applications running on that piece of hardware. Your home computer is going to be something that you can touch, that you can see, that you can listen to, like, right? That's going to be completely under your care and your responsibility. That means the networking for that computer, so making sure your Wi-Fi is working, right? Making sure, and it could be Wi-Fi or even if you're using Ethernet cables to have a hardwired connection. That could be making sure the operating system is up to date, right? Patching and making sure that the latest version is being installed at all times. That could be physical security, making sure that no one has access to the computer. No one can just walk in and walk out with the things that belong to you. That physical security is something that a home computer or on-prem computer is going to be at the responsibility of the owner. Versus when you go into the cloud, you are delegating a lot of that physical responsibility to that cloud service provider, to that vendor. They're going to be responsible for the physical security. They're going to be responsible for the power and making sure that those computers are kept running, right? With either batteries or actual, you know, being plugged in at all times. They're going to be responsible for making sure the operating system is always up to date and always having those patches. That gives you less responsibility and less operational complexity in your day-to-day. You don't have to deal with all of those pieces. And you can rely on a company that has nearly perfected the responsibilities, right? They know exactly how to manage access control in a physical environment. They know exactly how to migrate or up and bump the version of an operating system without causing any or significant outages inside of the applications running on those systems and running on that hardware. They know how to implement redundant networking and redundant power supply, right? You don't have to do that yourself. You can rely on their expertise and their teams to do that for yourself. So all you have to worry about is how do I run my application on this computer that they have provisioned and made available to me. And that benefit allows you to focus more on the value that, if you're thinking about an enterprise or a business, the business the value that your team can provide to your user, that only you can provide. You don't have to worry about those extra things, those extra steps, because they're handled for you by someone else, by that third party. Another benefit of the cloud is that you no longer have to come up with the upfront capital requirements. Back in the 1990s, that sounded like it was that long ago, but back in the 90s or the 80s, if you wanted to run a system that relied on computers, you had to buy and spend maybe thousands of dollars or hundreds of thousands of dollars and millions of dollars in order to hire people, in order to uh buy the computers, buy the servers, buy the networking racks, buy all of these this equipment. Now you can get started with like $100 a month to rent the same amount of computer power, the same amount of networking power and get started in a day, get started immediately without having to go through all of that upfront capex. So that's been why a lot of these companies have been able to grow and start making, you know, I would say more progress and be able to innovate without having a lot of capital up front. You can really rely on their infrastructure and just build and focus on building. What does it mean to be agile? So, in my opinion, agility is not just about speed, it's about making sure you're doing things in a beneficial way. It's about testing your workflow and testing the products that you're building in your development deliverables, measuring the results of that development, and then learning quickly so that you can apply those learnings to help make the next iteration even better. So you need, in order to be agile, you need to have set up feedback loops, you need to have a defined process that you can adjust progressively as things change. So you should know where you're starting from and what the output is going to be, and then know how to measure that output to know how we change our inputs to get a better output in the future. So for me, in my work, that means I am, you know, having defined tests. Like I know exactly how a piece of software, whether it's an automation or some script or some CLI tool, is going to work. And I know exactly what use case it's going to be useful in. So I define those tests very early. Like this is what you need to do. And if you can't do that, it's wrong. Right? When I'm when I am recruiting an AI assistant or even some other team member, some human team member to help me provide the service or create the product, I'm comparing the output of our current process against the final deliverable standards, right? So if the current process is giving me a standard or a product that is just below my standards, then I know the process is not working the way it needs to work. So I know I need to adjust either a step in there, either to add a step, to remove a step, or just replace a step to make sure that that final output more directly aligns with what we're looking for, whatever that goal is. And a lot of that requires you to have a mindset that you're not looking for perfection the first time. You're looking to iterate, right? You're looking to make measurable gains, you're looking to learn quickly. That means you out and you want to move fast, right? You want to try things quickly, but you also want to have structured breaks inside of your process so that you can actually test things appropriately, so that you can pause and reassess when you see things are not working the way that it's supposed to work. If you're thinking about agility as just a way for you to move quickly, if you think that agility just means you can deliver something out quickly without testing or verifying that it works, I think you're going to have some serious problems in the future, especially when a lot of people get things out quickly without ever documenting what they've done. So they can't actually reproduce those same results. So that type of workflow and that type of standard or structure is not really agile. That's really more uh, I would say chaotic when you're just building things and you get something out the door and you don't really know how to ever reproduce that. That means every deliverable you get from now on, there's a high likelihood that it won't actually meet that final output, that final quality that you had hit that first time, or you're gonna have very inconsistent results. And inconsistency is not a positive characteristic of anything, not people, not companies, not products or services. We want at least to know that the thing that we're getting today is the same as the thing we got yesterday if we are paying the same amount, if we are you know expecting the same thing. And that agility again comes from having that checklist, having that process and that procedure in place, documented and auditable, so that you can learn from it over time. Why should I be using GitHub? So, for builders, GitHub is more than just