Entitlement Leads to Disaster [Raw Session]

00:00 — Watching someone you love struggle

Hey, welcome back to Slow Builds. So lately, I've been thinking a lot about entitlement. And I don't really mean the internet version of entitlement, where somebody thinks they deserve a nice car or they're mad because they didn't get something they wanted. I'm thinking about something a lot deeper than that.

I've talked about a situation in one of my other videos, and right now we're watching someone we all love go through a really difficult period of their life. Things are being lost: housing, income, relationship, family, opportunity, stability.

And when you care about somebody and you see that happening, obviously your instinct is to help. You want to protect them. You want to soften the landing. You want to make sure that when they finally decide to get better, there's still something waiting for them.

But what I've been struggling with is this: what happens when almost everything that goes wrong is still viewed as something someone else did to them? "They're taking this from me. They're not giving me this. They won't let me have that. No one's helping me."

And eventually you start wondering where helping someone ends and enabling them begins.

01:23 — When everything has always been provided

I think some of this comes from what you learn throughout your life. If things have always somehow been provided, you can lose the connection between having something and what someone had to do to create it.

Housing is just there. Food is always there. Someone has a vehicle. Someone will drive you. If you get in trouble, someone will probably help you out.

Even work can have a completely different meaning. If your income has never really been necessary to survive, then having a job might just feel like something you do. You go there, you meet people. It's your socialization. You make some money, you spend it. It's almost an experience rather than a requirement.

But the paycheck isn't keeping the lights on. It's not paying for the mortgage, buying the groceries. It isn't the difference between having somewhere to sleep and not having somewhere to sleep. And then suddenly life changes, and those things actually matter, and you're expected to understand all of that.

I think that's where entitlement can become extremely dangerous. Because if you've always been protected from the relationship between decisions and consequences, consequences probably feel like someone attacking you when they finally arrive.

02:46 — You can't learn while someone always holds you up

This reminds me of another thing I've talked about before: learning how to ride a bike. Someone can buy you a bike. They can put the helmet on you. They can hold your seat. They can run alongside you. They can stop you from falling every five seconds. That's helping.

But eventually they have to let go. Because if they never let go, you didn't actually learn how to ride a bike. You learned how to ride while someone held you up, kept you from falling.

And I think we do this with people in life too, especially when it's someone we love. We start planning the recovery for them before they've even started recovering, or even asked for help.

"We'll keep this because when they get better, they'll want it. Don't get rid of that because they'll need it when everything gets straightened out. When they're back on their feet, when they come to their senses, we'll make sure this is waiting. We'll make sure that door stays open. We'll protect this for them."

And I completely understand why it's done and why we do it. It's done out of love. It's done out of not wanting to see suffering. It's not done as being like a prize at the end. It's not a rainbow. There's a rain cloud, then there's a rainbow, and then there's the pot of gold. So we're in the rain cloud.

You're picturing this person coming back. You want this person you know back. So you're almost preparing their old life for their return. But lately I've been wondering if we're accidentally allowing them to skip part of the journey they need to go through.

04:19 — The boat and the life preserver

The picture I've had in my head is someone falling out of a boat. And obviously, if someone is literally drowning, you help them. I'm not talking about abandoning someone in actual danger. I'm thinking about it more as someone trying to rebuild their life.

I don't know if you can constantly have a life preserver sitting right beside you, because if they know it's there, they don't really have to learn how to swim. They don't have to suffer. They know there's a rope. They know someone's eventually going to pull them back into the boat. They don't have to do anything. All they've got to do is stay in there, stay where they are, and they will be saved.

Maybe all they have to do is say the right thing. "I'm ready to change. I'm going to get better. I know I made mistakes. I'm done with this life. I want to come home."

And everyone gets excited because that's exactly what they've been waiting to hear. "Okay, great. Here's your stuff. Here's this opportunity. Here's that thing we've been keeping for you. Here's the old life again."

And technically they've gone from the water back into the boat without really having to cross the distance themselves. That's the part I've been thinking about, that distance. Maybe you don't remove the boat. Maybe you don't turn the light off. Maybe they can still see you. They can hear you. They know where you are. They know you're there. They know you're waiting. They know you're a little bit out of arm's length, basically. But they know you're still waiting.

But the rope might need to be farther away than they want it to be. The life preserver, they've got to swim a little extra hard to get there. They've got to tread some water. They might actually have to swim through the current, through the storm. They might have to get tired. They might have to struggle. They might swallow some water.

And it's not because you want them to suffer, but because there are parts of that journey that no one else can do for them.

06:15 — When consequences become real

And that's where this idea of rock bottom becomes difficult. I don't think someone needs to lose everything just for the sake of losing everything. And I'm not cheering for someone I love to suffer. But there does have to be some point where consequences become real. There has to eventually be a point where someone else's guilt isn't the escape route.

Because families are really easy to pull on those strings. That's what makes it so difficult. They love you.

They don't want to see you hurting. So maybe Mom will eventually do this. Dad will do that. Your brother will fix something. Your sister will give you some money. Someone will give you food. Someone will give you a place to sleep or stay. Someone will clean up after your mess.

And every individual decision can look like compassion. That's the trap, because taken together, you might be preventing the one moment that actually has to happen. The person saying, "This is where I am. Whatever anyone else did wrong, whatever happened before, these are my circumstances now. What am I going to do about it?"

I don't know how real change happens before someone reaches that point, before they ask for that help, before they know there's no other option, before they know they're the ones who have to get themselves out of it. Or at least ask for help and put in the work.

07:36 — Why earning things matters

And this is probably why I think earning things matters so much. Not everyone needs to struggle. I don't believe that. I've had help in my life. I've had opportunities. I've been very fortunate. There are absolutely things that have gone my way. But I've also put a lot of work into everything I've done.

And I have relatives and friends and people around me throughout my life that look at things that worked out for me and basically say I was lucky. Things were handed to me. Things just seem to work out for him. And sometimes maybe they're right about the luck. Luck is real. But people normally see the result. They don't see what happened before the result.

08:17 — The work behind this YouTube channel

This YouTube channel, it's actually a pretty good example right now. I'm putting a lot of work into this thing, and right now it's basically going nowhere. I'm glad for the people that follow. I'm glad I get the watches. I love it dearly. But it's going slow, and that's just reality.

I'm making videos. I'm showing up. I'm thinking through my ideas. I'm experimenting. I'm learning how to talk through things better, I hope. I'm trying thumbnails. I'm trying Shorts, Reels. I'm using AI to help me build everything. I'm having fun, basically. And maybe nothing ever really happens with this. That's possible.

Well, let's say I keep doing this for the next five years. Let's say there are hundreds and hundreds of videos sitting there, and then something catches. One video gets picked up. People watch another one. Then they find the back catalogue, and suddenly the channel starts growing. If that ever happens, it's going to be awesome. I'm going to love it.

Somebody's actually going to look at this and say, "You got lucky." And maybe I did. Maybe one lucky video was the thing that opens the door. But that lucky moment wouldn't tell the story of the four or five years before it. And that's the part people don't normally see.

09:28 — Luck and work aren't opposites

I think I've slowly learned that luck and work aren't opposites. You can get lucky and still have done the work. You have to do the work to get lucky, in my mind. You can have people help you and still carry your own weight. You've still got to put the work in, and people have got to be willing to help you. So they're not going to be willing to help someone who doesn't want to do the work.

You don't need to come from absolutely nothing for something to have value. But I do think you need some connection to the process, because the process teaches you what things cost. Money, time, stress. Getting up when you don't feel like doing something. Doing something repeatedly while seeing almost no results. Failing, starting again, making stupid decisions and then having to fix them. Saving for something instead of just getting it. Waiting. Learning.

There's value in that. Because when you finally get somewhere, you understand what went into getting there. And I think that's where some of the gratitude comes from. You don't casually want to go back to zero because you remember what zero felt like. You remember what the struggles were. You remember how long it took to move away from zero and start adding up and building up.

10:39 — Helping without restoring everything

And so I think that's what watching this situation in the family right now is teaching me. Helping someone doesn't always mean restoring everything they've lost or keeping that there for when they're ready. Helping doesn't necessarily mean preserving that old life so it's waiting for them whenever they decide they want the help and they're ready to get it.

But helping doesn't mean abandoning them either. There's somewhere in between. Keeping the light on, letting them know where you are. Help them see the direction they need to go. If they're genuinely swimming towards something better, encourage them.

But maybe you don't swim every part for them. Maybe you don't keep throwing another rope every time the water gets uncomfortable. Because at some point they need to know they can swim. And probably more importantly, they need to understand that they're responsible for swimming.

That's the part I'm still trying to figure out. Because when you love someone, pulling them into the boat feels like the kind of thing you're supposed to do. But I'm starting to wonder if constantly pulling someone back into the boat can sometimes be the exact thing that keeps them from ever learning how to get there themselves.

11:52 — Learning enough to stop repeating the cycle

I hope the message landed on this one. It's a shorter video. Yeah, there's a lot to talk about there. You've got to go through the journey, because you've got to understand where you came from. You need to know how you got to where you were. You need to know the things you lost.

Because if you don't lose anything and you don't have to fight to get things back and re-earn them and rebuild them, then what's to stop you from doing it again? What's to stop you from just repeating the cycle? Like, "Okay, well, I did that. Caused a lot of trouble. But I'm back to where I was, and I don't feel any different."

So, you can throw out a life preserver, but don't... make them swim a little harder for it. But you can't just keep doing that over and over again. At some point they've got to learn how to get to the boat themselves. They've got to learn how to swim. They've got to get stronger. They've got to get more resilient. They've got to learn how not to fall off the boat.

13:03 — Not every adventure is fun

I hope this resonates. I hope someone listens to this. You don't have to comment on it. These are personal stories that we all go through. We all have families. We all have situations. We all have friends.

And life is an adventure. That's what I say. But not every adventure has... Adventure is a great word, and it always sounds like fun, but not every adventure is fun. Adventures give you lessons. They help you learn. And that's the way you've got to look at everything.

My life's been a disaster forever, but we're always happy. We get through it. We move forward, and we learn from it. It can always be worse, and the sun's always coming out.

So have a great one. Thanks for watching. Bye.

AI Should Tell You When You’re Wrong [Raw Session]

00:00 — Why this one is difficult to talk about

Hey, welcome back to Slow Builds. I've started this video a couple times. It gets a little personal and a little deep, but it is AI related. It's AI being used in situations where it pushes people. It kind of reframes their words around their opinions and the story they tell it, rather than objectively.

This one's affecting me a little bit because I want to tell my story, and I've done it a few times. So I'm going to start by going to that deep part first. I'm going to stumble. I've tried to do this one four or five times. I want to get through it. I'm going to read the script the way it is, and we'll get there.

00:53 — I don't need help being wrong

So what it is, it's been bothering me quite a bit, something about AI. I don't want AI to constantly tell me I'm right all the time. And I know that sounds very weird, and it's an odd complaint to have about something always telling you you're great. Because normally when we talk about AI, we're always talking about the coding abilities, how great it is, the advancements and everything like that.

But this is a little different when I think about it. I think AI is incredibly good at taking whatever direction you give it and helping you move further into that direction. And sometimes that's exactly what you want. But what happens when the direction itself that you gave it is wrong to begin with? Because I don't necessarily need AI to help me become better at being wrong.

