Launch-in-a-Week Hype Culture is Killing Discipline
Why Skipping Research, Critical Thinking, And Self-Control Can Make You Build Faster, But Think Worse
Hello everyone,
We are pretty much in the middle of May. Holy moly.
Where did the year go? 2026 has gone by fast, and we are moving at light speed.
Well, it has moved fast for me, at least. It has been four weeks since I gave my TEDx talk, so hopefully the video should be out soon. I’ll make sure to share it with you once it is.
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Today, we have the honor, once again, of having Abbey Jackson as our guest. You already met her in our collaboration: Today’s Walk Is For Tomorrow. There, she shared her own idea of discipline, which boils down to doing the hard things for tomorrow’s sake.
In today’s issue, we get a little deeper into her mind.
The topic is critical thinking: why the rising culture of launch-in-a-week is threatening our ability to keep up and return to what we care about. How getting trapped in a get-rich-quick version of building what matters is weakening our ability to learn, and ultimately, to think.
I’ll let her take it from here.
Let’s dive in.
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Open any feed right now and you will find someone who built an app in a weekend. Someone who launched a SaaS in 48 hours using AI. Someone who went from idea to product in a week and is already talking about what is next. The content is everywhere and the message is consistent: the tools are so good now that the hard part is basically gone. Just prompt your way to a product.
I want to talk about what this culture is actually teaching people.
Because here is the thing: the hype-driven approach does work sometimes, let’s be honest. There are founder-led products that succeeded entirely on founder vision, speed, and luck. So I am not here to tell you that launching fast is always wrong. What I am here to talk about is what happens when skipping the thinking becomes the default, when it becomes habit, when people stop doing the work not because they made a strategic decision to move fast, but because everything around them is telling them the work is not necessary anymore.
And I see it constantly. I run a free course for people who want to become app founders and two very different groups of people are finding me right now. The first group is hungry for the real thing. They’ve been lost in the noise, the launch-in-a-week hype, the AI-built MVPs full of bugs and bad UX, the overnight success stories, and something in them knows it does not add up. They want to understand how product development actually works. They want to do the research. They are willing to go slower because they understand that slowing down (a bit!) now means not rebuilding from scratch in six months.
The second group is harder to help. They come in wanting AI to do all of it. Not to assist their thinking, but to replace it entirely. Their first question is usually some version of “Can I just use AI for this part?” And I get it, because the tools are genuinely impressive and the promise is enticing. But here is what I have learned from watching both groups: If AI does the research for you, it is going to produce the same output it produces for everyone else who asked the same question. You end up with the same product, the same positioning, the same conclusions as everyone else who outsourced their thinking. There is no differentiation. There is no real understanding of your user. There is just a very fast path to building something nobody needed…or you may get lucky and blow up, like all those success stories you see on YouTube.
What the hype culture does not tell you though is that skipping the thinking does not actually save time. It just moves the cost somewhere else. If you launch without knowing who your users are and whether your assumptions about them are true, you will spend months afterward trying to find product market fit that you could have built in from the start. If you think the research phase feels slow, just wait until you have to rebuild. The rebuild phase is much slower. And a lot more expensive.
Most people who want to build something arrive to my course already in solution mode. The features are mapped out, the vision is clear, and the last thing they want to do is slow down. That feeling is completely understandable. But underneath the excitement, if you are honest with yourself, there is usually another voice. The one asking: what if I spend all this time and money building this and nobody wants it?
That voice is discipline. And the hype culture is very good at yelling louder and drowning that good sense people once had.
The uncomfortable truth about doing the thinking first is that it might tell you something you do not want to hear. Your assumptions might be wrong. The problem you thought you were solving might already be solved. The users you thought you understood might want something completely different than what you had in mind. One of my students described choosing to listen to that voice as having to “take a step, or several steps, back, breathe, and commit to doing the research with the acknowledgment that my original idea might not be the right one.”
That acknowledgment takes real discipline. Not the grind, not the hustle, just the willingness to stay in the uncomfortable part long enough to find out what is actually true before you commit to building. The hype culture exists partly because it gives people permission to skip that uncomfortable feeling entirely. Just build it and find out. But finding out after you have built it is a much more expensive lesson.
This is actually where I push back hardest on the AI-first approach. When a student asks how to get AI to do the early research in order to get deeper into the process faster, my answer is usually: not here. Not at this stage. This stage sets the foundation for everything that comes after it. When you let AI decide what to surface and what seems important, you lose control over the judgment that the whole product will be built on. AI tends to tell you what you want to hear and even if you’ve given it instructions to challenge you and be creative, by leaving the early research to AI, it may inadvertently bias you towards the wrong problem. It may surface photo sharing as a key user problem because people talk about it a lot but then completely miss the fact that users already have five solutions for that. It is not trying to do good work, it doesn’t understand what “good” work means. It is trying to give you a useful-sounding answer. And at this stage, what you actually need is something that will help you find out where you are wrong, not confirm where you think you are right.
Doing the research yourself, with your own judgment, before you hand any of it off to a tool or a shortcut, that is the willpower you need. And what this kind of action produces is not just a better product strategy. It is the kind of confidence that actually holds up. Not the confidence of someone who launched fast and hoped for the best, but the confidence of someone who did the uncomfortable work of finding out whether their idea was real before they committed to building it. As one student put it after going through that process: “I have a research-backed strategy for my app. I know the problem space, who my users are and what they need. I am moving forward with confidence.”
