DeepSeek vs Frontier AI, Anthropic Power Moves & Why Developers Still Win

This week on Software Sundays, KD breaks down the shifting AI landscape and what it actually means for builders, engineers, and the future of opportunity.

We start with DeepSeek’s latest model and why it’s not competing with frontier models like OpenAI, Claude, or Gemini — but still winning in a completely different way. KD explains how open-source, low-cost models are changing distribution, accessibility, and how developers can experiment without burning through tokens.

Then we get into Anthropic’s Mythos model and the tension between innovation and national security. The U.S. Treasury wants access to one of the most powerful vulnerability-detection systems, while parts of the government still treat it as a supply chain risk. KD unpacks why limiting access to the best tools could actually increase risk.

We also cover the massive investments flowing into Anthropic from Google and Amazon, what “circular investment” really means, and how hyperscalers are positioning themselves to dominate the next phase of AI through infrastructure, not just applications.

In this episode’s Q&A, we cover how to take care of your health as a software engineer, the real difference between threads and processes, how to run effective meetings, how many environments your application should have, and what it truly means to be competitive in today’s tech market.

We close with a mindset reset on self-talk, mental health awareness, and the importance of building yourself while you build your career.

Timestamps:
00:00 - Welcome and disclaimer
02:10 - DeepSeek vs frontier models and why cost matters
10:45 - Distillation and why open-source models lag (and still win)
18:20 - Anthropic Mythos, cybersecurity, and government access
27:40 - AI risk: attackers vs defenders imbalance
34:15 - Google & Amazon invest billions into Anthropic
42:05 - Circular investments and AI infrastructure strategy
49:30 - Why developers benefit from cheaper tokens
25:10 - Q&A: Engineer health and avoiding burnout
28:15 - Threads vs processes explained simply
33:40 - How to run effective meetings
39:20 - How many environments you actually need
44:30 - What it means to be competitive in tech
50:10 - Mindset reset: self-talk and mental health
55:00 - Announcements and community updates

#SoftwareSundays #AI #DeepSeek #Anthropic #CyberSecurity #SoftwareEngineering #TechCareers #Leadership #AIInfrastructure #BuildLearnImpact #Developers #Startups

