Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

marsbitPublished on 2026-06-20Last updated on 2026-06-20

Abstract

Alliance Co-founder's Letter to Entrepreneurs: On Cursor's $60 Billion Sale Many aspiring founders see massive exits like Cursor's $60B sale and wonder why they can't achieve the same, often concluding opportunities are exhausted. But great companies aren't built in obvious, crowded spaces. Cursor, like Stripe, Figma, and Shopify before it, started with a non-consensus belief about the future. Before ChatGPT, they believed AI would transform knowledge work. They focused on a genuinely exciting domain, became their own customer, and obsessed over power users. Their journey involved years of "glass-chewing" effort before the market was ready. The pattern is consistent: identify a long-term technological shift, find a missed entry point, and execute for years before the trend becomes obvious. First-generation products (PayPal, Adobe, Amazon) prove a market exists. Second-generation winners (Stripe, Figma, Shopify) rebuild that market around new insights, technology, or changing customer behaviors. Founders must identify their phase in the cycle. Early entrants like Coinbase or Cursor focus on making new technology usable for power users. Later entrants find the "yin" to the established "yang"—the blind spots incumbents miss as they grow distant from individual users. The key is deep market immersion. Use every product in your space. Talk to users. Build an audience. Stop looking for ideas and start *seeing* them everywhere. Then, choose one. The idea must offer a 10x improve...

Author: Imran

Translation: Jiahuan, ChainCatcher

Sitting in front of your computer, an entrepreneurial idea sparks. You see Cursor selling for $600 billion to Elon Musk. Perhaps the idols of the previous generation were Mark Zuckerberg or Evan Spiegel. You look at these founders and can't help but compare yourself to them. They don't seem much smarter than you. Their resumes aren't much more impressive than yours.

So you naturally ask yourself: Why can't I do the same? This is where most founders begin their journey. But this is also where most founders get stuck.

They see AI. They see crypto. They see thousands of startups that have already raised funding. Every space seems crowded. Every obvious idea has already been implemented.

They conclude: opportunity has run dry.

So they close their laptop, give up, and walk away.

This is how a huge portion of startups die in the womb. Not because the founders weren't capable, but because they thought the game was over before it even started.

Let's take Cursor as an example. Not every path is a direct and smooth one.

As early as 2022, Cursor began the "eating glass" grind. This was before ChatGPT existed. There was no ready-made playbook. No obvious market. Just a belief that AI would fundamentally transform knowledge work.

To stay grounded, they focused on three things. First, they picked a space they were genuinely excited about: AI. Second, they were their own customer. Third, they focused relentlessly on power users.

Because if you can win the power users, the rest becomes easy. Honestly, this story is not unique to Cursor.

Stripe started when online payments seemed solved, but the founders believed developers would increasingly become decision-makers inside companies, and whoever won developers would eventually win the internet. They had experienced the pain point themselves. While PayPal had proven online payments could work, Stripe saw the opportunity to build a "developer-first" version of that future.

Figma spent years building before the market was ready because they believed the future of design wasn't about better single-player design tools, but about everyone working together in the same file. Google Docs had shown the power of real-time collaboration for documents. Figma extended that insight to design.

Shopify started just to sell snowboards online because the founders believed millions of small businesses wanted to own their customers, their brand, and their destiny, rather than depend on big platforms. Amazon had proven centralized e-commerce worked. Shopify bet entrepreneurs would eventually want to be in the driver's seat.

Different products. Same pattern.

Each founder started with a non-consensus belief about where the world was headed, then spent years quietly building before that future became obvious to everyone. Their luck was catching a strong tailwind.

For Stripe, it was the conviction that more and more commerce would move online. For Figma, it was the belief that software would be cloud-first and collaborative by default. For Shopify, it was the hope that the internet would empower millions of entrepreneurs to build independent businesses.

Cursor followed a similar trajectory. The company was built on the belief that AI would fundamentally reshape knowledge work, and that software engineers would be the first power users to adopt it. The product feels obvious today, but when they started, there was no clear roadmap. Just belief.

Different products. Different markets. Same underlying logic.