01:41 — Praise and participation awards

And I think this probably connects to something about me that has always been there. I've never really liked praise just for the sake of praise. I remember when my kids were younger and everyone would get an award just for being there or just being on the team. Everyone gets something no matter what, and I really, really hate participation awards.

And I know some people probably think that makes me miserable, and it makes me a grumpy old man, and "back in my day." And it probably does, and I probably am like that.

And real quick, graduation ceremonies, high school. I always say, we're supposed to graduate high school. I don't understand why it's always such a massive accomplishment. I understand back in the day, when a lot of people dropped out, went to work, all that stuff, and school became part of the curriculum, became part of life. And now, in my day, like my kids, nobody fails. No one gets kept back in grade. No one jumps a grade either. But everyone pushes through. They go through the pipe. Everyone gets it.

Now some kids, yes, they have a harder road. There's a lot of circumstances we don't know about, 100 percent. There are a lot of people that get through high school because they have learning disabilities, because of home life that we have no idea about. And it's amazing that those people can make it through life. They deserve to have the best rewards. And the sad part is, they're probably the ones that don't get it.

It's the other kids that were going to get through no matter what. They got the best grades. They're going to go to the great university. They got a job lined up. They're going to get the big celebration, where the kid who struggled, had the hardest time, he's the one who gets left behind. He doesn't get the great job. He doesn't have the things lined up, and he gets no celebration. He's the one that deserves a celebration, or she.

Anyway, I digress. Let's get back to the story. So I'm not really trying to make a video complaining about graduations, participation awards.

03:38 — Helpful and agreeable aren't the same

The thing underneath it is what interests me. I don't like reinforcement when you haven't established the thing being reinforced is actually good. If I do something stupid, I don't want someone telling me it was brilliant because they want me to feel good. If I have a terrible idea, I don't want someone helping me convince myself it was a great idea.

And that's where I think AI gets really interesting, because these systems are designed to be helpful. They're conversational. They're agreeable. They're trying to understand what you're asking and helping you accomplish it. Most of the time that's fantastic, but sometimes I wonder if helpful and agreeable start becoming the same thing. And they're not.

Sometimes the helpful answer should be, "No, you're wrong." Or maybe not even that harshly. Maybe it's, "I think you're missing something here. Your assumptions don't support that conclusion. You're asking me to help execute this, but before we do that, I think we should question whether you should be doing it at all."

Because there's a huge difference between helping someone execute a decision and helping someone make a good decision.

04:45 — When AI enters a difficult family situation

And I've been thinking about this because we're going through a difficult situation in our family right now. This is where the story goes to where I wanted to get. I didn't want to lose too much, and I get here quickly.

So I'm deliberately not going into all the details because it's not my story to tell alone. And some of it's very personal. But someone is going through something we don't really understand. We don't exactly know everything behind it because there's little communication. There could be drugs, mental health. It could be a combination. We don't know, and I'm not qualified to diagnose it. But there's enough evidence that we have. Our hunches are probably more than correct.

What I do know is that a lot of decisions being made are objectively making the situation very much worse than it needs to be. And it's getting worse all the time. Relationship, financial, the family. There are consequences accumulating quicker than we know. And AI's become part of that problem. It says here "solution," but really it's part of the problem.

This person can take their version of what happened, put it in an AI tool and say, basically, "Here's what happened. What are my rights? What should I say? Give me a response."

And the response comes back incredibly polished. It sounds reasonable. Sometimes it sounds almost legal. It can use the right terminology. It can explain rights that actually exist. It can take something that started as an emotional thought and turn it into this very structured, confident message.

And if you're on the receiving end of that message, which I have been, you have a problem. Because you don't know exactly where it came from. Did they actually speak to a lawyer? Did they talk to someone at the government? Did they contact somebody who understands the situation? Is this something we genuinely need to react to immediately? Or did somebody give an AI half of the story and ask it to construct the strongest possible argument from that half?

And those are very different things.

06:47 — An incomplete story can sound complete

And that's where it gets complicated, because the AI might not technically be lying. Imagine I tell an AI, "My family has my belongings and refuses to give them back. What are my rights?"

There are probably rights associated with it. There are things I can do. There are messages I can send. There might be laws that apply. The AI can help me write a very, very convincing response on that one.

But what if I leave out that I moved out a month ago, or two months ago, or three? What if I leave out that I was given multiple opportunities to get my stuff? What if I, through messages, said they could dispose of my stuff and get rid of it? What if there are safety concerns? What if there were other agreements put in place? What if I'm wrong about one of the facts?

The AI doesn't magically know any of that. It knows the world I gave it. And that's the part I keep coming back to. AI can take an incomplete version of reality and make it sound complete. That's powerful and potentially very dangerous. It's already being dangerous, and it's already being used this way.

Because now I don't just believe I'm right. I have this really intelligent-sounding thing agreeing with me. It can reinforce this feeling of, "See? I knew it. I'm right. They're wrong. I'm being mistreated. I'm owed this. I should do this." And that can escalate things very quickly.

I'm not even necessarily talking about delusion. It can be much simpler than that. It can reinforce entitlement, anger, somebody's interpretation of a situation. It can make somebody more confident in something they already wanted to believe.

08:25 — The questions AI should ask

And the strange part is, I don't think this is completely an AI problem. Humans do this too. People tell stories from their own point of view. People leave out details that make them look bad, make others look bad, make them look good. Sometimes intentionally, sometimes they don't even realize they're doing it. We've probably all done it. It's like there's three sides to every story.

You get into an argument with your spouse, and you tell your friend what happened. And somehow in your version, you're incredibly reasonable. They're like, "Why is she mad at you?" It's amazing how that works when your friend only has your version. So your friend says, "Yeah, that's ridiculous. I can't believe she did that." Well, of course. I gave you the story where I'm right.

AI has the same problem, except AI can sound a lot more authoritative than your friend. And that's where I think the AI should sometimes push harder back. Not, "You're wrong because I somehow know the truth." It doesn't know the truth. But maybe, "I only have your version of the situation. What would the other person say happened? Is there information you're leaving out that could change this? Do you have documentation? Are you asking me what is legally correct? Are you asking me to make your argument stronger?"

Those are really valuable questions. Sometimes more valuable than the answer.

09:37 — The same pattern in AI coding

And here's the weird part. The exact same thing happens to me in code. See, it always comes back to software, because AI is software in the end. Obviously the stakes are different, but the pattern is almost identical.

I use AI a lot for development now. And because I work inside existing systems, like at work and that system, we have rules, patterns, and architectures. There are things we do and things we don't do. When the AI has enough context about the application and understands those constraints, it's really useful.

It can say, basically, "No, this doesn't belong here. The application already handles this over here. Use this service. Follow this pattern." That's what I want. I don't want it inventing a new architecture or framework because I had a random idea on a Tuesday afternoon and it went wild.

But if I'm working on my own project, I can tell it almost anything. I can say, "No, I don't want to do it that way. I want all of this in the controller. I don't want a background job. I don't care about tests. Don't refactor it. I want the database structure to be this. This is the technology we're using."

And eventually AI will usually go, "Okay, given those requirements, here's how we do it," which is useful. But it's also kind of hilarious when you think about it, because if I'm stubborn enough, I can probably convince this incredibly advanced AI system to help me build complete garbage.

10:59 — Can I make AI build a terrible application?

And I know I actually want to test this now, because I think this might be a great video. Can I make AI build the worst application possible? Not broken. That's the important distinction. I want it to work. I want to make increasingly terrible technology decisions and see where the AI actually refuses to go along with me.

Could I make it build some horrible old ColdFusion application? Could I insist on no JavaScript, no testing, terrible database design, maybe just flat files, everything coupled together, giant files, super bad performance? Could I keep saying, "No, that's what I want"?

At what point does the AI stop saying, "You probably shouldn't do this," and start saying, "Okay, here's the implementation"? Because I suspect that eventually it will build me the best possible version of a terrible idea. And that's fascinating to me.

To be clear, old technology isn't automatically bad. There are banks running on COBOL systems still, I'm sure. Governments are too, AS/400. They process enormous amounts of data and money every day. There are companies with old ColdFusion applications, I think maybe, that probably work perfectly well. Maybe. That's questionable, but that might be the experiment.

Sometimes maintaining an old system is exactly the correct engineering decision. I'm talking about intentionally choosing bad constraints when there's no reason for them. Because that gets to the real problem. AI is extremely good at optimizing inside the box you give it. But who decides the box was good? Me? That's not exactly reassuring.

12:49 — Working software can still be a bad result

This is probably especially important with vibe coding, because somebody who doesn't have much software experience might not know that the decisions they're forcing AI to make are bad. And if the application works, that's even harder to notice. You click the button, the thing saves, the page loads. Great, boom, it works.

But maybe there's no authentication. Maybe there's no security. Maybe there's no encryption. Maybe the database structure is completely awful. Maybe it falls apart as soon as there's, like, 10 users. Maybe every new feature is going to be harder because the foundation's terrible.

The AI succeeded. It did exactly what you asked, and you still failed. That's the sentence I've been trying to get to with all of this. AI can make a bad idea better without making it a good idea.

It can make bad code function. It can make an angry message sound reasonable. It can make a weak business idea sound professional. It can take a half-complete story and build a really convincing argument around it.

13:47 — What we lose when AI removes friction

And the better AI gets at execution, the more important I think this problem becomes. Because bad execution used to create friction. If I had no idea how to build a website, at some point my lack of knowledge stopped me. If I didn't know how to write a legal-sounding letter, maybe I couldn't produce one. If I had a business idea but couldn't figure out how to execute it, there was a natural barrier there.

AI removes a lot of that friction. Mostly that's amazing. It's one of the reasons I use it. But friction wasn't always useless. Sometimes friction was the thing that forced you to stop and question the idea. Now you can go from thought to execution incredibly quick. And I don't know if our judgment has improved at the same speed. Mine definitely hasn't.

14:31 — Challenge the premise without taking control

So I don't think the answer is that AI should insult people. I started thinking about this as, AI should just tell you you're stupid sometimes. I know it's wrong, but it would get your attention. But that's probably wrong too. Calling people stupid doesn't solve anything.

Let's read that again. So I don't think the answer is that AI should insult people. I started thinking about this as, AI should just tell you you're stupid sometimes. But that's probably wrong too. Calling someone stupid doesn't solve anything.

What I actually want is resistance. I want it to challenge the premise. I want it to recognize when I'm asking it to validate something instead of analyzing. I want, "Here's how you could do that, but I think the underlying decision is bad, and here's why." And that's useful.

Or, "I can write this message, but based only on what you've told me, I can't determine that you're actually in the right." And that's useful. Or in code, "Yes, I can implement that architecture, but you're creating these three problems, and I strongly recommend you don't."

If I still say, "I understand that. Do it anyway," fine. At that point, it's a tool. Sometimes I know something it doesn't. Sometimes there's a business constraint. Sometimes there's legacy code. Sometimes I'm experimenting. I don't want AI controlling the decision. I want it making sure I've actually made one.

And maybe that's the distinction I've been missing. I don't want an AI that agrees with me. I don't want an AI that argues with me just for the sake of argument either. I want something that is willing to create friction when the facts don't support what I'm saying.

Because if AI agrees with me when I'm right and agrees with me when I'm wrong, then eventually the agreement doesn't mean anything. It's just reinforcement.