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_03 0:01

Welcome to Software Sundays Builders. This is a space where we have high-level conversations around technology and the impact that it has in our community. We make sure that you can walk away with tools that allow you to become an owner, grow your income, and shape what happens next in this digital society. If this is your first time tuning in, thank you, you are in the right place. And if you've been rocking with us for a minute, it is great to have you back. Thanks for returning. So before we get started, quick disclaimer: Software Sundays is for informational purposes only. This show is not professional advice. The views expressed are my own or those of individuals quoted. The topics discussed may or may not impact your specific situation. So if you are looking for information on your situation, please consult your own legal, business, or tax advisors before making any decisions based upon information you found in this show. With that being said, this is great knowledge. It's good for you. You can grow with it, and welcome to share your own knowledge as we go farther. We're gonna jump into the news. So DeepSeek's long-awaited new model fails to compete with US frontier models in AI. The major thing I wanted to share with this story is the fact that, yes, the models from DeepSeek are not competitive. They're not, well not, I won't say they're not competitive. They're not competing in terms of reasoning and complex task management the same way a model from OpenAI or Anthropic will. They're not doing better than Gemini or Claude in those types of tasks. But the major thing to remember is that they're not designed to. Two, it was to open source and make that capability more widespread and available. I've mentioned it before. The model that China and even Meta have gone for with developing their model is that they want distribution. They want it to be as easy as possible for anyone to get started using their models. When you create a model that is cheap to run and cheap to train for a number of reasons, I'll get into that in a moment, it becomes much more accessible to everyone around the world, no matter what type of resources that they have available. So that's really where they're winning at. They're winning, and the their goal is to win on distribution of these models and people using the model. So that means for a builder like you and I, a developer, we can actually pull down these models, get access to all of the weights, and run them locally on whatever hardware we have available. Whether that's your local laptop machine or that is some home server that you're running. Or you could even, if you choose to, set up some cloud environment and get deep seat v4 models. I don't know, the v4 is the newest model, but uh whichever model that you choose to run, you can run it on that hardware without any issues. Very easy to get started with. So this is great because you get to play around with the capabilities available from the model while avoiding some of the heavy costs of you know playing around with AI. If you've ran any type of system using AI in that intelligence layer, you realize that those tokens cost, I won't say a significant amount, but they can add up over time, especially if you're doing a lot of testing and you're evaluating the effectiveness of your model and your changes. You're going to have to go through and burn a lot of tokens just to understand what your model is doing, what it's capable of, and how far you left you need to go. So this can help make it easier to get a product or a system up and running without having to go through that high initial cost. So that's a great thing. That's for everyone, right? So I would encourage everyone who is interested in figuring out how do I run a model, how do I train an agency system, and you don't have the like the funding to go into it uh straight, then play around. Figure out how to run Deep Seek models or any other open source model and start using those tools in your system and just see what happens. One of the interesting parts that I just wanted to highlight about why these models are so much cheaper is because they have not been trained on the same large data set that these larger frontier models have been trained on. They've been distilled or they've been trained using a process called distillation where the smaller language model will be trained using a larger language model. So a lot of these companies have just used Chat GPT or Claude or Gemini in the background to actually accelerate and evaluate their models or these deep seek smaller models without having to go through the process of curating that data set themselves, going through the long training time. So it's almost like a derivative of these much smarter models. So that's why we see a lag in terms of the effectiveness or the competitiveness of these open source models, at least a few months behind, because you're almost trying to train someone to you're trying to train someone to do or follow some steps, but you're training them from someone else who's still learning. So it's not like you're training them on the real world, you're training them on based on someone else who only knows a portion of the world. So you're never gonna really beat the trainer, you're not gonna get past the teacher because the teacher is the limit that you're you kind of set for yourself. So something to keep in mind with just knowing kind of what the limitations are with these models and what you can do with them. So again, I encourage you to build some pretty cool things with it and just see how far to take you before you actually have to go invest into any type of Claude or other like more cloud-hosted models. The point is you should also understand how to build systems that can easily swap out that foundational model. Whatever the model is, whether it's Gemini or uh Claude or Deep Seek or whatever the model is, you should be able to mix and match these models and be able to evaluate how effective a particular model is for your specific task. In other news, the US Treasury is seeking access to Anthropic's Mythos model to help them find vulnerabilities. This was a funny story to me because we are aware that Anthropic has been categorized by the Pentagon and multiple departments in the government as a