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🌊 The game has changed
Today, you can build almost anything in a few hours. That changes the central question for people creating products: it’s no longer "Can I build it?" but "Is it worth building?" This module shows what changed before we talk about strategy.
Module topics
What it is
The phenomenon of having too many apps, built too quickly because AI tools brought the cost of building software close to zero.
Why learn it
When everyone can launch, launching stops being a differentiator. Understanding the app boom helps you avoid confusing "I managed to build it" with "I have a product."
Key concepts
App boom, marginal cost of building, excess supply, scarce attention.
What it is
The discussion around the "SaaS apocalypse": the idea that software subscriptions lose their purpose when anyone can build their own AI-powered tool.
Why learn it
The thesis is partly right. The opportunity lies in knowing where it’s wrong.
Key concepts
SaaS apocalypse, arbitrage, niche, use case, speed.
What it is
The classic product lifecycle and how AI changed the order and cost of each step.
Why learn it
If you follow the old order to the letter, you lose the advantage of building fast. If you ignore the order completely, you build without knowing whether anyone wants it.
Key concepts
Product lifecycle, validation, prototype, order of steps, iteration.
What it is
The situation where you’ve solved the same problem many times for clients or coworkers and want to turn that solution into a standardized product.
Why learn it
It’s the safest shortcut for someone just starting out: your own work has already proven the need.
Key concepts
Micro-SaaS, operationalize, standardize, validation through experience, relative pricing.
What it is
The possibility of one person, supported by AI agents, doing work that used to require a product manager, engineer, and QA analyst.
Why learn it
That’s both power and a trap: you can do everything, but you can also get everything wrong with no one there to challenge you.
Key concepts
Product manager, engineer, QA, AI agent, self-critique.
What it is
The principle that in a market where anything can be copied, the window of opportunity is short, and whoever moves fast captures most of the value.
Why learn it
Today's advantage lasts months, not years. Planning as if it will last for years is the most common way to lose it.
Key concepts
Window of opportunity, first to market, short cycles, fast learning.
🎯 The problem with average
Language models learn from what already exists and tend to return what’s most common. That’s great for speed and terrible for differentiation. This module explains why average doesn’t grab attention and what to do about it.
Module topics
What it is
The tendency of language models to produce the most likely answer, which is also the one most similar to what already exists.
Why learn it
If you let the model decide the design, copy, and user journey, your product will look like all the others built the same way.
Key concepts
LLM, most likely answer, statistical average, pattern, generic.
What it is
A stimulus that breaks the viewer’s expectations and demands attention: something different from what they’ve already seen a hundred times.
Why learn it
In an endless scroll, anything that looks the same disappears. Your product needs at least one element that makes people stop.
Key concepts
Pattern interrupt, attention, expectation, differentiation, first impression.
What it is
The risk of losing the ability to think for yourself because AI always offers a ready-made answer, even for product decisions.
Why learn it
Judgment is what sets apart people who build products that work. When it atrophies, all you produce is the average.
Key concepts
Judgment, cognitive outsourcing, standards, user journey, independent thinking.
What it is
The flood of new product announcements every day, which makes people stop paying attention to any launch.
Why learn it
If your marketing plan is "announce it and wait," you’re competing with dozens of announcements a day, and you’ll lose.
Key concepts
Launch fatigue, "introducing," favorites, attention, noise.
What it is
The idea that even with too many products and few moats, there are always problems no one has solved well or brought to the right people.
Why learn it
It helps you avoid the opposite mistake of getting carried away: thinking it’s no longer worth building anything.
Key concepts
Gap, moat, distribution, problem precision, underserved niche.
What it is
The three levels of judgment for people creating products today: technical skill, problem selection, and value assessment.
Why learn it
The first level became almost free with AI. The advantage shifted to the other two.
Key concepts
Technical judgment, problem judgment, value judgment, discernment.
🧱 Productive pessimism
Productive pessimism means honestly imagining everything that could go wrong, not to give up, but to prepare. This module turns that attitude into a method: reasons against, reasons for, a small bet, and an AI-assisted premortem.
Module topics
What it is
The practice of deliberately listing the ways a plan could fail, with the goal of reducing risk rather than justifying inaction.
Why learn it
Untested optimism leads to products nobody wants. Pessimism without action leads to nothing. The middle ground is what works.
Key concepts
Productive pessimism, defeatism, optimism bias, risk management.
What it is
A habit of recording concrete plans over the years for surviving the worst-case scenario, such as losing all your income overnight.
Why learn it
It trains your mind to find creative solutions under pressure. The same mental muscle helps you find a way forward for a product.
Key concepts
Contingency plan, creativity under constraints, extreme scenario, habit.
What it is
List the five strongest reasons your idea will fail, without softening any of them.
Why learn it
It’s the cheapest way to find the weak spot before the market finds it for you.
Key concepts
Distribution, copycats, addressable market, individual pain, local scope.
What it is
List the five concrete reasons the idea could succeed, based on resources and channels you actually have.
Why learn it
The positive side shows you where to start. But it needs to be just as honest as the negative side.
Key concepts
Owned channels, commissions, groups and forums, early feedback, minimal cost.
What it is
Design the cheapest test possible that answers the riskiest question about the product.
Why learn it
With AI, testing has become incredibly cheap. Spending months before testing has become an expensive, avoidable mistake.
Key concepts
Small bet, minimum test, risk hypothesis, learning cost.
What it is
Use an AI assistant to run a full pre-mortem: imagine the product failed in a year and work backward to figure out why.
Why learn it
The model isn’t attached to your idea. With the right instructions, it can find weaknesses you don’t want to see.
Key concepts
Pre-mortem, devil’s advocate, structured prompt, mitigation plan.