16:20 — Helping me think or helping me sound right?

And the more we start using these systems for code, money, relationships, businesses, legal, health, and everything else in our entire lives, the more I think we need to understand that difference. Is this thing helping me think, or is this just helping me become more convincing about something I've already decided?

I don't know exactly what the right balance is. I don't want AI constantly stopping every conversation and lecturing me. That would get annoying incredibly fast. But I also don't want the smartest tool I've ever had sitting beside me saying, "Great idea," every time I have an idea.

Some of my ideas suck. Most of them suck. I know that. And I would rather find that out before I spend six months building one.

So maybe what I actually want from AI isn't encouragement, and it isn't negativity. It's honesty. Or as close to honesty as a tool working with incomplete information could give me. Tell me what you know. Tell me what you don't know. Tell me when I'm making assumptions. Tell me when I've given you constraints that don't make sense.

And if I'm still determined to build a ColdFusion website in 2026, fine, let's build it. But at least make sure I know what I've decided to do.

17:40 — The best debater in the world is on your side

So thanks for watching. This one took a while to get to the end. This one deserves a deeper conversation about how we're always being agreed with and how the context is built, and the more it knows of you but doesn't know the whole story.

There needs to be guardrails. There has to be something, because outside of code, and people making decisions and feeding in information and trying to get responses for text, email, inquiries, filling documents, fake certificates, fake references, make up a resume, file reports. It's endless. It's endless.

You have the most powerful brain in the world at your fingertips, constantly agreeing with everything you do and doing what you want. And I don't mean maliciously. It's just, it'll write the words in favor of how you tell it, however way you want it. You can tell it, "Argue with me," and it will do it, and it'll probably win because you can't debate with it.

But you're basically saying the best debater in the world is on your side, is on your team. And it's like bringing the smartest person in the world, or all the smartest people in the world, to trivia night. You're going to win. There's no getting around it.

And that gets hard because it's too easy for everyone to use. That's a good thing. It's not a bad thing. More people need to use it. More people need to learn. More people need to be aware. But there have to be fine lines. There has to be a different level.

I'd rather see someone asking for help with AI to get an actual answer on how to do something and be pushed in the right direction than to go out to Twitter or Facebook or Reddit and just end up with the trolls giving them answers and putting them in the wrong space, and they fall down a rabbit hole. I'd rather have a combination of both, I guess, in a way.

Hmm. There's something there. All right. Thanks for watching. Bye.

The Small Choices That Quietly Build Your Life [Raw Session]

00:00 — Sleeping in was a different choice

Hey, welcome back to Slow Builds.

So this morning I did something that normally I probably would have said was the wrong decision. I slept in. Not really slept in, because I was awake, but normally I get up early, come downstairs, work out, get some things done, and start my day.

I've talked before about doing little things for the future self, and getting my workout done early is a good example of that for me. Morning me does something that nighttime me probably isn't going to want to do. If I leave the workout until six or seven o'clock, now I've worked all day, we've probably eaten supper, maybe we're watching something, and suddenly I have to convince myself to come downstairs and do it.

So normally, most days I give up that lazy morning and get it done. But this morning my wife was still sleeping, and lately I've been trying to spend more time at home and get some of that normal time together back that I think we lost a little over the years.

So I stayed there. We slept a little longer and woke up together. And then I went downstairs and did my workout, where this video idea actually came from. I didn't write the script. I talked to AI between sets and helped it flesh it out with me.

So the workout still happened. I just made a different choice on when I did it, and I let myself relax a little more and build that connection back.

01:41 — Sacrificing something or building something?

And it got me thinking about those little choices I've always called sacrifices. You sacrifice something now because you want something later. But I'm starting to think sacrifice might be the wrong way to look at it, because sacrifice puts all the attention on what you're losing.

Maybe those little choices are actually more about what you're building. And that's the way my mind has been trying to focus on these things.

02:06 — Noticing my own part in the pattern

Before any of that can happen, though, you have to notice that something needs to change. That's probably the hardest part. You have to pay attention to yourself, and sometimes that means listening to things you don't really want to hear.

If one person has a problem with something I'm doing, maybe they're wrong. But if I keep hearing the same thing from different people, or the same problem keeps showing up in different parts of my life, eventually I probably have to stop and ask whether I'm contributing to it. Maybe I'm doing something wrong. Maybe the way I'm acting keeps helping create the same outcome.

That's very uncomfortable, because it's much easier to think about what everyone else could change. You want someone to treat you differently. You want your relationship to feel different. You want things at work to improve. You want your health and you want your finances to change. But if you keep doing exactly what you've always done, it's hard to expect everything around you to suddenly become different.

At some point something has to move, and the part I have the most control over is myself. That doesn't mean every problem is your fault. Sometimes another person really is the problem. Sometimes circumstances are outside your control. But I still have to decide what I'm going to do with that.

That's where these little changes and choices start. You notice something. You decide you don't want to keep going that way. Then you start behaving a little bit differently.

03:33 — Small decisions become normal behavior

Most changes don't happen because of one giant decision. Usually they're made up of things that barely seem important while you're doing them.

Maybe you eat differently that afternoon because supper matters more to you. Maybe you leave something in the store because you don't really need it. You finish something at work instead of pushing it till tomorrow. You go for a walk. You put some money away. You spend some time with someone instead of doing whatever else you would have done.

None of that looks particularly impressive, and most of the time nobody even knows you did it. There's an idea in Atomic Habits that fits very well here: your habits aren't only about producing an outcome. They're also shaping the kind of person you're becoming.

I like that way of looking at it because it takes some of the pressure off needing immediate results. One workout doesn't make me fit. Saving a hundred dollars doesn't make me financially independent. Staying home one day doesn't repair years where maybe I wasn't around as much as I should have been.

But they're pieces. They're bricks. And eventually enough of those decisions start becoming your normal behavior. That's when you notice yourself. Something that used to require effort is suddenly just what you do now.

04:47 — Choosing to work from home

One of the big examples for me lately is staying home to work. For years I would go work at my friend's house. And many other years I was on the road and not even in the same country, province, or whatever.

And I did like that. At my friend's house I have my own office. I have my own routines. On the road I had new offices, new experiences, new contracts, new places to explore.

At my friend's house, I'd always have someone to talk to, someone I work with. And there was a social side to it that I enjoyed. So right now, me staying home is me giving that up. I'm giving up that socializing with a coworker and a friend. I'm giving up someone I can bounce ideas off with and go to lunch with and reminisce about the past times. Just friendship, basically. I still have that. We still have it. We just don't have it on a daily basis.

So staying home actually did mean I have to give something up, and that's an important distinction too. Sometimes change isn't choosing between something good and something bad. Sometimes it's choosing between two things you like and deciding which one matters more right now.

I traveled a lot over the years. And then even when I wasn't traveling, I was often leaving the house to work at my friend's house, because he didn't always travel with me, but I still had my office. It was a comfort and convenience.

Eventually I started noticing how much time that actually added up to. I could see some strain there. Not some huge dramatic thing where one day everything fell apart. It was more that I started noticing the time I wasn't home.

So lately I've been staying home more, and one decision gave me quite a bit back. There's no commute, so I get that time back. I'm buying less gas, putting less wear on my vehicle. But the bigger thing is I'm just here. If one of my kids comes through the house, I'm around. I'm around my wife. I can cook supper. There are random conversations and little things that happen during the day that I used to completely miss because I simply wasn't physically there.

You can't really schedule that stuff. You can't put random conversations with your children into a calendar for 2:17 today. You just have to be around when it happens.

So yes, I'm giving up some of the routine and social part I had at my friend's and coworker's house. But when I look at what I'm getting back, I don't really see it as a sacrifice anymore. I'm building something.

And this morning was part of that too. For where I am right now, staying there and waking up [unclear] might have been the better brick to put down in that wall right now. And I honestly believe it is.

07:46 — Choosing what I want to enjoy

Food is another place where this shows up for me. I've tracked calories. I've been really strict. I've paid attention to my weight, my workouts. But I don't want every meal for the rest of my life to become a math problem.

So a lot of it now comes down to choosing what I actually care about. Maybe there's a protein bar there, and I eat half instead of the whole thing. Maybe there are chips around, and I have a couple. Or lately, I haven't been eating any of them. Not because chips are bad—they are bad—or because I'm punishing myself.

Maybe I just know we're having a bigger supper later, and that's the thing I actually want to enjoy. I want to be able to have more on my dinner plate and enjoy it and not think about it, than have some unneeded snacks and then worry about how much is on my dinner plate.

I don't have to sit there thinking about blowing my diet because earlier I had that bag of chips, or had that bar, or had that hot chocolate, or whatever it might have been. That works better for me than constantly being either perfectly on track or completely off track.

I'm not giving everything up. I'm deciding which things matter more. And if you repeat those little decisions enough, obviously they start affecting how much you eat, your weight, how you feel, and how easy it is to maintain everything without constantly thinking about it all the time.

09:09 — Money and room to breathe

Money might be the easiest place to see this. There are so many things that give you an immediate reward: eating out, buying another shirt or something else you like but don't really need, upgrading something just because the better version exists. And then there's that whole idea of, "I deserve it."

I don't really like that argument. Not because you don't deserve things. You probably do. We all deserve a break. But deserving something and deciding that spending money on it improves your life aren't necessarily the same thing.

Say eating out costs a hundred dollars. If we're going somewhere for a special occasion, or if it's something we're all going to enjoy together, that's different. I'll spend money on things that matter to me. I'll spend money on the experience. But maybe this month it's just eating out because that's what I normally do.

What happens if I don't? That hundred dollars stays with me. Maybe I invest it. One hundred dollars isn't going to change my life. That's not really what matters. I built the habit of having money left over instead of automatically finding somewhere to put it and spend it. Then that happens again, and over enough time something that looked tiny doesn't stay tiny.

That's an idea in The Psychology of Money that fits this really well too. A lot of financial progress is invisible. People can see the car you bought. They can't see the car you decided not to buy. [Unclear] sees the restaurant you skipped, the clothes you left in the store, or the money that quietly went into an account.

A lot of decisions that build financial security are pretty boring from the outside. But eventually that money gives you something much more valuable than the item would have ever given you. It gives you choices. It gives you time. It gives you [unclear] some room to breathe.

10:55 — Doing work people can trust

And work is another version of this. I'm not talking about working yourself into the ground or into the grave, or giving a company your entire life because you think somebody is eventually going to notice. That's not what I mean.

It's more about being willing to put in a little extra effort when it actually matters. Maybe you're about to go for coffee, but you're five minutes away from finishing something, so you finish it. A project needs an extra hour that week, and you put it in. There are support tickets there, and you take another one even though you've already filled your quota.

A client asks you something. Instead of replying as quickly as possible, you take the time to understand what they're actually trying to accomplish. Or you read the entire email chain, because the answer probably isn't just in the last message.

None of these things should consume your life, and none of them guarantee you anything at all either. You can work hard and still get overlooked. Companies lay people off. Managers make bad decisions. AI is changing jobs, and no one knows exactly where all this is going.

But we're still building something. Over time people learn whether you're reliable. They know if you follow something through. They learn whether you're someone who tends to disappear once things get hard, or somebody who stays around long enough to help figure it out.