supply chain risk. That just means that they have been considered a national security risk if you use them inside of the system. So most contractors and government organizations have been uh encouraged to move away from using anthropic models for any of their missions, workloads, or processes. So that being the case, and at the same time, understanding that they have one of the best models, or they have been reported to have one of the most effective models at finding vulnerabilities, this new Mythos model. So it's like you are almost encouraging people not to use the best tools and resources available, or at least the government is encouraging their employees and their groups not to use the best technology available, which is dangerous and not great for the overall development and security of these systems, right? Because if you have a tool that you know is effective and capable at finding vulnerabilities, and you could use it to identify some of the vulnerabilities on your system, and you choose not to use that tool, then you are doing yourself a disservice at that point. But the current uh I believe he is the CIO or um one of the leaders inside of US Treasury has like understood that you know we're not trying to keep that limitation on us. So he's looking for access. But one of the things with this new model that Anthropic uh is or has released or has created is that they have not released it to everyone. Early access was only granted to a select group of companies. It was um like CrowdStrike, Google, Linux Foundation, uh, which is a nonprofit open source uh organization that you know very pretty, if you're not familiar, they're pretty uh popular in the software development community. So they're one of the there's a very select list and group that has access. So and the it doesn't, I didn't see any government institutions on that list. So it was very interesting. So I don't know if or even when they would get access to it. And from a financial industry standpoint, I think only uh Chase, JP Morgan and Chase did get access. And I think over time, uh companies like Bank of America, maybe a few other financial institutions, uh, have gotten access also. So it's something that they're slowly rolling it out to give these institutions and these organizations time to actually run the scans against their system so that they can determine kind of what their what vulnerabilities they have and assess the threat and risk potential for when those advanced models actually become more generally available. And I would also highlight that it doesn't even matter if the Mythos model becomes generally available, the existing models that exist, the existing models that exist, right? Uh the models that are already released, they are already good enough to launch a sophisticated attack. We were seeing nearly fully automated attacks using Claude back in December or November, and there have been better releases of Gemini, of OpenAI, or ChatGPT, excuse me. Those models have continued to get better over the last couple of months. So the risk has been here, it's been talked about for a few years. I remember even back in 2023, uh going to some of the like the cybersecurity conferences and hearing people talk about the risk with AI is not the fact that AI just becomes so sophisticated. It's the fact that because you have more of these tools available, the barrier of entry to getting more attacks going has decreased. So you have to expect more attacks more frequently, and it's just much more work for usually overworked so c's to actually deal with. So this is something to keep in mind from a like a I guess public-private partnership perspective, because any type of tension between an innovative company and the institutions, the governments that manage critical infrastructure is going to be a problem from my perspective. It is dangerous if the best solutions on the market are not accessible to the people that may need them the most. I can't imagine a organizational industry such as the government or the treasury or uh like our public utilities, like I can't imagine them not needing access to the best tools to manage their cybersecurity. So having limitations in place from a national level that say we should not use these tools, even though they are available, is strange to me. And it kind of represents a greater risk than we probably need to be allowing us like ourselves to have. And that means attack. So when you have that type of dynamic where the bad guys are getting better tools and doing more, and the good guys are kind of blocked, holding their hands or sitting on their thumbs, then nothing gets fixed and the risk just increases. So I would suggest that we not choose to avoid using AI systems, even if we don't choose to trust those systems. And I can understand that's a challenge for anyone inside of the government. Like, how do we trust something or how do we use something we don't trust? And it's hard to say just have a leap of faith, but we kind of have to at least understand the systems that are available because they may work. And in some other news, Google has committed to investing 40 billion into anthropic, and that investment is not going to happen all at once. The initial investment is around 10 billion, and then as Anthropic meets other benchmarks and milestones, the rest of that funding will become available. Uh and even a few days ago, Amazon also agreed to invest $25 billion into Anthropic with similar conditions. But all of this is leading to the fact that Anthropic's valuation is currently growing faster than open AIs. I think it might actually have exceeded open AIs at this current point in time. Uh, and we'll keep an eye on that. But they're becoming a very valuable company, uh, and it's very exciting to watch. Uh one of the things that I'm seeing though from this investment, and it's kind of been happening, it's a pattern that I've seen, is that there's a lot of circular investment. And I know we've heard a lot of stories about it over the last couple of years, like now it's like it's a little bit of a risk when you look at all of those diagrams, like, oh, this company investing in this company, that's a customer of that company. It's like, oh, how does how long does this last? Is this a bubble and all these questions? I don't know. I'm just saying I can see the fact that