Product-market fit is not enough anymore. You need position-market fit:
There was a time, not too long ago, where in startupland one could build a thing that solved a real problem, put a price tag on it, and see if the market wanted it:
• If they did, then we would have said he had found product-market fit
• If they didn’t, we would say he didn’t and it was “back to the lab”
That time, for better or worse, is long gone.
Here’s how @0zne and I break it down:
In 2024, a utility provided through software can’t make a dent effectively anymore. People’s heads are overstuffed with competing products, messaging, and narratives. It’s hard for a product alone to get a market edge.
The main exceptions are new tech or hyper-niche markets. ChatGPT, for example. But that is a rare instances of breakthrough technology where the “product” itself carries the bulk of the impact.
Most companies don't have that luxury and are not in such a position. So, if a product alone isn’t enough, then what is enough?
Enter position-market-fit.
• If “product-market-fit” means that you’ve found the right kind of product that the market wants…
• “Position-market-fit” means that you’ve found the right combination of product/brand/marketing/pricing/go-to-market/sales/etc in a given domain.
The Importance of Brain Estate
The fundamental reason why “position-market-fit” is so important is that it operates more at a personal and subconscious level. Our brains can only conceptualize a finite set of “characters'' per domain.
Similar to the "Dunbar number" rule, which suggests we can maintain stable social relationships with up to 150 people, our brains are wired to understand only a finite number of company-market associations.
Gaining a strong positional edge, or nailing “position-market-fit” is the exercise through which a company, with the right combination of product, brand, pricing, marketing and go-market is able to conquer a certain portion of consumer “brain-estate.”
The Story of Startup Success
If you step back and analyze some of the best startups from the last decade, you'll see they excelled at this.
→ Are you building in an established market dominated by large incumbents with feature-bloated, slow, and clunky software? In that case, you might want to position your product as a speed-first, high-craft, premium option, similar to a luxury car company. Does Linear ring a bell?
→ Alternatively, if you're entering a highly commoditized market dominated by a few corporate-looking brands, consider positioning yourself as the quirky, fun company that doesn’t take itself too seriously. Embrace the David vs. Goliath narrative with bold, edgy marketing and design. Does Arc Browser come to mind?
Their pricing strategies are almost a second-order effect of their employed market positioning.
And that’s the power of position-market fit.
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This is the most important part of the homepage. Too many people waste the space:
A. Convey the category of software your product is in, and how your solution differs
B. Add in wow logos from industries in your ICP (ideal customer profile)
2. Three Key Value Props
Remember the rule of threes.
Deliver on your hook above the fold and make your differentiators crystal clear.
Don't just tell, either. Show. Let people experience the product. Attio's videos move when you scroll.
For a company founded in '93, Nvidia's ascent to $2.7T market cap has been FAST. But what really is Nvidia's moat?
Let's break it down.
PART 1 — SOFTWARE
The story starts all the way back in the early 2000s. That's when Jensen Huang, Nvidia CEO, and his team were out meeting researchers using their products.
Most researchers were hacking graphics packages to run complex parallel compute tasks. It was not ideal. To say the least.
So, when the Nvidia team met Ian Buck, who had the vision of running general purpose programming languages on GPUs, they funded his Ph.D. After graduation, Ian came to Nvidia to commercialize the tech.
Two years later, in 2006, Nvidia released CUDA.
C ompute
U nified
D evice
A rchitecture
CUDA made all those parallelization hacks the researchers were doing available to everyone. Over time, CUDA became the default choice for researchers.
CUDA allowed accessible customization of the low-level hardware. So developers loved it.
Nowadays, when startups like MosaicML evaluate the available technology vs CUDA, they inevitably choose CUDA.
The ecosystem around CUDA has grown so robust that its lead is virtually unbeatable. This software layer is at the core of Nvidia's moat.
PART 2 — HARDWARE
The other side of Nvidia's moat is hardware. But it's not graphics cards for crypto and gaming. The hardware that matters is AI supercomputers.
The story of these supercomputers begins in the late 2000s. As Nvidia was developing CUDA, Jensen asked the team to build a supercomputer to help him build better chips.
The result was a massive supercomputer that weighed 100 pounds and strung together many GPUs with world-class networking for ultra-fast computing.
In the early 2010s, Jensen gave a talk at a conference about this AI supercomputer. Elon Musk got wind of it and said, "I want one."
So, in 2016, Jensen actually donated one to Elon Musk's relatively unknown nonprofit, OpenAI. He hand delivered it, and there's photographic proof.
OpenAI quickly learned the supercomputer worked really well. Especially for training large neural networks. That 2016 Pascal architecture delivered an impressive 19 TFLOPS of FP16 operations.
That's 19 trillion floating point operations per second. It's a massive amount. But that was just the beginning.
Since then, Jensen and the Nvidia team have been lapping the industry in delivering more TFLOPS, growing them at an exponential rate.
The latest Blackwell architecture delivers a massive 5000 TFLOPS. That's >260x AI computer in 8 years. And sells for more than $75K. But buyers like Meta, OpenAI, Google, and Amazon just can't get enough, as their internal ASICs are nowhere near Nvidia's level.
As a result, Nvidia's profits and market cap continue to soar, cementing its position as a leader in the AI hardware and software space.
Jensen is one of the most impressive entrepreneurs alive.
He spotted the AI revolution before any other semiconductor CEO and bet the company on it.
That's a rare trait.
And he has a rare management style as well.
He has over 60 direct reports, and doesn't have 1:1s with any of them.
He believes in sharing feedback in public, so everyone can learn from it. And he also does it to remove layers.