Then a special project comes up. Someone needs a person they trust with a client. A review happens. A promotion opens. Those little things can matter in those moments. And even if the company itself never rewards you for it, the skills don't disappear. Neither does the experience. Neither do the relationships you've built with the people you've worked with. That's still yours.

A career isn't built because you stayed late on Tuesday. It's built over years, becoming more useful, more capable, and more dependable.

12:43 — The ordinary things that add up

Once I started thinking about this, I realized there are examples everywhere. Learning is one. Half an hour scrolling on your phone isn't a disaster. I still waste plenty of time on my phone. But sometimes that half hour can be twenty pages of a book. Do that enough times, and eventually you've read a lot of books.

The same idea applies around the house. Fix the little thing while it's still a little thing, instead of waiting until it turned into an expensive thing. Make the appointment you've been putting off. Deal with the paperwork when it's ten minutes instead of allowing it to become a pile that takes an entire afternoon. For me, it takes a weekend sometimes.

Relationships probably have more examples than anything else. Sometimes it's putting your phone down because someone's talking. I don't like having my phone out when we eat out. I hate when people have their phone. We're all sitting around or eating out. We should be together. It should be people.

Sometimes you go somewhere with your wife even though staying home would be easier. You call someone. You stay for another coffee. Or in my case lately, maybe you skip that coffee because being home is what needs more attention. And that's where I think this becomes personal.

13:53 — What am I trying to build?

There's no universal list telling everyone which little thing they should give up. Sometimes getting up early is the right decision. Sometimes sleeping in is. Sometimes work needs an extra hour. Sometimes the better decision is closing the laptop. Saving money is important for all of us, but there are also things worth spending money on.

The important question probably isn't, "What should I sacrifice?" It's, "What am I trying to build?" Once I know that, the little choices start to make more sense.

That's why I don't really want to call these sacrifices anymore. Sacrifices make me focus on what I'm losing. I didn't eat something or buy something or go somewhere. I gave up some time. If that's the way I look at it, eventually life starts sounding like this miserable process where I'm constantly denying myself things and hoping someday I get a reward for it. That's not what I want.

I'd rather pay attention to what those choices are adding. Staying home more is helping me build something with my family. Changing the way I eat helps me stay healthy without having food take over my life. Putting money away gives me a future with more options. Doing good work builds skill and trust. Reading books builds knowledge.

15:05 — One imperfect brick doesn't erase the wall

And none of this has to happen perfectly. That's another reason I like the idea of bricks. If you're building a wall and one brick isn't perfect, the whole wall doesn't disappear. You put the next one down.

You eat too much one day? Fine. You spend money you probably shouldn't have. You miss the workout. You waste an afternoon. You have a bad week at work. None of those erase everything you've already built. You just continue.

And eventually I think you hit that point I've talked about before where you notice yourself. You realize the thing that used to require effort has become normal. Maybe there's money sitting there that wouldn't have been there before. You're stronger. Your relationship feels different. People trust you more. Your house feels a little different. You feel different.

There probably wasn't one specific day where any of that happened. It was built through all these little decisions that almost no one else was paying attention to.

That's what I'm trying to get better at. Not making huge sacrifices. Not optimizing every second of my life. Just paying more attention to what I'm building. Because the thing I give up right now might only matter for ten minutes. What I'm building from that decision might still matter ten years from now.

And sometimes the brick is getting up early and doing the workout. Sometimes that brick is staying in bed with your wife for another hour. This morning, that's the one I picked, and the workout still got done.

So thanks for watching. Hope you liked it. Bye.

What If AI Brought Opportunities to You? [Raw Session]

00:00 — Waiting for someone to notice

Hey, welcome back to Slow Builds. So lately I've been thinking a lot about how much opportunity still depends on somebody noticing you, and whether AI could eventually change some of that.

You might send somebody your work, apply for a job, or upload a video and hope the right person sees it. Sometimes a connection comes through somebody you know. Other times somebody just happens to be there when you do something very well.

We've built all these systems for finding people: recruiters, scouts, auditions, applications. And they all work to some degree. But being capable of something and getting a chance to do it are still two different things.

You might never get in front of a person who would recognize what you can do. You might not even know there's something worth showing them. That's the part I keep tracking back to and coming to.

And what if AI could help make those connections from things you're already doing? Something you've chosen to use that can notice a possibility and bring it to you. You still have to decide what to do with it, but maybe you won't have to know exactly what you were looking for before anything could happen.

01:20 — The kid running for the bus

Now, the picture that started this in my mind, and what made me think about it, was imagine a kid running because he's late for the bus. He's not trying out for a track team. He's just trying not to miss the bus and be late for school. But maybe he's quicker than he realizes.

And unless somebody happened to notice, he gets on the bus and his day continues as normal. Or maybe you miss the bus and you run the whole way, which is another thing. Maybe he's a marathon runner and not a sprinter. But like I said, he gets on the bus and he doesn't think anything of it. He just had to catch it. There's no reason to think much about it.

Now, one run wouldn't tell you whether somebody has unusual ability. And I'm not imagining cameras everywhere, judging kids on their way to school. But suppose he already uses something that tracks his activity, and he and his family chose to let it look for patterns in his running over time.

Maybe it notices something worth exploring. It wouldn't need to announce that he's going to the Olympics. It could just ask whether he enjoys running and help him find somewhere to try it. Maybe there's a local club he didn't know about. That's a small connection, but without it, running might stay something he only does when he's late.

And I think that same gap exists in plenty of less obvious places. Because as unobvious as that one is, there's even more that are less obvious, I believe. And that's just a simple example of someone wearing a tracker. They've got their Apple Watch, their Fitbit, or their WHOOP or something that their parents put on them to track them or to notify them or keep access or whatever. And it just happened to have an ability attached to it that could look like, “Hey, this is worth looking into.”

03:17 — Abilities we might overlook

And so in my case, somebody could be making videos in a tiny little room with almost nobody watching them. Sounds very familiar. Maybe there's something in the editing or the way they explain an idea that could be useful in work, something they never considered. They're thinking about making their next video. They might have an idea that somebody elsewhere is looking for help doing that exact same kind of thing.

Or think about a person at work who's always figuring things out when something breaks. They might—back to the video, I like my ideas. I just don't think I'm the right person to be putting them out there. Maybe I am, but I don't think I'm the right person to be editing in any way whatsoever. I do a one-take shot and I'm done.

I would like to learn and experiment more, but I don't know. So maybe there's someone out there that might eventually find my videos, or there's a tool that lets people find other people making videos, and they can help them, I don't know, team up. I'm just thinking outside the box and way off script when I do this.

But again, bringing it back to that, somebody could be at work right now, and they're the person who always figures things out when something breaks. They might not have the right degree, the right experience, or know anyone who could help them move into another role, or move up in the role, or switch jobs completely. They might not even describe themselves as a good problem solver. It's just what they do.

If they chose to bring examples of what worked to an AI, could it help them see where else those abilities might be useful?

And that interests me because we don't all get the same chances to be noticed. Where you grow up, the school you went to, and who you know can affect which possibilities you even hear about. Some people also have more time and freedom to put their work out there. Other people are busy getting through the week. AI wouldn't remove those differences, but maybe it could help someone find a connection that currently depends on knowing the right person.

05:28 — A first step that fits your life

The question then is what happens after it finds one. Because telling that person at work they're a good problem solver doesn't give them much to go on. They might say, “Okay, thanks,” and go right back to doing the same thing. What's the next problem on the list? Give me the next ticket.

What kind of work could they explore? What would they need to learn? Would they even enjoy doing it all day? That's where I'd want the help to continue. Maybe there's a small project they could try, or someone they could talk to who actually does that work. Something that lets them find out a little more before committing to a big change.

And that first step has to fit their life. If they have a mortgage and a family depending on their paycheck, a suggestion to leave work and retrain for two years might not be something they could use.

The same goes for a kid and a running club. Finding a club is useful, but maybe the fees are too high, or no one is available to drive them there. So the next question would be whether there's something nearby or support the family [unclear] know to look for.

For the person thinking about different work, it might mean finding a way to try it without leaving their current job. Those details are part of the opportunity. Without them, we could get much better at showing people possibilities they still can't act on.

I don't necessarily need an AI to tell me I have some hidden talent. I want it to help me find something worth exploring and a first step I could actually take. Don't just tell me I'm a great runner. Tell me why I'm a great runner. Give me opportunities and suggestions on how to train, where to train, and who to contact.

Same with the work. What can I do at my current job, or do on the side at home, or in a short period of time? What tests could I take? What skills could I take? Give me a problem to solve.

07:26 — Useful help needs personal context

But helping with those details would mean knowing something about the person. It might need to know roughly where they live, what time they have available, or what they can afford. And this is where the idea starts getting uncomfortable for me, because now it's getting into privacy.

The more useful I imagine it becoming, the more information I can imagine giving it. Something tracking that kid's running could also end up keeping a record of where he goes. And an AI helping someone understand their work could be given conversations or details about things they're struggling with.

We could start with a fairly simple request and gradually build a very detailed record of someone's life, all because each extra piece of information seems like it might make the help a little better.

08:16 — What I share should stay my choice

Choosing to use it would have to be the starting point. But agreeing to that first request couldn't mean agreeing to everything that follows. I'd want to know what it actually needs for the thing I've asked it to do, and whether I can still get useful help without giving it access to everything.

For me, that would mean being able to decide what the AI gets to see and what it's allowed to remember. If I ask it to look at a few pieces of work, that should be the scope of what I'd agreed to. If it needs something else, I'd want it to explain why and let me decide whether to add it or not.

I also want to be able to stop and delete what it had kept, and choose whether anything gets shared. Finding a possible connection for me wouldn't give it permission to send someone else a profile of me. I might want to explore an idea privately before telling anyone about it. I might decide to leave it alone altogether and not even pursue it.

And I wouldn't want information I shared for help quietly turning into a report for my employer, an advertiser, an insurance company. If it's supposed to be working for me, I need to decide what happens with the things it notices.

09:29 — Being good at it doesn't mean I want it

And that includes being able to say that it's noticed something real but drawn the wrong conclusion. Maybe I'm good at organizing people because I've spent years having to do it. An AI might see that and keep finding me opportunities to manage people. But that could be the part of my day I'd most like to get away from.

Yeah, I don't like meetings. But I'm okay with small groups. I'm okay with a great team. But being responsible and reporting back up is not always the funnest thing to do.

But like I said, it might know I'm great at something, but it doesn't know that that's the thing I don't like doing. Because being good at something doesn't mean I want more of it in my life. And what I've done so far isn't necessarily what I want to do next.

If I spent ten years doing one kind of work, there's going to be plenty of evidence that I know how to do it, and probably know how to do it very well. There might be very little evidence for the thing I'm interested in learning. I might be fairly bad at it right now. I'd still want room to explore.

So I need to be able to tell the system what I'm trying to move toward, even if that doesn't match the patterns found in my past. And I want that answer to actually change what it brings to me. Otherwise, I could end up with something that knows a lot about what I've done but keeps missing what I'm asking for.

Maybe there's something I dabble with on the side, and because I only get to spend very little time at it, I might be getting worse and worse, and my ability looks really bad. Or maybe there's something I do spend a lot of time, too much time, my extra time, and I really have a passion for it. But maybe I'm really, really bad at it.

So there's all these ins and outs, and I need honesty, and I need truth, and I need to give permission to certain things, but I need to control it all at the same time.