Google investing 10 billion into Anthropic for Anthropic to spend that 10 billion in Google using their cloud uh computing systems, and same with Amazon, like right, like the provider, supplier is providing an investment to their customer so their customer can actually pay for their services. That definitely is circular. There's a lot of assumptions you have to make for that to work. The good part is that the tools and services that Anthropic actually provides are becoming more valuable, right? They have increased their revenue over the last two years of their operations. They have become more popular in the market. People are using cloud code, people are using cloud. They're starting to see the value of using AI and integrating it into everyday life for consumers and into different business processes and enterprises for you know accelerating development or just building better products. So the value actually exists. So that should lead to the like it shouldn't just be the investment from Google paying for the services. There should be some other revenue coming in from actual operations. That's something to keep in mind. They are a private company, so we can't actually see their books. But when they do IPO, we will be able to see and have a little bit more access into kind of where the money is coming from that they're spending. And that will give a lot more clarity to you know whether or not this investment really makes sense. But from Google's perspective, I think it's fine. Uh, Amazon saying, right, they are investing into the systems that will continue to make their infrastructure, their data centers valuable, right? They, hyperscalers in general, have planned to invest nearly $3 trillion by 2030 into data centers. Those data centers are going to be used to run cloud workloads, and those workloads will include AI systems, but it'll also include just you know storage, uh normal compute for just batch workloads or you know, long-running workloads. It's gonna be used to just run computer and data, like uh these applications. Making sure that there are more customers available is a good thing for them, right? If you make the tools available to accelerate development or expand access to develop more applications, then you can almost guarantee that if you had a thousand customers, a thousand new apps being developed every year, then you can maybe have at least 1,500 more applications being developed in the next couple of years. And so it does help increase the revenue expectations over the next three years or however many years that uh these tools continue to just make it easier for more companies to launch and more new products to be released. From a competition standpoint, the real challenge to the Googles and the Amazons and even the Microsoft's is that they now need to compete not on the application itself. They're competing a bit on their ability to manage the infrastructure and how cheaply do they get power, how cheaply do they set up uh these data centers. So they have different competitions that they're working with, but from an application software's perspective, it's going to be a good time because the tokens are gonna get cheaper, so you can start to you know really go crazy. I think everyone is token maxing at this point, for whatever reason they want to use the most tokens. Let them do it. Uh as they use more tokens, the and more providers become available, again, even with Deep Seek uh becoming accessible, all of these things lower the cost per token. So then you can actually will likely spend more. Uh some type of rule or model effect where just when things get cheaper, more of it's actually spent. So you end up spending more of it over time just because of that pattern. So if you even think about electricity, more electricity being available didn't make us use less electricity. We actually started using more electricity for more services, more products, and more things across our life. So that cycle will continue with tokens and electricity and power. So there's a few opportunities ahead of us for what will happen next. But I do think this is this is a positive signal for just the market as a whole and technology as a whole. It's a great thing for developers because I do feel like the more accessible technology is, the more ideas that people feel confident enough to execute on, the more opportunities there are for skilled developers to get out of. Access to new roles to build cool systems. And so there's going to be a lot of opportunity over the next couple of years. I know there are some issues today with like Google spending and agreeing to invest 40 billion into anthropic and having to make other investments into their data centers, causing them to have to clean the books a little bit by uh laying off significant parts of their workforce. And this is a pattern that has kind of been repeated in different companies and different hyperscalers. It's a constant pattern, at least for the last uh 12 to 18 months, and it might continue at least until the end of this year. But it's a I think it's a short-term pain that they're trying to load up to when the actual results can be felt a little bit more uh a little bit more, I'll just say. So in this time, I would encourage everyone to just become more familiar with the tools that are being invested into, like learn how to use clawed code or even cursor. Uh learn how to accelerate your development lifecycle process. Like, how do you go through planning, testing, developing, deploying, securing your code, and making sure that you can get products out there faster for the teams that you work with. That's all we had for news this week. Uh, let us know in the comments what your take is, what you think the actual implications will be to the community and the global impacts of some of these developments. Very curious what your thoughts are as we continue. And we're gonna get into the QA section for this week. We have a lot of great info and topics to share about technology and how to be more effective as a professional inside of the technology industry. I want to just re-emphasize it's not just about becoming the best coder today. Code is very easy to write. We need to understand why we're writing the code and what it actually does to improve the solutions that this organization has been tapped to do. Let's get started.

