AI Ruins Your Competitive Advantage
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The Last Moats Standing
Everyone's freaking out about AI commoditizing everything.
And they should be.
The speed at which products can now be created is absolutely insane. What used to take months now takes days. What took years now takes weeks.
Think about that for a second.
A single person with AI can now build products that would have required entire teams just a few months ago. We're seeing solo founders launch fully-featured apps in days. Small teams shipping in weeks what would have taken quarters.
But here's what everyone's missing:
When products become easy to make, they become impossible to compete on.
The "we have better features" pitch is dead. The "our tech is superior" advantage is evaporating. The "we execute faster" story doesn't work when everyone can execute at lightning speed.
The real game is being played somewhere else entirely.
When products become commodities, the true moats reveal themselves. And they're not what most people think.
No amount of AI can replicate real network effects. No algorithm can generate authentic brand loyalty. No model can replace strategic distribution. No prompt can substitute for deep user data.
These are the advantages that matter now. The ones that get stronger, not weaker, as AI improves.
And almost nobody is talking about how to build them.
The Great Product Commoditization
Remember when having a "good product" was enough?
Those days are over.
AI is flattening the playing field so fast it's making people dizzy. The gap between good and great products is shrinking daily. What used to be your competitive edge is becoming table stakes.
The uncomfortable truth about modern product development:
Every feature you build can be replicated in days. Every technical advantage you create can be matched in weeks. Every product innovation you launch can be copied in a fraction of the time it took you to develop it.
Welcome to the sea of sameness.
Look at productivity apps. To-do lists. Note-taking tools. Project management software. They're all starting to feel identical. Not because companies are copying each other, but because AI makes it trivially easy to implement any feature your competitor has.
The barrier isn't technical anymore. It's not even speed or execution.
Want proof? Go to Product Hunt right now. Count how many AI-powered productivity apps launched just today. Each one probably took less than a month to build. Each one probably has 90% of the features of established players.
But almost none of them will succeed.
Why? Because they're playing the wrong game. They think having a good product is enough. They think speed of execution is their moat. They think technical excellence will save them.
The reality? You can't win by being marginally better at something everyone can do well.
Network Effects in an AI World
This is where network effects become fascinating.
Think about what makes OpenAI valuable. It's not their technology anymore. Multiple companies have matched or exceeded their technical capabilities. What makes them valuable is their network of developers, users, and applications all building on top of each other.
Each new user makes the network more valuable for everyone else.
When a developer builds a new tool on GPT-4, it attracts more users. More users attract more developers. More developers build better tools. Better tools attract more users. Round and round it goes.
And here's the wild part about network effects:
They actually get stronger as AI improves. As products become easier to build, the value of having a strong network becomes even more important. It's the one thing AI can't easily replicate.
Discord understands this. Their core chat functionality could be built by any competent team with AI assistance. But their true value is in the millions of communities and connections they've fostered. Each new user makes Discord more valuable for everyone else.
The power of network effects lies in their compounding nature.
Take Figma. Their collaborative design tools are impressive, but that's not their real moat. Their moat is the millions of designers who share, collaborate, and build together on their platform. Every new template, every shared component, every collaborative project makes the platform more valuable.
Linear gets it too. They're not just building a better project management tool. They're building a network of teams and workflows that become more valuable as more people use them.
But here's what most people miss about building network effects:
You can't just build a product and hope network effects emerge. You have to deliberately architect your product to create and capture value from user interactions. Every feature needs to strengthen the network, not just serve the individual.
Brand: The Human Moat
Let's talk about the most misunderstood moat.
Most people think brand is about logos, colors, and catchy taglines. They're wrong. Dead wrong.
Brand is about identity.
When products become identical, people don't choose based on features. They choose based on who they want to be. What tribe they want to belong to. What story they want to believe in.
Look at Apple. Their hardware isn't dramatically better than competitors anymore. But their brand represents creativity, innovation, and premium design. People don't just buy Apple products. They buy into the Apple worldview.
This becomes even more powerful in an AI world.
Why? Because when AI makes it easy for anyone to build good products, the emotional connection becomes the differentiator. The human element becomes the moat.
Notion gets this perfectly. Their core product could be replicated. But their brand stands for something bigger. It represents a new way of thinking about work and creativity. Their users don't just use Notion. They evangelize it.
But here's the thing about building a strong brand:
You can't fake it. You can't AI-generate it. You can't growth-hack it.
Real brand building happens through consistency. Through having a clear point of view. Through making hard choices about who you are and aren't for.
And most importantly, through actually standing for something.
This is why most AI-generated content feels hollow. It can mimic the style, but it can't create the substance. It can copy the form, but it can't generate the authenticity that makes great brands resonate.
Distribution: The Force Multiplier
Distribution might be the most underrated moat of all.
When everyone can build great products, reaching the right people becomes everything. When features are equal, being in the right place at the right time becomes the difference maker.
But most founders get distribution completely wrong.
They think it's about marketing spend. About running more ads. About shouting louder than everyone else.
Real distribution power is about building paths that others can't easily replicate.
Stripe didn't win because they had better payment processing. They won because they built distribution right into their product. Every developer who implemented Stripe became a distribution channel. Every startup that grew with Stripe helped Stripe grow too.
Distribution compounds in ways that product features don't.
