In the current landscape, thinking ahead about the competitive advantages after achieving Product-Market Fit (PMF) may be more important than ever.
Author: qw
Translated by: Deep Tide TechFlow
Three years ago, when ChatGPT was first launched, I wrote a small program to help myself prioritize emails and messages. Since my programming skills were a bit rusty, I chose to use ChatGPT to assist with the coding work. At that time, I immediately felt the power of AI. This project took me only half a day, whereas in the pre-AI era, it might have taken several days to complete.
In the following years, the technical founders we collaborated with at Alliance gradually began using various AI coding tools, such as Cursor. I once asked them how much these tools could improve productivity. On average, it was about 1.5 times, with some even claiming it could reach 2 times.
Just this week, I posed the same question to the latest members of Alliance. Their responses indicated that productivity improvements ranged from 2 to 4 times. This surprised me greatly. Not only because of the significant increase, but also due to the rapid pace of progress—productivity has already increased by 4 times in just three years, and this trend continues.
When I first used ChatGPT as an assistant, I had a vague sense that AI would forever change the rules of entrepreneurship. Now, I am convinced of it.
The cost of writing software is rapidly decreasing, approaching nearly zero. But this is just the beginning. The costs in other business areas such as marketing, sales, customer service, and operations are also significantly lowering. This change has already manifested in large companies. For startups that have yet to find their PMF, the impact is temporarily smaller, as founders need to personally handle user acquisition and support to be closer to customers. However, for startups that have already found PMF, they are beginning to leverage AI to scale their businesses more quickly.
Such changes have led to an obvious result: startups no longer need large amounts of funding and massive teams to grow rapidly. In other words, in the future, we may see more unicorn companies created by a few co-founders with less than $500,000 in funding. In fact, over the past few years, we have seen an increasing number of Alliance startups achieve millions or even tens of millions of dollars in revenue growth annually after securing only a small amount of seed funding through us and a few angel investors. Their team sizes are typically less than 10-20 people, and they may never need to raise funds again.
This raises a question: If the cost of writing software and scaling businesses is so low now, what "moats" can companies rely on to maintain competitiveness?
Proprietary Data: Unique customer data or hard-to-obtain public datasets can provide competitive barriers for businesses.
Network Effects: While it is theoretically possible to rebuild the technical architecture of Facebook or Nasdaq, acquiring their users is not an easy task.
Deep Integration: Enterprise software that is deeply embedded in workflows has high switching costs.
Ecosystem Lock-in: Platforms with strong developer ecosystems and third-party integrations are stickier.
Regulatory Barriers: AI cannot help businesses obtain the licenses and relationships needed to operate in highly regulated industries like finance, healthcare, or defense.
Trust and Brand: Consumers and organizations still tend to trust well-known brands more when making critical decisions.
Physical World Constraints: Physical infrastructure, robotics, and supply chains still present real-world constraints that AI cannot overcome.
Deep User Insights: While AI can help realize some decent ideas, truly understanding user needs is not found in AI's training data but comes from direct communication with users.
For startups that have yet to find PMF, achieving PMF is a top priority. However, at this moment, thinking ahead about the competitive advantages after PMF may be more important than ever.
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