11:28 — When AI gets it wrong

So, of course, it could also be wrong about what I'm good at in the first place. It might mistake a few examples for a pattern, or overlook something because it doesn't recognize the way I do it. And I'm worried about whether certain people keep getting shown certain kinds of work. You could think you're opening up possibilities while quietly narrowing them.

A suggestion would have to stay something I can question and test. I wouldn't want to treat it as a verdict on what I'm capable of, especially if other people start trusting those judgments.

Because once getting an opportunity depends on what an AI thinks of you, there's a reason to start performing for it. You might choose work because it looks good to the system, or change how you present yourself because you think that's what it rewards. Then we've added another audience you have to impress.

And that brings me back to why I like the idea in the first place. I was imagining someone getting on with their life, with a bit of help finding possibilities along the way. I wouldn't want ordinary life to become one long audition.

12:32 — Who is the AI working for?

So I keep coming back to who the AI is actually working for. So much of my experience with algorithms has been about what they want to show me next: another video, a post, something to buy.

What interested me here is being able to ask for help finding things I actually want to explore. That would involve listening to what I want, accepting what I don't want to share, and understanding that I can turn something down, even something I might be good at.

I don't know how well that would work. There are probably problems with it I haven't even thought about. But I keep thinking about that person who's capable of more than their current situation has given them a chance to try. Maybe they don't know what to apply for, or who to talk to, or that something they already do could lead somewhere else.

I can see how a useful connection could make a difference there. Something they've chosen to use notices a possibility in what they're making, learning, or figuring out in their ordinary life. And it asks, “There might be something here. Do you want to see where it goes?”

I like that possibility. I'm not sure how we build it without slowly turning it into something else. I'd want the person getting that suggestion to still feel like the answer belongs to them.

13:53 — Closing thoughts on discovery

That's why I like the idea of silent tracking, silent noticing, by maintaining privacy and protecting the person's information. But finding trends, finding oddities that the person is showcasing or doing. And you can make suggestions. You can let them know, “Okay, you're great at playing this video game. Let's try this one. Oh, there's a tournament for that. Would you like to join for it?”

Or the running thing. I love that idea because it's so simple, and it's so easy for a person who doesn't run or do any kind of exercise, like swim or row or anything, bike. And once they have a tracker or they pass by something, it can pick up on that. And it could give suggestions. It can ask if they want to pursue that.

And I think there's ways to add nudges to this, add metrics that are private. But also, for the person that it's giving the suggestion to, it gives them an opportunity.

I think the world could become a little more open, a little more of a place that we can all explore more. Because we all get bored on a rainy day, or on a day when we don't know what to do. And we don't like wasting our time. We don't like just watching TV and binging on social media.

So going out, or going online to talk to other people, or explore new things, or try new things. I think AI has a great way to present opportunities to see where we can grow and become great at what we don't even know we're great at.

All right, thanks for watching.

You Have to Be in the Game [Raw Session]

00:00 — Being in it, not just winning

Hey, welcome back to Slow Builds.

So, we all know the saying, like, “You gotta be in it to win it.” And it's one of those sayings that sounds almost too simple, really. You hear it with lotteries, gambling, all kinds of stuff. There are a bunch of versions of it in every form, really. You gotta have your cards on the table. You gotta be in the game. If you're sitting on the sidelines, you're not playing.

But I've been thinking about it lately more because I actually think there's something in there that describes a lot of decisions I've made in my life. Not necessarily the winning parts—more probably the losing parts. And more the being in it part. That's what I believe in.

I think I've always had this thing where, if something genuinely interests me, eventually I'll want to experience it myself. I don't really want to spend ten years standing outside looking at it and wondering what would have happened if I tried that. I hate having regrets. I hate looking back on those things like that—the should'ves and could'ves.

And sometimes it's worked out very well for me. Other times it's cost me money. There are definitely things I did when I was younger that I look at now and think, probably should've done a little more research before I went all in on it. Maybe asked a few more questions. Maybe a little less confident when I didn't actually know what I was doing.

But even with that, I don't think I would want to completely remove that part of myself. Because a lot of what I know now came from actually getting into things, not just reading about them.

01:44 — Starting my first business

One of the bigger examples goes way back to when I started my first business. The company I was working for was basically a sinking ship. We were all losing our jobs, and we all could see the writing on the wall.

And I could see what most people were doing. You start looking around, find another company, get another job in the same industry, same stuff, same group of people, and you just keep moving forward. And there's nothing wrong with that. The stability, that staying in your lane—and that would've been the very safe move.

But there was an opportunity sitting there where a group of us could try something ourselves. And yes, I was naive and young. There was no point looking back now and pretending I had some brilliant business plan and knew exactly where it was all gonna go. I didn't. I knew software, I knew the work, and I knew some people. But actually running a company and finances and travelling and networking and budgeting is a totally different ballgame.

Still, I think it was basic: this company's going to go under anyway. This opportunity is right here in front of me. I can go get another job if I have to. If it fails, no loss. I get another experience under my belt. I got a little leeway before I really need to worry, basically. So why not see what happens?

So we did, and it changed the direction of my life. Not in this clean, straight line either, where I started a company, became successful, and everything worked out. I wish. It was very messy. There were times when I almost lost it. Eventually I had to bring myself back around, and I did okay.

But once I had done that, something changed. When that part of my life ended, getting a normal job wasn't automatically the only option anymore. I had already been self-employed. I've already made money myself. I knew it was possible because I'd actually done it.

So there was this feeling of, I'm already in this game now. Let's see if I can keep playing it. I can still get a better job later—better, I can get another job. I can get a real job. A nine-to-five, or work for a company, work for a corporation.

And eventually I did end up back working for a company in the end. But even that isn't really separate from everything that came before it.

04:01 — What the retail business led to

Years ago, when I also got involved in retail, my wife hated the idea. She wanted nothing to do with it. She's a little more cautious on things, so she's my guardrail. But sometimes I go a little freelance, and I'm hard to contain on that. So we went in on it. And I liked the idea, and we did it.

But retail is a beast that has ups and downs. It's constantly changing. You have a lot of employees, a lot of moving parts, inventory. So basically, in the end, financially, it was an extremely bad move.

But here's where it gets interesting. When you look back over that longer period, that business did last a long time. It kept a lot of people employed. A lot of close family members relied on it. It built a lot of relationships. Obviously, we had to deal with suppliers and customers, and it just kind of fizzled out in the end.

But one of the people I built that business with is connected directly to where I am today. I'm now part owner of the company I'm working with. And that's a relationship that came from us, my retail partner. And we turned that into something else, completely different, in the software world.

That's totally different. And you would never think that when we started a retail company, we would eventually, after losing a lot of money and a lot of headaches, a lot of pain, we would end up creating a software company. And now we're thriving, and we're doing quite well, and I'm just an employee. My wife was an employee, and most of my friends that I've got along the way are employees. So we're all part owners, part employees. So it's very awesome.

But it wasn't a straight line, and there were many downs along the way. But if I wasn't in it, what would have happened, right? And you don't always know what the return's gonna be. Sometimes it isn't the return you were looking for at all.

06:13 — Selling eyelashes with my kid

It doesn't have to be a company either. My kid wanted to sell eyelashes on Amazon, like, not too long ago. So from the retail business, I already had the know-how and the connections for the shipping side of things. So we had to figure out Amazon reselling, dropshipping, Alibaba, marketing, and all the things involved with that.

None of that turned into some massive business, but I got to figure out how those systems work. How do you find a product, fulfilment, what the margins are, how to use Amazon for selling and shipping, and figured out what goes wrong.

But I got to do some of that with my kid, and that's worth something to me. So we had an experience together.

So I think sometimes we look at experiments like that and judge them only by whether they turn into the final thing. If you try dropshipping, you don't build a million-dollar store, apparently it failed. I don't really see it like that.

If I spent an amount I could afford to lose, learned how the thing actually worked, and enjoyed doing it, that wasn't necessarily a waste of time or a waste of money. It might just have been an experiment, a learning experience.

It was definitely something I got to do with my kid, an experience we now share together and look back on fondly. And I know if an opportunity shows up again, I'm not starting at zero. I've touched it before.

07:45 — Investing without betting everything

Investing is another version of this for me. There are stocks I look back over the years and wanted to buy. Netflix was one of those, and I didn't. Other people talked me out of it. Sometimes I talked myself out of it. And looking back, you can drive yourself crazy doing that because, obviously, hindsight makes everything look easy.

I'm not gonna pretend every stock I wanted to buy would have been an amazing winner. There would have been plenty that went the complete opposite direction. I would have lost a lot of money.

But I noticed something about myself from those experiences. If there is something I'm really interested in, I believe there's something happening there, I'd rather have a little bit in it than spend the next decade watching it and wishing I had made the move.

That's different from betting everything on it. Like, I bought SpaceX exposure because I wanna be part of that. I bought Lemonade. There's another space one, Canadian-related, that I've jumped onto because I wanna see where it goes.

And any of them could turn to absolute garbage. I could lose all my money, but I'm in it to see where it goes. I'm in it because I believe in it, and I wanna be a part of it. So that's all I'm saying there. I'm not saying I know where those companies are going, and I'm definitely not saying someone else should go buy them.

The difference now is I have some capital I can allocate to things like that. Twenty-five-year-old me and almost fifty-year-old me aren't playing with the same resources. So the games have changed.

I can have some serious long-term investments, and I can also decide there are a few things where I want some skin in the game, basically, because I'm genuinely interested in seeing where they go. If it fails, I knew that was possible when I went in.

09:37 — Trying Airbnb for myself

That's part of why I'm looking at Airbnb right now. We already own a rental. We're going through a total hassle right now trying to get a tenant out and cleaning up the mess, and we've done it before. So now we're looking at, maybe we just Airbnb it and try to see what happens. And the opportunity's sitting there for us to try right now.

I've always been interested in Airbnb from the technology side, from their growth, their story, everything about it. And so now I wanna be part of the platform, see how the platform works. What makes a place perform better than others? What's the actual experience of running one? Is it worth the extra—is there extra work? Is it worth it?

I can read about it forever, watch YouTube videos, but at some point, if the numbers make enough sense and the downside is something I can handle if it doesn't work, I kinda wanna find out for myself.

Maybe a year from now I'll be sitting here saying Airbnb was a pain, and I should have just rented the place normally. That's possible. But then I'll know. It won't be always looking back and saying, could have and should have. I would have tried it. It would have been an experiment, and either it's gonna work or it's gonna fail. But either way, I know because I lived it, and I did it.

I call these things adventures. Everything to me—life's an adventure. Good or bad, it's an adventure. So it's another story to tell, and that's something I'm putting in the book because I really believe you gotta look at life as an adventure. Because otherwise it can be very depressing.

11:13 — Why I'm finally getting a Tesla

So again, another one like that is Tesla. It's obviously different because that's not—I kinda lost where I was going—it's not a business.

So Tesla's different because I wish—I didn't invest in it back in the day. I invested in it now. I've always wanted one. There was a lot of ups and downs, worry, concerns. But now, you've seen my other videos, I hope. I'm a believer.

There is a future with AI, with autonomous driving, driving becoming a utility, gas, solar, everything you can imagine. I believe it's the obvious winner. I believe it's the obvious choice—or maybe not the winner, but it's the leader of the pack. And I strongly believe that.