Think about Spotify. They don't have better music than Apple Music or Amazon. The core product is virtually identical. But their distribution through social sharing, playlist embedding, and platform partnerships creates a massive advantage.
What makes great distribution so powerful now?
It's the ultimate paradox. As AI makes it easier to build products, distribution becomes harder. More products mean more noise. More noise means attention becomes scarce. Scarce attention means strong distribution channels become invaluable.
But here's what nobody tells you about distribution:
The best distribution strategies aren't obvious. They're not about buying attention. They're about creating systems where growth happens naturally as a byproduct of using your product.
Like how Figma grows through design file sharing. Or how Notion spreads through workspace sharing. Or how Discord grows through server invites.
These aren't just features. They're distribution mechanisms baked right into the core product experience.
Data as a Defensive Weapon
Everyone talks about data. Few understand its real power.
Most people think data is about training AI models. About improving algorithms. About making better predictions.
They're missing the bigger picture.
Data becomes truly powerful when it creates barriers to entry.
Every time someone uses your product, they make it better for themselves. They create shortcuts, build workflows, save preferences. They generate personal data that makes switching to another product painful.
This is why Superhuman users rarely leave.
It's not the speed. It's not the features. It's the fact that Superhuman learns how you work. It adapts to your patterns. It builds a personal dataset that makes switching email clients feel like starting over.
Think about what makes GitHub valuable. It's not the code hosting. It's the entire history of how teams work together. The commit histories. The collaboration patterns. The project structures. That's data no competitor can easily replicate.
But there's a crucial difference between training data and user data.
Training data can be replicated. User data can't. Anyone can scrape the internet to train an AI model. But no one can replicate the specific, personal data that users generate through actually using your product.
This is where data becomes a true moat.
Every time a Linear team builds their workflow, they make Linear more valuable for their specific needs. Every time a Notion workspace creates their knowledge base, they make Notion harder to replace.
The data moat gets deeper with every user interaction. With every customization. With every piece of user-generated content.
And in an AI world, this type of data becomes even more valuable. Because while AI can help competitors catch up on features, it can't replicate the unique data your users have built up over time.
This goes way beyond software.
Look at Stitch Fix. Their real advantage isn't their clothing selection. It's the millions of data points they've gathered about how real people interact with fashion. Every time someone keeps or returns an item, rates a piece, or gives feedback, they make their personalization stronger.
Even something as simple as a local coffee shop builds this kind of data moat. They remember how regulars like their coffee, which pastries sell out first, what times are busiest. This isn't big data. It's small, specific, valuable data that chains can't easily copy.
Or take Sweetgreen. Their app knows your favorite salad combinations, your usual order times, your dietary preferences. That data makes each visit more convenient, more personal. A new salad place can copy their menu but can't copy your history.
The best part about this type of data moat?
It works for any business that can create ongoing relationships with customers. Any service that gets better with user interaction. Any product that learns from how people actually use it.
The New Playbook
Now you might be wondering how these moats fit together.
They don't just fit together. They multiply each other.
Strong networks generate unique data. Data strengthens your brand. Brand powers distribution. Distribution feeds back into networks.
The best companies don't just build one moat. They build self-reinforcing systems where each advantage makes the others stronger.
Look at Figma again. Their network of designers creates valuable data. That data strengthens their brand as the platform where design happens. Their brand drives distribution through word of mouth. And that distribution brings in more designers, strengthening the network.
And for a CPG example, let’s look at Magic Spoon cereal. Their direct-to-consumer network of health-conscious customers generates valuable data about flavor preferences and eating habits. That data strengthens their brand as the leader in healthy cereal alternatives. Their brand drives word-of-mouth distribution through Instagram shares and subscription unboxings. And that distribution brings in more health-conscious customers, strengthening their customer network. Each new flavor launch and customer interaction makes the entire system stronger.
But you can't build all these moats at once.
You have to start somewhere. And that somewhere is usually with one core interaction that has the potential to create multiple moats.
For Figma, it was collaborative design.
For Discord, it was community chat.
For Notion, it was shared workspaces.
For SoulCycle, it was group fitness experiences.
For Airbnb, it was unique local stays.
For Blue Bottle Coffee, it was subscription coffee tasting.
Each of these core interactions does multiple things:
Creates network effects through collaboration
Generates valuable user data
Drives natural distribution
Builds brand through shared experiences
The Future of Competition
The world of AI abundance is going to be wild.
Products will be built faster than ever. Features will be copied instantly. Technical advantages will evaporate overnight.
But the fundamentals of business aren't changing. They're intensifying.
The companies that win won't be the ones with the best AI. They'll be the ones who use AI to build and strengthen real moats that others can't easily copy.
This is actually incredible news for founders.
Because while everyone else is obsessing over AI features and capabilities, you can focus on what really matters: Building genuine connections with users. Creating real network effects. Developing authentic brands. Crafting smart distribution systems. Generating valuable user data.
These are the things AI makes easier to execute but harder to replicate.
And that's the ultimate paradox of the AI era. The more powerful AI becomes, the more valuable human-centric moats become.
The future belongs to those who understand this shift. Who see that AI isn't the moat. It's the tool you use to build real moats.
The rest will be stuck competing on features in an endless race to the bottom.
The choice is yours.
– Scott