There is a concept I keep coming back to with my students, which is knowing what you are skipping. The founders who launch fast and win are usually not skipping the thinking accidentally. They know exactly what they are skipping and they have made a deliberate choice about it. That is very different from skipping it because everyone you see on YouTube is telling you the thinking is optional. One is intentional. The other is just avoidance that feels like efficiency because everyone around you is doing the same thing.
I love this quote from one of my students when she was telling me what she gained from taking my course: “I would have easily spent more time and money in vibe coding and building what I thought would be a simple prototype so I could test it out. In the end, the time, effort and the startup costs would have been way more expensive if I ended up building the wrong solution.” I had another student who’s entire idea fell apart after he realized that while the problem he wanted to solve does truly exist, and people complain loudly about it, but everyone had solutions that more or less worked and they did not want to have to pay for an app to solve the problem for them. His self-control in pausing to do the research before building, and honestly also after he did that research his vulnerability in admitting that people don’t want his idea, saved him.
The real cost of the launch-in-a-week approach is not just that you might build the wrong thing. It is that you will not know you built the wrong thing until you have already paid for it. And by then the cost is not just money. It is the months you spent building. It is the idea you were most excited about. It is the confidence that you could actually do this. One student said it plainly: “In the end, the time, effort and the startup costs would have been way more expensive if I ended up building the wrong solution.” She was talking about a prototype she almost built before doing the research. And this was a highly experienced mobile engineer who has been around the product development process for her entire career. For her, building is easy and a lot of engineers fall into this trap. They decide to build their ideas without practising self-restraint because for them building is easy and fast.
Often we must choose the path that is hard and slow.
Discipline in this context does not mean doing every single step every single time. It means knowing what the steps are. It means understanding which of your assumptions could sink you if they turn out to be wrong. It means being honest with yourself about what you actually know versus what you are hoping is true. And it means doing the uncomfortable work of finding out before you commit to building.
And when someone actually has the discipline to do the work, you can hear it in how they talk about their product. It sounds less like excitement and more like clarity. Instead of “I have this great idea for an app that everyone will love!” you hear them say “I have a research-backed strategy for my app. I know the problem space, who my users are and what they need. I am moving forward with confidence.”
That confidence is not the confidence of someone who launched fast and hoped for the best. It is the confidence of someone who chose to do the harder thing first. And that is really what discipline looks like in this space. Not the speed, not the output, just the willingness to stay in the uncomfortable part long enough to actually know what you are building and why.
My message is pretty simple: In this new AI-driven, launch-in-a-week world, now more than ever self-discipline is one of the best skills you can cultivate for long term success. Do the research yourself. Sit with findings that contradict what you hoped was true. Don’t outsource your judgment at the exact moment your judgment matters most.
Thanks, Abbey, for sharing these ideas with us.
One of the passages that resonated the most with me was:
That confidence is not the confidence of someone who launched fast and hoped for the best. It is the confidence of someone who chose to do the harder thing first. And that is really what discipline looks like in this space. Not the speed, not the output, just the willingness to stay in the uncomfortable part long enough to actually know what you are building and why.
It resonated because it aligns a lot with the ideas I share across this newsletter. Maybe not at first sight, but if you think about it, what these lines say, and maybe Abbey can confirm, is that discipline does not really look like performance. It looks like having the ability to set a direction and stay truthful to that direction, even when it is hard.
Now, part of the hardship of keeping that direction comes from the fact that we have to constantly act so we can return to the path when drift pulls us away from it. As we know, drift is inevitable, so staying in the uncomfortable is highly connected to the fact that the road will not be free of bumps. It is on us to stay aware and bring order back when it is needed.
Staying truthful, then, does not mean staying on the path no matter what, because we are human. It means keeping the direction in mind so we know what to come back to and why.
Studies show that doing hard things rather than skipping them, by practicing small acts of self-control, can improve our ability to regulate ourselves. Basically, every time you choose effort over impulse, you are training your ability to endure the uncomfortable1. So when we skip the moments where we need to apply effort, think, build, and learn, and delegate that responsibility to somebody or something else, like AI, we are actually doing the opposite. Our ability to endure weakens, making us more prone to drift.
What I want you to take from this is not that you should avoid AI, or that AI cannot help you in your thinking process. What I want you to take from this is that AI should be a copilot, not the one steering the wheel. Because the minute you hand over control, you also give up part of the control that keeps you moving in the direction you chose.
In our next paid companion, we will learn how to kickstart the practice of small acts of self-control, so our ability to withstand hardship, and with that our return to what matters, becomes easier over time.
As one final note, Abbey teaches founders, career-changers, and early-stage builders the product strategy they need to lead app development, and it does not require any experience.
She offers a free course. In it, she writes about tech education, building in public, taking care of yourself, and what it actually takes to go from idea to launch.
To take the free course, check out this link.
Have a wonderful week!
✨Ideas Worth Exploring
If this piece resonated, here are a few more that go hand-in-hand.
Muraven M. (2010). Building Self-Control Strength: Practicing Self-Control Leads to Improved Self-Control Performance. Journal of experimental social psychology, 46(2), 465–468. https://doi.org/10.1016/j.jesp.2009.12.011
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