Identify a long-term trend shift early, find the entry point others missed, spend years executing before the rest of the market catches up. Where there is Yang, there must be Yin. PayPal gave birth to Stripe. Adobe gave birth to Figma. Amazon gave birth to Shopify.

The first-generation product proved the market exists. The second generation rebuilds it around a new insight, new technology, or changing customer behavior. For founders, the important question is figuring out where you are in the cycle. If you're early, like Coinbase or Cursor, your opportunity is usually about making new technology practically useful for power users.

Coinbase didn't invent cryptocurrency. It just made buying and holding Bitcoin infinitely easier than managing your own wallet or wiring money to Mt. Gox.

Cursor didn't invent AI programming. It just realized autocomplete wasn't the endgame, and developers truly wanted an AI-native way of building software.

But if you're entering in the mid-to-late stages of a technological change, the opportunity often looks different. Infrastructure exists. The market is proven. Your job isn't to prove the technology works, but to find the 'yin' to the existing 'yang' — the blind spot the first players missed. Many of the greatest companies are born here.

Now you've identified your place in the technological change. You have a few ideas and are ready to get started, but then you realize something unsettling: you don't actually have many unique insights. You don't have a deep understanding of the market, the customers, or even the product. And that's perfectly normal.

This is when you must roll up your sleeves and start building your network, insights, and reputation. Thankfully, we live in an era where with X (Twitter), this is easier than ever. You can build an audience, meet customers, engage with power users, and learn directly from the people shaping the market.

The first thing I would do is use every product in the space. If you're starting a company in a category but aren't a power user of the leading products, it's hard to develop a unique perspective on where the market is headed. Map out every product in the ecosystem. Become a power user of each. Talk to people who love them, hate them, and have given up on them. Figure out why they stay, why they leave, and what they wish existed that doesn't.

You'll eventually discover that most markets aren't won because incumbents are stupid. They are displaced precisely because they became successful.

As companies grow, they naturally move further away from the individual user. Feedback cycles lengthen, edge needs are ignored, and a new generation of power users emerges that doesn't fit the existing product. This is where sharp founders spot the opportunity.

The goal isn't to think up an idea in isolation. The goal is to immerse yourself in the market until the missing piece becomes obvious. Once you do this long enough, you'll stop looking for ideas and start noticing them everywhere. This is the state you want to reach. You'll eventually find there are more opportunities than you could ever possibly pursue.

Next is the hard part: choosing one.

Once you've settled on an idea you believe is right, the next question is simple: Is this a 10x improvement, or a hair-on-fire pain point? If the answer is no, don't bother. People rarely switch products for marginal improvements. They switch when something is dramatically better, or when the pain is so severe it demands an immediate solution.

The easiest way to find hair-on-fire pain points is to look for people already hacking together workarounds. Spreadsheets, WhatsApp groups, manual processes, copying data between systems — these are all signals.

The best founders look for pain, because when the pain is big enough, customers will rip the product out of your hands. And when the pain is trivial, no amount of marketing, growth hacking, or clever positioning will save you.

Now you've validated the idea, found the pain, and are building the MVP.

With Claude, Codex, and all the AI tools, building has never been easier. Ironically, this becomes its own trap.

I found myself adding features just because I could. The product slowly became a Frankenstein monster. Every feature made sense in isolation, but together they made the product worse.

Eventually I went back to first principles. The most important question isn't what feature I should build. It's why someone would abandon their existing tools to use yours.

Every great startup has an answer to this. Cursor could have built another coding plugin. Instead, they forked VS Code. Developers already loved this editor, knew how it worked, and had it embedded in their workflow.

Cursor didn't ask users to learn something completely new. It let them keep doing what they already loved, just with AI baked directly into the experience.

The best startups rarely force users to learn completely new behaviors. Instead, they find familiar workflows, remove friction, and make them dramatically better.

As founders, we obsess over what we're building. Customers care about what they have to give up. The lower the switching cost, the higher the value created, the faster the adoption. That's why the best MVPs aren't feature-rich. They're incredibly focused, giving customers a single, undeniable reason to switch.

By this point, you've found the pain, built the MVP, and hopefully given customers a strong reason to choose you. Next is the part most founders underestimate: distribution.