So that's why I'm finally gonna get one. That's something I've always wanted for years. I follow the company, follow technology. I watch EVs, keep a close eye on it, and even to the point where I always figured plug-in hybrid is what I wanted. But no, all in, all or nothing, basically.

So I'm getting one, and I'm excited to actually live with one and see what it's like instead of having an opinion just from the outside. That's part of this for me too. Not everything has to turn into money. Sometimes I just want the experience. And fortunately I'm at a point now where I can afford some of those experiences in a way that I couldn't twenty years ago.

Now, side note, I have a sixteen-year-old Jeep, and my wife has a fifteen-year-old Pathfinder, and we have a little tiny horrible car of a Kicks. And so you can tell where I'm going with this. I don't spend money on vehicles.

So to me, buying the Tesla, I do have to replace something. I believe it's a car I will buy that reduces the maintenance, the gas. Obviously, you heard what I drive—not easy on gas. So for me, it's buying something to replace that with little maintenance, but future me. And I want to drive an AI app while it drives me.

So anyway, I digress, and I'll just get back to the script.

13:46 — Learning AI by using it

So AI might be another clear example of me wanting—if you're not in it, you gotta be in it. So I use AI for everything now. Not because I think AI is perfect. The more I use it, the more problems I find with different models and different ways. But I want to understand what the technology actually changes.

I don't think I can really understand that by reading articles all day. I'm a developer. I can actually put the work into it. I can use it in my work. I can build with it. I can use it for writing, planning, research, these videos, automation, whatever I'm doing. Then I can decide where it's useful and where it's nonsense based on actually living with it.

14:28 — What YouTube is giving me

And like I said, YouTube is kind of the same here. This channel is not moving fast. I'm not sitting here pretending it is, but I'm enjoying doing it. I'm learning what it's like to make videos consistently. I'm finding out what I like to talk about.

I'm getting more comfortable. Not really. I waited till my family left to go for a walk so I could do this. Just turning on the camera isn't such a bad idea. It doesn't hurt me so much anymore.

But maybe the channel eventually becomes something a little bit bigger, I hope. But at the rate it's going, I don't think it will. I think it's just gonna be a place for me to vent and speak and put my thoughts out there.

But if I had spent the last year thinking about starting YouTube instead of actually starting it, I would know absolutely nothing more than I did before. Now I know what it feels like, and that matters to me.

15:22 — Can I survive being wrong?

The thing I do think has changed is how I get into these things. When I was younger, I was more naive. Something looked interesting, and sometimes that was enough. Now I'm more critical. I research more. I question things more. I try to understand where the catch is.

What's this going to cost? What happens if I'm wrong? How much time does it actually take? What's the downside that I'm not seeing because I'm excited about the idea? I let things sit a little longer too.

I don't think that makes me less willing to try. Hopefully it just means I'm a little better at deciding what kind of risk I'm taking. Because I don't think the lesson from any of these is that everyone should go take some giant risk. That's not what I'm saying at all.

The way I look at it now is probably closer to this.

I can survive being wrong. If I put money into an investment and it goes to zero, is that going to damage my life? If I try Airbnb and it doesn't work, can I turn the place back into a regular rental, or can I just sell it?

If YouTube never goes anywhere, am I still okay with the hours I spent doing it? Yeah, I think I am, because it's a venting place and just content I can use. I do want to finish my book, so there is content coming from the book into this, into the book. So there's something there.

If I buy something I wanted and it doesn't live up to expectations, can I live with that decision? That's a big one. So I'm more careful what I buy now.

And that's a better question than simply asking whether something's going to work, because I don't know if it's going to work. Nobody does.

16:54 — I'd rather find out

So maybe “You gotta be in it to win it” isn't quite the right way to say it, because winning isn't really what I'm talking about. Some of the things I've been in, I've lost.

I've lost a lot. I lost money. I've wasted a lot of time. I've made a lot of bad decisions, ruined relationships. I've done a lot of stupid, stupid things. There are things I would do completely different now.

But they've also connected me to people, taught me things, opened other opportunities, and given me experiences I wouldn't have had if I stayed on the sidelines. And some of those benefits don't show up until many years later. You may not even notice the building blocks you're laying down, the path you're laying for yourself.

And I think that's the part I've been noticing. Maybe because I am getting older and seeing my decisions now play and come to fruition. I'm still interested in what's next. I'm just a little more careful about how much I'm willing to put on the table.

But if something genuinely interests me, I've done my homework, understand that I could be wrong, and I can afford that downside, I still wanna be in the game. Because I know myself well enough at this point. I'd rather find out.

So, thanks for watching. I hope you liked it. Bye.

Is AI Making Me Think Less? [Raw Session]

00:00 — When asking AI becomes the first step

Hey, welcome back to Slow Builds.

I've been thinking about something with AI that feels a little uncomfortable, mostly because it involves how I'm using it myself.

I use AI to help me with writing, write these scripts. It helps me format it, segment it, do the websites. It helps with coding, helps with the YouTube channel, like when it comes time to thumbnails, titles, descriptions, comments, replies. And sometimes just figuring out what I'm trying to say, and for text messages, emails. And I get a lot of value from that.

But I've started wondering what happens when asking AI becomes the first step.

We did go from an era of when we had to look everything up. My friend and I were talking a while ago about how we used to have to go to the encyclopedia to look something up. But then that turned to AltaVista or—Lycos, all the old websites, and the original Yahoo. And then Google changed that.

But now AI has become the first step in almost everything. Before I've tried to explain the problem, before I've decided what I think, before I've even sat with the question for a few minutes in my head, trying to figure out what I think, what I think the answer is, or what the outcome is, or trying to remember something from the past.

I'm not saying everyone is going to forget how to think. I'm wondering about something quieter: whether I could get so used to having help with the first pass, the first instinct, that I stop wanting to do it myself.

01:49 — What would AI limits actually measure?

The easiest comparison for me is phones. They became useful enough and easy enough to keep reaching for that we started putting limits around how we use them. Screen time, app time, app limits, focus mode, sleep mode, Do Not Disturb. All these things are ways of putting a little friction back into something we've made incredibly convenient.

I wonder what the equivalent looks like for AI. Are we going to see that in AI? Is AI going to tell us to take a break? Is AI going to say, "Maybe you should go read this, go find this, go here, step away"?

Maybe it's going to do this. Maybe we can put limits in it. Maybe we can, just like the screen time, or kids, or anything else.

Because it may not be about how many minutes I spend using it. I could spend an hour with AI questioning an idea and thinking really hard, or I could spend thirty seconds accepting an answer I barely understand.

The time alone wouldn't tell me much. I'd need to look at what I was actually doing during that interaction.

03:02 — This video started with AI too

And I need to be clear: I'm not standing outside of this. I use AI for these videos. I use an idea. We build out on that idea. We create a script for it. And then after the script is done, then we see if there's a title, a description, first comment, and then a thumbnail idea.

Then we move on to rewriting the script, because I'll read it, we tweak it, we change it. And then once the videos are up, AI helps me convert that for the website. It helps me do the thumbnail. Now I'm using it to help me do Shorts, because that's a new thing that I've discovered, and I kind of like them. Hopefully a few come out of this one.

But anyway, sometimes I bring a thought that's barely formed, and I ask it, "Help me work out what's there." So yeah, this video started that way.

The rough thought was something like, "AI causes people to lose reasoning." And even saying that now, it sounds more certain than what I actually mean.

I don't know that I'm losing my ability to reason. What I'm trying to understand is whether the convenience could change my habits. Those are different claims, and working through that difference is part of the thinking.

When I read a draft and realize it's saying something I don't actually believe, I have to stop and correct it. Sometimes I reject a whole direction. Sometimes the wording sounds good, but it makes the idea too certain or misses the part I was actually interested in. And that's still reasoning.

So I don't think it would be honest to say that using AI means I've stopped thinking. The question is whether I'm staying involved, and whether I'd notice if that started to change.

05:06 — A polished answer can feel finished

One thing that makes this difficult is how quickly AI can give a thought a finished shape. A rough idea goes in, a clear explanation comes back with a beginning, a middle, and a conclusion. And that can be useful.

Sometimes seeing the idea written out is exactly what helps me understand what's wrong with it. But I think there's also a temptation to accept the shape because it feels complete. The sentences connect. The explanation sounds reasonable. Nothing immediately jumps out as wrong.

And suddenly I'm reviewing the answer it gave me instead of working out how I would have approached the question myself. And that doesn't automatically make the answer worse, but it can influence where my thinking starts and which possibilities I consider.

If it gives me three options, do I seriously consider that there might be a fourth? If it frames something as a problem, do I stop to ask whether I agree with that framing? Or do I just start improving what's already in front of me?

That's the part I want to pay attention to. AI can make weak thinking look finished. And I don't want to confuse a clean explanation with having understood something.

06:23 — What do I want to stay good at?

I also think there are different kinds of work happening here, and I don't want to lump all of them together.

If I know what I want to say and AI helps me shorten a sentence, that's one thing. If I'm trying to make a decision and I ask what I should value, that's something else.

I don't need to personally struggle with every title, description, or every piece of routine writing to prove I'm still capable. Some of that work is exactly what I want help with. The harder question is which parts I actually want to remain good at myself.

If I care about explaining my ideas, then I probably need some practice explaining them. If I care about judging an argument, I need to do more than recognize that it sounds convincing. And if I'm making a choice that affects my life, I want to understand why I'm making it.

It doesn't mean doing everything alone. It means being a little more deliberate about what I'm handing over.

07:21 — Working through uncertainty or making it disappear

Because the early part of thinking can be uncomfortable. You don't quite know what you mean. You try to explain it, and halfway through you realize the pieces don't fit. You write something down, read it back, and discover you've made a claim you can't really defend.

I don't enjoy all of that. But sometimes that's where I find out what the actual question is.

AI can help with that process. It can ask something I hadn't considered or show me a contradiction I wasn't seeing. And it can also give me a smooth way around the discomfort.

And I'm not sure I always know which one I'm asking it to do. Am I asking for help working through the uncertainty, or am I asking for something that makes the uncertainty feel finished?

Those could look very similar from the outside. In both cases, I end up with a readable answer. But I might come away understanding very different amounts.

08:26 — Losing the urge to make my own first attempt

The part that worries me most is the possibility that I stop wanting to make my own first attempt. Because my first attempt is probably going to look worse. I'll be slower. It'll have holes. I'll repeat myself.

AI can give me something that looks much further along almost immediately. Once that's available, starting from scratch can feel unnecessary. And sometimes it is. It is unnecessary. But I don't want speed to make those decisions for me every single time.

There are thoughts I like to sit with before somebody or something starts organizing them for me. I might take a different direction. I might realize I'm asking the wrong question. Or I might end up in roughly the same place, but understand how I got there.

I think there's value in that, even when the finished result doesn't look more impressive.

09:17 — Can I explain why I agree?

So for me, a useful version of AI isn't necessarily the one that does the least. It's the one that helps me understand more.

Sometimes that means bringing a rough thought first. Even a few sentences about what I currently think, what I'm unsure about, and what I'm trying to work out. Then I've got something to compare its response against.

Did it actually address my concern? Did it change my mind? Or did it just say something more confidently than I did?

Other times I might need help getting started. I don't think that should somehow disqualify the thinking that happens afterwards. A draft can give me something useful to push against. But I want to go beyond whether I like the wording.