a place for us to store code. GitHub can be used as an IDE, it can be used as a place to collaborate with other developers, showcase your portfolio, and help manage many code adjacent workflows. If you're using GitHub Actions to deploy or to automate your CI CD process, if you're using the issues feature to keep track of potential enhancements to your project or potential uh bugs that it might have, this is why you want to use GitHub. And it's one of the de facto standards for source code management inside of the industry. If you're thinking about GitHub or even GitLab, these tools are built off of Git. Git is the actual source control tool that allows you to, you know, make a commit, to roll back a change, to merge vers different versions of code developed by different people, right? A lot of that is coming from the Git tool, but GitHub or GitLab just builds on top of that just to give you a better user experience, to give you a little bit more functionality that you wouldn't usually get from that simple Git tool. It's incredibly important to be familiar with GitHub because if you're going into any technology adjacent role, you're likely going to have some exposure to Git or Git repositories, especially if you're a developer, if you're in some type of security or cloud role, you want to be familiar with something called GitOps. And it's the concept of having all of our technology and our software being defined through and being auditable through some type of Git process, some branching strategy. And that is all going to rely on Git or GitHub, GitLab, whatever tool you use. Azure DevOps is also another tool in the space, but pretty much the standard is in the technology industry that you have a GitHub repository. You have a GitHub profile, and that you are sharing the things that you build, that you are familiar with creating a PR or a pull request, that you are familiar with contributing to a repository, that you are familiar with, you know, checking out a branch, right? Cloning a repository and being able to create a new branch and updating some updating some code on that branch and being able to push it back out to that source code repository. If you're not familiar with that, then you are not meeting some of the like bare minimum standards that are going to be required for a developer for an engineer, and that's not where you want to be. So definitely make sure you are familiar with GitHub and how to use it, right? You look into open source projects, look into how other people are writing their code. That's one of the benefits of GitHub too, right? Not only can you showcase your code, but you can also get you know firsthand access to some of the most masterfully created projects in the world, right? Kubernetes is an open source project. Terraform is an open source project. These are enterprise grade code bases that you can actually see what the commits look like. You can see what the code looks like, how it's organized, what comments are in there, how people are naming variables and functions. You can see what the issues are and how those issues translate to pull requests. You can really learn in open from these people that are really the OG developers and very experienced developers in our space. And that learning is the value of that learning is immeasurable. You can actually really grow as a developer by just exploring GitHub and the things that are available there. And so that's all we have for our QA for today. If you have any additional questions on any of these topics, whether it's how to become a better developer, what tools you need as a developer to get started in the field, what should you be doing when you are in your first role and how to improve in your team dynamics or improve your output and quality, definitely drop them into the captions, caption, into the comments, let me know what you're thinking. Uh, we're gonna jump into our mindset session very quickly. So, my tip for this week is that getting all you need in life is probably going to require you to make a different push in a different direction that you may not currently be making. And sometimes the problem is not going to be you. Sometimes the problem is the environment that you're in. Sometimes the environment that you find yourself in is clicking properly with the goals that you have for yourself, and that will require you to go, or I guess if you if you want to reach that next level for yourself, it will require you to go somewhere else so that you can become someone different in that other place. And I'm not saying totally to change who you are, but sometimes the environment that you're in expects you to be a certain way, and the person that you want to become is an entirely different person altogether. So going to someone to a place where no one knows you, where there are no expectations for you to be that old person could allow you to hit a new phase, to hit a new destination that you really want, but that you're really not able to hit right now. And I know it can often be scary to leave, right? It's difficult to leave a place that you know you're comfortable with, or that you're more comfortable with your just current discomfort than you imagine yourself to be comfortable with the unknown discomfort, right? The known versus unknown, that risk. But even if it's difficult, even if it's scary, sometimes again, it's going to be the best thing for you. Sometimes that may be all you need in order to hit the next milestone that you have for yourself. And sometimes it's all you need in order to really just drive that next wave of growth for you and where you want to be in the future. So take if you're finding yourself, you know, not in a place that you want to be, if you're finding yourself not comfortable with where you are, really look and explore what places are more conducive to the person you want to be and to the plans that you have, right? I I've heard uh philosophies and thoughts about there are different cities that are better for different industries, depending on what you want to do, right? If you want to be a pro in tech, going to Silicon Valley is where you want to be. If you want to really immerse yourself inside of the tech ecosystem, if you want to be a great politician going to DC, going to the capital of your country or your city is going to be where you can get the most impact because you can learn from the people that have been doing it at the highest level. If you want to be great in financials, in the financial services industry, you go to New York or UK or Singapore because that's where the capital markets are centralizing. That's where the bankers go, where the insurance brokers go, that's where the money is going to reside. And so you have to go where the not only the opportunity is, but where it allows you to stretch the most you can inside of that area that you really want to stretch and grow in. So, you know, challenge yourself to do that and make the most of that opportunity. And that's all we have for this week. Uh enjoy your week. Happy Sunday. Be great, be safe, and continue to build, continue to learn, and continue to make great positive impacts inside of your life and your community. And I will see you in the next one. Peace out.