I've seen founders spend months on product and five minutes thinking about how users will find it. The truth is, distribution is often the moat.

Airbnb didn't win because it had a better website. The founders knocked on doors, personally photographed apartments, and manually seeded cities one by one. Stripe recruited developers one by one. Coinbase was in Bitcoin forums long before crypto went mainstream.

Cursor is another perfect example. Their team posted on Hacker News six times. Most posts sank without a trace. They DM'd thousands of developers, listened to feedback with extreme patience, and won users one by one.

Today everyone says Cursor's success was inevitable. But for years, they did unscalable, manual work.

Founders love talking about product-market fit, but before product-market fit, you have to solve distribution-market fit. Where do your customers spend time? Who do they trust? How do they discover new products? The best founders don't just build product. They build distribution engines. Because the market can't fall in love with a product it's never seen.

The final stage of all this is grit, resilience, and refusing to quit.

Sadly, I can't teach you this. No one can. It can only be learned through experience.

Cursor is again a perfect case. They spent years building before the market matured. They posted repeatedly, DM'd thousands of users, and were ignored by most. In hindsight, it all makes sense. At the time, the future was far from certain.

The same pattern is everywhere.

Airbnb's founders were repeatedly rejected and even resorted to selling cereal boxes to keep the company alive.

Nvidia faced near-death experiences multiple times before becoming one of the world's most valuable companies.

Rain, a company in our incubator batch, was born after the FTX collapse, when most thought crypto was dead. While others fled the industry, they kept building. Years later, they raised over $100 million at a $2 billion valuation.

The lesson isn't that these founders are smarter than you. It's that they stayed in the game long enough for their insights to compound.

So, I've laid out the whole framework for you.

Look for shifts in technology cycles. Cultivate unique insights. Obsess over your market. Talk to customers. Find hair-on-fire pain points. Build the simplest possible wedge. Win your distribution.

And most importantly, when it gets hard, absolutely do not quit.

That's it.

There's no secret. Most people can't do these things consistently, for a long period of time. The very few who do end up building the great companies that the next generation of founders study.

The world is yours.

Go build.

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Related Questions

QAccording to the article, what is a common mistake that aspiring founders make when they see successful tech giants like Cursor?

AThe article states that aspiring founders often conclude that all the opportunities have been taken and the game is over, leading them to give up before even starting. This is a primary reason why many startups die prematurely, not due to a lack of founder talent but because they mistakenly believe there is no space left for innovation.

QThe article mentions a consistent pattern followed by companies like Cursor, Stripe, and Figma. What are the key elements of this pattern?

AThe pattern is: 1) Start with a non-consensus belief about the future direction of the world (e.g., AI will reshape knowledge work, developers will be key decision-makers, design will be collaborative). 2) Spend years building for that future in obscurity before it becomes obvious to everyone else. Their success hinges on riding a powerful tailwind, such as the shift to online commerce or cloud-native software.

QWhat is the 'yin' to the 'yang' strategy mentioned for founders entering a market in its middle or later stages?

AFor founders entering in the middle or later stages of a technology shift, the opportunity lies in finding the 'yin' to the existing 'yang.' This means identifying the blind spots or unmet needs of the first-generation players who have proven the market. Great companies are built by reconstructing the market around a new insight, technology, or changing customer behavior that the incumbents have overlooked.

QWhat does the article suggest is more important than product-market fit in the early stages, and why?

AThe article suggests that before achieving product-market fit, founders must first achieve 'channel-market fit.' This refers to figuring out the distribution channel. The author argues that the distribution channel is often the moat because customers cannot fall in love with a product they never see. Founders must build not just a product, but a distribution engine to reach their customers effectively.

QWhat final, crucial quality does the article say cannot be taught but is essential for founder success, using Cursor as an example?

AThe final, crucial quality is resilience, grit, and the refusal to give up. The article emphasizes this cannot be taught, only experienced. Using Cursor as an example, it highlights that they spent years building before the market was ready, faced repeated rejection (like ignored Hacker News posts and DMs), and persisted through difficult periods where the path forward was unclear.

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Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

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What is AGENT S

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