Can I explain the main idea without reading it back? Can I say why I agree? Can I point to something that would make me reconsider?

Those questions seem more useful than counting how many words I wrote myself. Because changing a few sentences doesn't necessarily mean I've explained the argument. And accepting a suggestion doesn't necessarily mean I haven't.

What matters is what I understand and decide along the way.

10:34 — The kind of help I want from AI

That's also the kind of support I want from the tools. Sometimes I want a direct answer. I don't need a lesson every time I ask for help.

But when I'm trying to understand something, I'd like to be able to say, "Don't finish this for me yet. Ask me what I think. Help me find the gap. Show me the part I haven't considered."

If I'm making a bad decision, maybe start with what matters to me before producing a list of advantages and disadvantages. Because a neat list can still miss the thing I care about most.

And I wouldn't want that extra friction forced into some interaction. I'd probably get annoyed and turn it off. I want to choose it when the thinking itself is part of what I'm there to do.

Sometimes I'm trying to finish a task. Sometimes I'm trying to become better at something. I don't think those situations always need the same kind of help.

11:28 — I still live with the consequences

There's another reason I keep coming back to this. When I use an answer to make a choice, I still have to live with what happens afterwards.

The explanation might be clear. The advice might even be good. But I need enough understanding to recognize when it doesn't fit my situation, or something changes, or when a detail I left out of the conversation turns out to matter.

I can ask another question at that point. But I still have to notice that there's a question to ask. That's part of the process I don't want to drift away from.

11:58 — Whether I'm still part of the process

So I'm going to keep using AI. Obviously, I find it useful. It's a powerful tool. And I don't think doing everything the harder way would automatically make me a better thinker.

But I want to be more aware of what kind of help I'm asking for. Did I come away with a better understanding? Can I explain why I accepted the answer? Was there room for me to disagree with it?

I don't have a perfect boundary worked out for this. I'm making this video with AI. Making this video with AI doesn't resolve that tension. It gives me somewhere to pay attention to.

Because I don't think the goal is to prove I never need help. I want the help. I need the help, obviously. I just want to keep practicing the judgment that lets me decide what to do with it.

Maybe that's the line to watch. Not whether AI is in the process, but whether I still am in the process.

13:00 — I noticed I was reading AI's words

As you can see in this video, I was reading pretty much what AI put in front of me. And going through it, I noticed that I was letting AI write these words. I did tweak, I did change a few of them before we went live, but I wanted to get this video out because I really do think that a lot of us are allowing AI answers to dictate what we do, how we think, what decisions we're making, what choices we're making, blindly in some cases.

Because AI is really—depending on which model you use and what your instructions are and how you have it set up—AI is very good at convincing you you're always right. You're never wrong. You're the best. You're awesome.

And it doesn't really push your boundaries. It doesn't really—well, it does if you know how to use it, if you use it right. But if you're a person that needs that reassurance or are afraid to make decisions, and you're letting it do it for you, then you're losing your ability to make your own choices.

And you're relying on a tool that doesn't know your entire life. And we talked about that in other videos. It doesn't have the complete picture of you. It doesn't know if you have struggles or problems or anything like that. It all depends on what you feed it and what you give it and what it has access to. And it can direct you in any way.

And so we have to be careful and keep our sanity, keep our humanity in it.

And yeah, thanks for watching. Goodbye.

AI Can Make Careless Developers Look Productive [Raw Session]

00:00 — The people using AI

Hey, welcome back to Slow Builds.

I've talked before about how I'm not really scared of AI anymore. I'm more scared of the people—people around AI, people making decisions and not understanding, or people looking at it from a different point of view. Basically, just people not understanding what AI can do, and they're the ones making the decisions for how it's going to be used. And that really scares me, and that still scares me quite a bit.

But specifically lately, I've been thinking about almost the complete opposite problem: people who do understand AI, or at least understand it enough to know how to use it.

And because I come at almost everything from the perspective of a software developer, an architect, just a developer in general, the group I keep thinking about is developers.

00:57 — Capable developers who don't care

And maybe the easiest way to say it is, I'm starting to get scared of bad developers using AI.

I wanted to use the word lazy, but I do have videos and I have other ideas where I want to show how I'm lazy, how I cheat with AI, how I use AI to be lazy. Just to help me get more done and remove a lot of the friction and low-level work to allow me to focus and be more clear-minded on what I want to get done. So lazy isn't the right word.

But bad developers—that kind of fits the mould I'm thinking about.

And I don't necessarily mean someone who can't write code. They might be a perfectly capable developer, probably an expert developer, who worked their way up, who have a great career.

I'm talking about someone who doesn't really care about what they're putting out. They care about closing the ticket, getting the PR merged and getting through a sprint, and just looking productive. Keeping their job, basically, and getting promoted. Whatever their motivation happens to be, the actual software is almost just secondary. They don't care about it.

And AI is becoming incredibly good at helping someone do something like that.

02:15 — AI used to require more involvement

I didn't really notice this problem before because, first, AI wasn't good enough yet. And honestly, it still isn't completely there.

Although with new models—I said I moved away from code. One of my videos was about how I'm not coding as much with it anymore, and it was burnout and fatigue and things like that. But with the new models, especially with OpenAI's new model, I feel completely comfortable allowing it to take the reins. I'm still guiding it. I'm still using it. But that's another video altogether.

But even a year ago, if I wanted AI to build something, I had to be involved. Really involved. I had to explain what I wanted, correct it, redirect it, look through the code, tell it something was missing, run it, and just find another problem and just recycle, repeat.

And there was this constant interaction between me and AI. And because of that, I was still very much the developer. AI was helping me, sometimes helping me a lot, but I was still driving it. I still needed to understand what we were building. And if I wanted something I was comfortable putting out, putting my name on, I couldn't really disengage.

The technology almost forced me to stay involved. And I think that protected us from some of these problems.

03:43 — When AI starts feeling like another developer

But these newer models, like I just said, they're getting extremely, extremely great. They're starting to feel different to me. And this is actually what made me start thinking about this and what I'm scared about, because I'm impressed so much by these new models and what they're putting out.

I'm very positive about where AI is going. I'm always optimistic and excited because I use it constantly. But we're getting to this point where I can give AI real development work, and what comes back feels more and more like another developer on my team. Not a little coding assistant, not autocomplete—a developer.

I explain what I need, give it access to the codebase, let it work through the problem. And increasingly, I get something back that actually works. And that blows my mind.

But there's also something a little uncomfortable about it, because I'm getting closer to being able to sit back. I can almost do nothing. We're not completely there, but I can see it from here. And weirdly, that's when I started getting more concerned.

Because I still look at the code. I still find things. Maybe it missed a test. Maybe there's a security consideration that wasn't handled. Maybe the happy path works, but there's failure conditions that nobody thought about. Maybe we need another guardrail. Maybe the code works today, but I don't like what it's going to mean six months from now.

And those are things I know to look for. And more importantly, I want to look for them, because I care about what I'm putting out.

05:14 — Working code can still hide problems

But here's the part that started bothering me: a lot of those problems don't stop the feature from working.

The ticket can be completed. The demo can work. The PR looks impressive. The code can still get merged. It's good enough to pass.

And that's a very different problem than AI producing obviously bad code. When the code breaks immediately, at least I know there's a problem. And that doesn't mean it's easy to fix, but I know it needs attention.

What worries me more is code that's convincing enough to get through, to get past. The feature appears to work. The ticket gets closed, and nobody bothers looking. They don't look deeply at it. They don't go beyond that. The code review passed because AI is doing the code review. AI wrote the code, so it knows what it's looking for.

06:03 — Taking ownership of what I build

And maybe part of this is just how I look at software. When I build something, I feel like it's mine. Even when I'm building for someone else, it's something I made.

I treat it like I built something physical. If I built a table, I would want the table to actually be solid. I wouldn't want someone to put something on it and have the thing collapse. If I worked on a car, I'd want to know the thing was safe and it'd run. If I built a house, I wouldn't want to hide a bunch of problems behind the drywall because nobody could see them.

Software feels the same way to me. There are users on the other side of this. There's data. There's security. There are people depending on these things working. And I want to be proud of what I put out.

I'm lucky with the people I work with. Honestly, I believe the developers around me care. They care about the product. They care about the company. They care about what they're putting out.

So maybe that sheltered me from thinking about this aspect of it until now.

07:03 — What companies reward

Because that's obviously not every development environment. There are developers who don't care about their product. Maybe they hate the job. Maybe they're burnt out. Maybe they don't believe in the company anymore. Maybe they're just there for a paycheque.

Or maybe the company itself has created that environment. They're measured on output. How many tickets? How many bugs are fixed? How much code was pushed? How much did they ship?

And I don't necessarily even blame the developer in every situation.

If you're sitting inside a massive organization and you're constantly being told you need to produce more, you're going to find ways to produce more. I've been there. I've been a consultant. You know how to push code. Show up. Punch your ticket. There's ways around it. And if you're just in it for the paycheque, you're going to find ways to make yourself look productive.

And now we have this tool that can dramatically increase how much you produce.

07:56 — Three careful changes versus fifteen quick ones

And this is where I think it gets very interesting. Imagine two developers.

One of them uses AI, but they're still going through everything carefully. They're thinking about the architecture, the testing, the security. They're thinking about weird edge cases. They're questioning what the AI is giving them back. And maybe they finish three significant things.

Then another developer using AI completely differently. They generate it, run it, looks good, push it, ticket's done. Generate it, run it, push it, next ticket. And they finish fifteen things.

Now go a couple levels above those developers. Now go above and higher. Go to the next level of developers in that scenario. Someone is looking at the numbers. Their manager's looking at three compared to fifteen.

Who looks productive? Who looks like they embraced AI? Who looks like they're performing? Who gets recognized? Maybe even who gets promoted?

08:54 — When careful developers start looking slow

And that's where this stops being about one developer, because everyone else is watching too.

If fifteen becomes possible, three starts looking slow, even if those three things were actually engineered better. And then another developer starts doing the same thing. Then another. And eventually AI-assisted output becomes the baseline.

Management sees how much faster things are moving, so expectations increase. Now everyone needs to move faster.

And the careful developer can actually start looking like the bad developer, which is a sad thing. You could be the smartest person in the room, but still feel like the dumbest.

And that's the cycle that worries me, because now we're creating an incentive to understand less. Not intentionally. Nobody sat in a meeting and said, "Let's make our developers care less about software." But that's potentially what the incentive produces.

09:45 — The software people depend on

And then you go to the thing about where the software lives. I'm not talking about some little side project no one uses. Think about banking, healthcare, insurance, transportation, any government system, massive corporations and infrastructure. The boring software that quietly runs huge parts of our lives and our environment and our communities and the world, in a way.

Those systems can have hundreds of thousands of people touching them.

People come and go. Teams change. Companies reorganize. Layoffs, hires. And the code stays.

Now imagine we're generating more and more of that code at a speed where fewer and fewer people really understand the whole thing, or even care. That's where I think the bigger problems come into this. It's bigger than just whether AI writes good code.

10:35 — I'm still using AI more

And I don't want the takeaway from this video to be that we should stop using AI to write software, because I'm doing the exact opposite. I'm using it more. And based on what I'm seeing, I'm probably going to use it a lot more. I already am. I know I am.