SPEAKER_02 24:26

How do I take care of my health as a software engineer?

SPEAKER_03 24:31

Great question to start. I know that as a developer, as an engineer, we are working on a lot of difficult projects. There's a lot of high stress. There is a lot of you know long days, and we live a primary, primarily said sedent sedentary. If I said that word wrong, but we don't move a lot, we don't move enough throughout the day, and that can cause a lot of issues when you're working in front of a computer, behind a screen, and inside of a building for a long time. So some of the things that you need to keep in mind when you're just pursuing a career as an engineer and in the tech industry is that the physical health, mental health, and spiritual health that you have failed and have, they all compound on each other. They all affect each other. So if you're starting to notice, you know, negative things inside of your physical body, it'll affect your mental. And if it's in your mental, it'll affect the spiritual and it and these things just if you don't address them quickly enough and well enough, they will continue to get worse and they'll compound in a negative way. So when you're thinking about improving your health as an engineer, be mindful about practicing habits that actually allow you to break some of the bad patterns that we almost have to do because of the way our jobs are. So if you're behind the desk all day, you should make sure that you have some opposite practice throughout the day to get moving. Make sure you're getting in your steps, whether that's a walk before you go into the office or walk after lunch or a walk before dinner. Make sure you're getting some steps in, make sure you're getting some movement in. Make sure you are uh, you know, actively moving different parts of your body. Right? You don't want to have injuries caused from you being stiff all day and then trying to move one day and it just hurts because you haven't prepared your body for that type of movement. So go out, do some strength training at least twice a week. You can do more if you want to, but let your brain continue to develop and your body, you know, let it just get what it what it gotta get to. Um do some cardio. Make sure you get in a nicer amount of you know blood flow through your body. I would give a lot of emphasis to your hip mobility. If you're sitting down all day, even if you're standing at your desk, that doesn't mean that you're moving your hips and your lower back enough to actually deal with some of those complications that you would get from just not moving your core. So make sure you're doing different workouts like yoga or even pilates to just keep all of that together tight, strong. Uh drink a lot of water. Like a lot of the time, and this is not even just force devs, a lot of us are chronically dehydrated. Make sure you are setting systems in your life to actually focus and improve the habits. Like make sure you're getting enough water, make sure you're getting enough of the right food, not just eating, you know, whatever is convenient to you. Eat something that's good, whole foods, nutritious, so that can actually make you feel good while you're doing the things you have to do. Uh again, even with the walks, going outside, touching grass, seeing other colors besides a blue screen or a white screen or uh dark light, if that's what you you're used to. Get some time looking at the sun, get some time looking at trees, different colors in the sky. Like all of these things are good for your mental health. Get some time listening to the water if you have some natural water sources around you, or just try to change the environment that you're in sometimes, so that you don't get so caught up in the cycle that you're already in every day. Uh keep in mind that even though tech moves very quickly and the industry is always changing, you want to be here for the long term. And if you burn out too quickly because you're not taking care of your health, you're not gonna be able to get the results that you really want, that long-term compounding, that long-term group growth. And you're not gonna enjoy the growth that you get because you're gonna be dealing with other issues in your life. So figure out those systems that work for you, whether it's reminders, whether it's a piece of paper at your desk that says do this, or like however you make it work, figure out a way that makes it work for you. Like I have systems in place to make sure that I'm working out at least once a week. Like twice, bare minimum, once whatever you could do to move, I definitely make sure I walk in the mornings or for me when I commute into the office, I actually take my bike, it's a 20-minute bike ride, and actually have a motorized bike so I can actually ride, not get too tired, but get enough at least a little bit of movement in throughout my day early in the morning. I could see the sun while I'm going to the train station, uh setting up reminders to call my friends and my family to make sure I have some communication, some natural uh conversations and build community and having other hobbies outside of tech, like I write or I read, and I paint sometimes or sketch, depending on how much time I have, to make sure that I have something else that my mind can kind of focus on where I'm not just thinking about the code or thinking about solving problems. Because your mind, if you use it all the time just to do the thing that you do, it's not gonna be able to rest. And that's what you mean. You need different ways of rest that gives you life satisfaction besides just the work that you do.

SPEAKER_02 30:48

What are the differences between a thread and a process?

SPEAKER_03 30:53

This is one of those fundamental concepts that you might skip, but that's definitely worth understanding. So a process is an independent instance of a program. Basically, your process is the thing that the CPU is handling at one point of time. It has its own memory space, has its own resources, and it's fully isolated from other processes. That allows it to not be affected when there's a problem in one process. It doesn't break and crash everything else running on your computer. That's a good thing. A thread is a thing or an instance that runs within a process. So you can have multiple processes or multiple threads running inside of one process. And when you have things, when you have that setup, then your threads can share resources, so they can share memory and data, which allows them to you know pass and do things much faster, but it also increases risk because now one problem in a thread on your left side can actually start causing issues inside of the running of the threads on the right side. That can cause some issues over time, depending on how you do it. One of the things to keep in mind when you're thinking about threads and multi-threaded programming is that having multiple threads doesn't actually mean that you have multi multiple threads running at once, right? If your CPU doesn't actually have multiple cores, you don't you still can't get the benefits of multi-threaded processing. Which I'll say I'll say multi-threading. I won't say thread processing, man. You can't get the benefits of multi-threading just because you have multiple threads running or you will create multiple threads. You have to have the hardware in place, whether virtual or physical hardware, that actually can run the thread itself. So you're still limited by the hardware available to you. Uh, an important thing to keep in mind when you're working in an application that is using multiple threads, is that you need to understand which operations are thread safe. I already mentioned that a process or a thread, multiple threads inside of a process can share resources. That can be great for some applications and some use cases, especially when you want to move quickly, but it can be an issue when you have data from one thread affecting a variable or some type of data that you need in another thread. And if you don't have any checks in place to know when there's something wrong or when a piece of data is being used or worked on, you can have some really say bad, it's bad because it's difficult to always determine that it's happening. But it so these problems can kind of fail silently. One of the things is in modern systems, you might have a concept of a thread pool where your web application is going to create multiple threads that each request can use, right? So every thread picks up a request as they come in and it will process that request. That gives the illusion of being able to process multiple requests at once. Not even say illusion, it is a way that we can process multiple threads at once or multiple requests at once because we have multiple threads running. This is useful. This allows for us to scale applications vertically. I've had a problem before when I was building and enhancing a Java API or Spring Boot API where I was implementing our logging system and we were trying to add tracing so we can understand kind of what requests were being triggered by which users. I made the mistake of saving some data inside of a thread that or saving some data inside of the context of a thread that usually would get cleared between requests. But when there were multiple requests that came in at once, sometimes those caches or those that context didn't get cleared. So I started seeing, or we started seeing in the logs inside of our production environment that there were requests that were coming through saying they were triggered by one user that was not actually accurate. So it was a logging failure that I started seeing. And this was just an issue of me not being aware of the threads sharing that or storing that data over the long term. So it's something that you have to keep in mind when you're using multiple threads to understand when something should be cleared or when the data should be cleared, understanding how to sync operations between multiple threads. There's a lot that could go wrong if you don't understand the difference between the two and how to use them.

SPEAKER_01 36:34

How do I run meetings effectively?

SPEAKER_03 36:38

So meetings are some of the most expensive activities that your business will wait. Meetings are some of the most expensive activities that your business will waste money on. When you have a call and you add more people to that call, the cost of running that call become or and grow exponentially. If you're running a meeting or attending some type of meeting, you should keep a few things in mind to make sure you use the best or you make use of the time in the best way possible. So start with why. Before you schedule any type of call, make sure you understand what the objective is for that call. Are we here to make a decision? Are we here to align on something? Are we here to do something? You should know what you're doing or what you plan to do in that call by the time you're uh scheduling it. And that helps you know who to invite. So you make sure you're only inviting people that need to be on the call. Invite people that are going to be there to help execute the task. So if it's a developer, making sure that they are the one that can run the code. If it's a leader or decision maker, making sure that they're the one that can make this final decision. If it's something that's alignment, you need to make sure they're the one that are actually doing the job. If you have people on the call that are just observers, they're just here, they don't need to be here. You can s you can share notes with them later, it'll be fine. They'll have gotten the same results from seeing the notes as they would have gotten if they had attended and said nothing during that meeting. So be mindful about who you invite. And a good tip that I can probably use more, and I do sometimes use it uh as I when I run my meetings, uh, but making sure you prepare some type of context, prepare some notes for everyone available. And that could be something as simple as if we're here to discuss a status on some type of task, as long as everyone understands what the status is and where to get that context and where the data is available, they should have or should be able to take some time prior to the meeting to actually go through those notes and understand all right, this is what this is what we can do to move this forward during this meeting because I have this context available. I know Jeff Bezos actually had a like a rule with his meetings where he would share, or the people, whoever was driving the meeting, would share a one-pager about whatever the thing was that they wanted to discuss. I think they spent like 10 many, 10 minutes at the beginning of a meeting to actually go through and read whatever the context was. So this is another helpful tip. Like if you prepare the notes and have that summary available, whether they read it before the meeting, which is sometimes hard for people to find time, or they read it in that first 10 minutes, it just gives everyone a good baseline to start with to have this conversation, especially if we're trying to make this meeting effective. We want to make sure that everyone is up to point, everyone is understanding what we need to do, what the options are, and what is required to move forward. So you can do that pretty easily. It can sometimes just take 10 minutes just to figure out going through this practice to say, all right, this is why we need the meeting, this is who needs to be there, this is what we want to decide. Share that context. I use uh I use a different, a few different models, but with my current project, I have been using uh copilot a bit more to create my notes. That could be a helpful tool to you when you're just trying to understand you know what format context is important to help prepare this meeting. And another tip is to drive the conversation if you're the leader of that meeting. When we go into a call, a lot of the time, if there's especially if there's a bunch of people there and no one kind of understands or takes responsibility for this is where we're going and this is how we're driving, this direction we're going, then you can get to a point where we're kind of just rambling and we're just not making the progress that we want to make inside of this valuable time. So when you're leading these meetings, make sure to enforce some type of structure. Invite people to share their thoughts if you are looking for alignment or feedback and listen to what they say. And then when you start to notice the conversations are kind of getting off topic or we're moving too far in the direction that we don't want to be moving into, you know, try to push and herd everyone back to where they need to be so that we can actually meet the goals of this meeting. We want to make sure we are running the meeting on time, we are getting to the bottom of the objectives that by the end of that meeting to make sure that the investment placed of everyone's time has been well spent. So think about it this way: a great meeting is one where the right people show up, make the best decision, and leave with a clear path forward. Everything else is going to be a waste of time.