It's making me better. It's giving me more. It's making me be more productive. It's allowing me to look at things differently and expand what I can do. It's letting me build things I couldn't build as quickly before.

And it's taking away a lot of that tedious work. It's incredible, and that makes this complicated. I don't want AI to become less capable. I want it to become more. And everyone is, and it's going to happen no matter what.

The easier it becomes for me to remove myself from the process. And I don't know that removing myself is always the thing we should be trying to achieve.

11:25 — Responsibility doesn't disappear

Maybe that's actually where my thinking is landing at the moment. As AI becomes capable of doing more of my job, my responsibility doesn't necessarily decrease. Maybe technically it has to increase.

Because eventually writing code might be the easy part. Generating another thousand lines might not even be that much. Understanding why those thousand lines exist, what we're doing, what happens when they fail, what they're exposing, and whether they should exist in the first place—maybe that's where the actual job moves to.

And that's where I talked about AI fatigue, because my job's changing. But I think as we get deeper into this, as we move forward right now and these models change and how this is happening, that fatigue is going away. And then I talk about burnout, but we're all falling into place, I think. We're learning our new roles.

And so I think I'm scared of AI writing code. I'm definitely not scared of AI replacing the act of typing code.

12:31 — I still want to know what I'm putting out

So let me back that up. I'm not scared of AI writing code. I'm definitely not scared of AI replacing the act of typing code.

I'm starting to think the thing that scares me is AI getting good enough that somebody can produce convincing, working software without really caring about what they produced. And worse, we might reward them for it, because from the outside they look incredibly productive.

And maybe AI isn't going to create bad developers. Maybe it's just going to make it a lot easier to be a bad developer.

And I don't really know where that leaves us yet, because I'm still going to use it tomorrow. I'm going to use it tonight. I'm still going to give it more responsibility. I'm still excited to see how good it gets.

But I think I'm going to keep looking at the code. Because at least for now, if my name is attached to it, I still want to know what I'm putting out.

All right. Thanks for watching. Bye.

Could AI Recommendations Make Your World Smaller? [Raw Session]

00:00 — Recommendations are getting almost too good

Hey, welcome back to Slow Builds.

I've been thinking about recommendations lately. Not because—obviously recommendations aren't bad. You do get bad ones, but actually, again, like the complete opposite: how good recommendations are getting now. How the ones that are being served up to you, and what you're being shown, are actually fitting what you're looking for. Or unexpectedly, it's what—magically, it's almost like you were thinking about it and something heard you, and then it pops up in your Facebook feed or your X account or shows up in your search.

It feels random, but I know it's not. But the recommendations are getting so good that it feels eerie in a way.

YouTube is getting pretty good at figuring out what I like to watch. Apple Music, really good at figuring out my next listen, what my favourites would be. Or it's like, you know, play this artist and similar artists and similar songs type thing. And it works really well. I'm very impressed with it.

Amazon's pretty good at showing me, especially when Amazon Prime Days come around and stuff. It's really great at showing me recommendations of things I might be interested in, things related to what I've already bought. And it takes a lot of guesswork out of me.

It's bad. It's good in that situation. It's bad because it shrinks the wallet and it adds clutter to my life. It's good because it helps me learn control, but it also helps. A lot of times useful things come out of it.

01:43 — AI can understand why I like something

And now AI—and I know AI is in the back of that a little bit—but AI is taking it further, like much farther. Because instead of just looking at what I've clicked on before, I can actually have conversations with it. I can tell it what I like. I can tell it what I don't like. And it remembers everything about me and everything I did.

Eventually I could probably just say, "Find me something to watch tonight," or, "Give me a book I'd really like." Even, "I'm going away for five days. Plan me a trip."

And that's a pretty good experiment. It's an app idea I had many years ago. I have a three-day window or a five-day window, like a random window. It's this time of year. I'm flying from this location. I could drive if possible, and these are the people coming, and these are what everyone likes. Find me the best deal.

It was an idea I had a long time ago, but now with AI it pretty much seems like it's very possible.

02:50 — Could getting exactly what I want limit me?

But I start wondering if there's a downside to getting exactly what I want all the time. Because if something gets really good at predicting me, does it also start limiting me?

And that's a different way to look at it, because recommendations aren't new. We've had them forever. Netflix recommends the next watch. Spotify builds playlists. YouTube fills my homepage. And sometimes it's great. I've definitely found things that way.

But those systems have always felt a little dumb in a way. You know, very rigid. You watch one video about fixing something on my Jeep and suddenly my whole thing is filled with Jeeps. Jeep stuff, overlanding, [unclear] soft tops, whatever.

Searching for hotels somewhere, and now every ad is about that location. It could be about that hotel. It could be a trip. But mostly it's around, like, "Oh, you're planning a trip to San Antonio. Well, here's everything about San Antonio: what to do, where to go."

They see behaviour, but they don't necessarily understand why you did it. AI is changing it and has changed it a bit, I find, because now I can explain myself.

I can say, "I like this book, but I don't like this part," or, "I usually like these kinds of movies, but I'm tired of watching the same thing right now."

That's a very different recommendation system. It's not just watching what I do anymore. I'm helping it understand why.

And if these systems keep getting better, I think they're eventually going to know my preferences extremely well. Maybe better than I know them myself, because they'll remember those nuances, those little nitpick things that I've come up with that I might forget. They might forget that I don't like a certain type of sheet at a hotel or a pillow made a certain way, or I need two pillows rather than one. I don't need it. I'm just giving you an example here.

But it would remember those things, and it would almost feel like a tailored concierge in a way.

04:47 — The recommendation loop

And this is where I think it's getting interesting. Let's say AI figured out that I like a certain kind of music, so it recommends more of it. I listen to that. Now it has even more evidence that I like that kind of music, so it recommends more. I listen to more and the prediction gets stronger.

That's a loop, and there's nothing necessarily wrong with that. I'm getting music I enjoy. The system is doing exactly what I asked it to do.

But after a while, I wonder what happens outside that loop. Because the system isn't necessarily showing me the entire world. It's showing me the part of the world that has the highest probability of keeping me interested.

And every time I respond positively, I'm helping reinforce that version of myself. It starts becoming, "You liked this before, so here's more of it." Then tomorrow, "You liked more of this, so here's more."

Eventually, how much of what I'm seeing is actually me choosing? And how much of it is a system getting increasingly confident about what it thinks it knows about me?

05:45 — What happens when I change?

There's another part of this that bothers me a little bit. People change. My interests aren't the same as they were ten years ago. There are things I like now that the older version of me probably wouldn't have cared about at all. And there are things I used to spend a lot of time on that barely interest me anymore.

That's normal. But an AI is going to have history, potentially years of it. It might know what I've watched, what I've read, what I've asked about, what I've bought, and what I've ignored.

So what happens when I start changing? Does it notice quickly, or does the old version of me keep influencing what the new version gets shown?

I don't really know. I don't think any of us know what's going to happen. Maybe these systems will be incredibly good at detecting that.

But there's something strange about having your past preference constantly helping decide what your future options look like. Because sometimes I don't know that I'm interested in something yet. There's no history for that. There's nothing to predict that.

06:43 — When AI starts shaping what I try

And this gets bigger once AI moves beyond recommending music and videos and purchases. This is the part I'm finding extremely interesting here.

Because imagine I'm planning that trip. I could give AI everything it knows about me and say, "Build the perfect five days." It might know I like walking, all kinds of food. I like activities, things to avoid, and those kinds of hotels or Airbnbs, what my preferences would be.

And that's incredibly useful. I would use it. I'm not saying I wouldn't, and I 100 percent will use it, and I still want to build it.

But if I do that every time, I'm basically asking AI to keep recreating vacations, variations of trips I've already enjoyed.

Something like books or movies, hobbies, or even people. We've already seen technology recommend people to follow, communities to join, things to learn. Eventually AI might help decide where I go, what I try, what I read, and who I even interact with. Not because it's controlling me, because I'm asking it to help. And that's what makes this a little bit different here.

I don't think this requires some evil algorithm trying to manipulate everybody. It could probably—well, there's one company I believe would do that. It could happen with a system that's generally trying to help you.

If I ask, "What's the best option for me?" the AI should probably use what it knows about me. That's what makes the answer personal. But "best for me" usually means based on the person I already am. My existing preferences, habits, history, maybe even my biases.

And I don't always want those reinforced. Sometimes I probably need something that doesn't fit. Something I initially don't understand, might even dislike at first. Because that's part of how interests change. That's part of how growing and opinions change.

And I don't know how you optimize for that. How does an AI know when to give me what I'll probably like and when to give me something completely outside of that?

08:51 — A discovery mode for AI?

Maybe eventually this becomes a setting. That's an interesting point, because it is a system. It is code. It is ones and zeros. So a toggle, a setting, a threshold, a temperature, anything like that is possible.

So I don't know. Maybe you tell your AI, "Don't give me the obvious answer," or, "Show me something outside my normal interests." Maybe basically a discovery mode. That'd be fun.

Because I don't think personalization itself is the problem. I want personalization. If I'm asking AI for help, I don't want it pretending it knows nothing about me. That would throw away one of the most useful parts of technology.

But maybe there's a difference between "know me" and "keep giving me more of me." Those sound similar, but I don't think they are. One helps the system understand where I'm starting from. The other could potentially keep me there.

09:41 — From knowing me to influencing who I become

That's probably the strange thread running through these last few videos. In the first one, I was wondering whether AI can really know me from the data it has. Then I started thinking about how every AI actually knows a different version of me. And now I'm wondering about what happens when those versions become good enough to start guiding me.

Because eventually this isn't just about whether AI understands who I am. It might start affecting who I become. Not dramatically, probably not in the same science fiction way. Just slowly, one recommendation at a time. A choice made easier, options moved to the top, one thing I never see because something else was predicted to fit me better.

And maybe most of the time that's completely fine. Maybe it's better for me. I just don't know yet until we get there. We can't really think that one through until we see how society moves with this.

I use AI every day and I want it to know me better. That's part of what makes it useful. But I don't think I want every decision optimized around the person I already am, because I'm still changing. I'm still finding new interests. I'm still changing my mind about things. And sometimes I don't know what I'm looking for until I find it.

So maybe the question isn't, "Can AI predict what I'll like?" I think eventually it'll be extremely good at that. It already is. Maybe the harder question is, "Can it know me really well without trapping me inside its prediction of me?"

Can it recommend something that's technically wrong for me today, but might become part of who I am tomorrow?

I don't know. But I think that's a much more interesting version of personalization than just getting better recommendations.

11:26 — Unscripted closing thoughts

The more I read about—script is over. Thanks for watching. But this one, I almost didn't do this one because it was mixed with the other ones too much. But going through it now, and even ending on a shorter video, this one really feels like it hit home here for me.

Like, are we—I don't want this to move. I just finished reading 1984 also. But I don't want to see this one as being creepy, Big Brother, society's pushed to one direction through what we're fed type thing.

But I do believe we need to keep an open mind. We have to question everything. We have to find ways. A good AI, a good prediction system, a good recommendation system is going to pull on other users, hopefully, that have similar interests, but are ones that are outside of the norm that I'm normally used to.

And I hope there's ways that we can build on this. And I think a lot of really interesting things are going to happen. Again, exciting times. I can't wait to see where this thing—every day changes, and I'm so excited.

All right, thanks for watching. Bye.