SPEAKER_01 42:21

How many environments should your application have?

SPEAKER_03 42:27

So the number of applications or the number of environments your application has is a risk and cost-driven strategy decision. When you're working in an enterprise environment, you could likely have four or more environments. You'll probably have a dev, QA, UAT, and make at least one production environment, depending on how you're set up for you know active, active or active, passive, uh high availability. You can have that set up. And this is a benefit depending on the industry that you're in, to make sure that you know nothing can ever go down. If you have a strict SLA, then and limited downtime availability, then you have to make certain decisions with your environment to make it all make sense. Most organizations are going to be cool with just three environments, a dev, QA, and a prod. And that gives you enough flexibility where you can make changes without breaking and derailing other people, while also giving a nice amount of reliability to your customers and your users over time. But for most startups and solo builders, I would recommend you can actually go with just a dev and a prod. You could even just have a prod if you know how to set up your local environment to match production. Accurately. Right? A lot of the reasons when you need multiple environments is because there are a bunch of changes going in at once from different developers and different teams, and you may not be able to keep track of some of those releases. And so something from team A could break team B's code. And you have to have different controls in place and different environments that can help you know create bottlenecks for those changes so that we can know and check effectively what is working, when it's working, and when it's not working. When it's just you coding and you know what you changed and you have the processes in place to roll something back and the alerting in place to know when something broke, then you could play a little loose with it. Not saying that's the best decision, but if you're a solo builder, you probably don't have a lot of funding anyway. So you don't want to be running too many versions of your application. Although it might not cost you too much to do it. Again, it's a cost and risk decision. You can decide which one is best for you. But it's really a part of your risk strategy. It's about how seriously you take user data and the availability of your application and how well you're able to continue to ship changes without breaking things. One of the reasons why you should always have at least some separation between production and development is that you want to be able to make sure you don't break anything with your users, right? Like if there's some type of data that you are storing for your app your users. If you don't have controls in place to separate dev from production, you might make a change to production data that's really hard to roll back from. And there's a few ways to kind of plan around that, but the easiest way is to just logically separate it. Make sure there are some boundaries that this version of the application cannot update data in this, and then you have strict controls to make sure that when this application version goes to this environment, it is the well, is the best version of it. It is exactly what we need for it, it's gonna do exactly what we need to do in the right way. But you probably still would need some type of controls or ways to roll back your data sets, right? Because you might no matter how good your team is, no matter how good your practices are, you still might make a mistake in production. You should be backing up data at least daily. Well, it depends. Again, it's up. It depends on your industry, how much data is being created, and what that data is being used for. So there's a few ways to look at it, a few things you could do.

SPEAKER_01 47:00

What does it mean to be competitive?

SPEAKER_03 47:04

So, this is a very interesting question today in this time because there is blood in the streets in the tech industry right now. Like we all see the headlines of you know thousands and significant portions of large companies being laid off or being pushed into retirement. This is happening daily. We I already mentioned we might continue to see a lot more of it over the next couple of months into the end of the year as things settle. Today, we're not totally sure what impact AI is going to have on the workforce, on business, and on just the industry in total. There is a lot of change that is happening, there's a lot of you know, new people coming into the industry. And with new people coming into the industry and some of these tools becoming better, right? You can have a cursor or a clawed code that gives someone with that used to be just a product person or with no real engineering skills, you can have them coming in and shipping production code. So your competition has grown. The number of people you're competing with has grown. But your ability to be competitive means that you are able to consistently deliver results beyond what is expected of someone in your class, quote unquote. If you are a senior developer, you are expected to continuously be more productive than the other senior developers inside of your group, inside of your year, whatever it may be. And that's the same for every level, whether you're uh staff, whether you're a junior, whether you are a college student, you're being compared against everyone else who is available in that same niche or that same bucket as you. And from one perspective, no one is exactly the same, right? You can't compete by being you, but you can compete by being a developer. You can compete by being an information security professional. There are ways you are competing with other people that require you to be better than them inside of whatever sport or activity that you are playing in. And even in that sense, there are some things that you should not compete in. There are some things that should just be done for fun, right? If I'm a software developer, I spend a lot of time improving my mind and my ability to process technical concepts. I'm not trying to be a built, a bodybuild. I don't want to be the strongest person in the room. I don't want to be the best fighter, right? So I'm not going to compete in those areas because that's not what's valuable to me. That's not what's interesting. So when you're thinking about competing and what it means to be competitive, you have to understand and find something that is interesting to you that you desire to be the best in and better than everyone else in. Because it's going to require you to put in a lot of energy to become the competitive version of yourself in that space. You're going to have to practice more than everyone else. You're going to have to practice longer. You're going to have to be more aggressive. You're going to have to go harder even when people are getting tired. You're going to have to do you're going to have to do things that other people would not do in order to be competitive in that space. And most people give up before they actually, you know, be competitive. Most people don't actually want to do better than the people around them. And that's okay. Understand everyone is not trying to be competitive. Everyone is not trying to be the best in their space or their field. But if you're not being competitive, then you're going to get whatever everyone else gets. And if you don't want to get what everyone else gets, you have to do better than everyone else. And again, that's not going to be easy. And I don't mean that you have to do wrong to people. You don't have to undermine others. You don't have to be a people pleaser. You don't have to chase things that don't work for you. But you need to understand the game that you're playing in. You need to understand how you adapt so that you can improve your position in whatever the spaces that you want to be the best in. That's all we have for QA for this week. I hope you got some value from the message and the thoughts. Quick just mindset reset for us in the community. I want to highlight that it matters the way you speak to yourself. The thoughts that you say in your mind, they are literally hypnotizing you as you go about your day. Your thoughts affect your emotions, and your emotions affect your thoughts. If you're not being mindful about the thoughts that you say, the words that you say, the feelings that you have, then you can get locked in some pretty negative cycles that will only get worse over time. So I encourage everyone to break those negative cycles by intentionally adding positive thoughts into their day. That could be something as simple as saying affirmations to yourself. And you could either say it out loud or you could write it down and read it back to yourself. That could be some other type of positive self-talk. Certain affirmations that I give to myself, I love you, Kevin. I am proud of you, Kevin. I am, you know, proud that I work hard. I'm proud that I didn't give up. Like there's things that you can say to yourself to improve the way you speak to yourself. And that's not going to mean that you don't say something negative in your mind whenever you see yourself. Like, I still have negative thoughts, negative self-doubts that sometimes pop up. But you have to control the narrative that you tell yourself. Otherwise, all of those negative thoughts will just become the constant conversation in your mind. And again, you don't want to have any type of messaging that is with you 24-7 that is not aligned to the development and better and improvement of yourself. So do everything that you can to not just avoid all negative thoughts. That's probably impossible, but reduce their power by adding some more compassion, adding some more love and support for yourself and others into the mix. Sometimes you could even get a benefit from giving a compliment to someone else and them saying thank you, and then you having that response in your mind, like, oh, I know I did something good for someone else, or I know I made them feel better, whatever it may be. Find some opportunities for you to change and break those cycles in your mind. Because sometimes, if you're not mindful about it, it can just start affecting you without you even realizing how much it's affecting you. And before we go, some quick announcements. Uh May is mental health awareness month. So take a moment to check in with yourself and with your family, your community, and you know, listen to someone, talk, show some empathy, create a space for honest conversations that can make a real difference in people's lives. Whether it's the people that are really close to you, people that you work with, or people that are just around you inside of the community that you may not even speak to throughout the day, but just see them. Try to give a kind word, try to listen if possible, uh make some time for others and make a space for others so that we can just live in better groups and communities. You want to be happy with the people around you, you have to be a good person in those groups. And it's also Military Appreciation Month. So thank you to our military members and their families for their strength, resilience, and dedication in protecting our country. Uh, it's not an easy job, and so salute to everyone that has chosen to uh just take that stand and you know, step forward another step back. So thank you all. Um, and on June 20th, we are having the Self-Esteem Awareness Walk with I Self-Empower Organization. It'll be in Harlem. It's good to be back in Harlem. Uh, June 20th, we will be walking, we'll be talking, we will be empowering our community and doing everything we can to grow as people, as professionals, as developers, and growing in all the ways that we want to be growing in. Uh, one of the things to keep in mind is that we have to be attention about the spaces that we show up in and find spaces that are positive, that are aligned with the growth that we want to be in. So, this is gonna be a great opportunity to you know find that community, find that conversation that you probably need, and that can help you become a better person in the future in the way that you want to be. So, with that being said, happy software Sundays, everybody. Enjoy your week, enjoy the time ahead, be safe, be healthy, be happy, be great. Uh, and I will see you guys next week. Peace out.