Sequoia America: How to Capitalize on the Trillion-Dollar Opportunity of AI?

Written by: Deep Thinking Circle

While the entire tech industry is still busy chasing the wave of AI, Sequoia Capital has already begun to contemplate the deeper opportunities behind this technological revolution. At their annual AI Ascent conference, three core partners, Pat Grady, Sonya Huang, and Konstantine Buhler, shared their unique insights into the trends of AI development and market opportunities.

This speech was not filled with intimidating technical jargon, but rather revealed how AI is changing the business world and our lives using simple and understandable language. From market size to application layer value, from data flywheels to user trust, they unveiled the key success factors for AI entrepreneurship. More importantly, they predicted the arrival of the AI agent economy and how it will fundamentally change the way we work. For entrepreneurs and investors, this presentation revealed a clear signal: the AI wave has arrived, and now is the time to move forward at full speed. Don't worry about the noise of the macroeconomy; the wave of technology adoption is enough to drown out any market fluctuations.

If you want to understand why Sequoia believes the AI market is ten times larger than cloud computing, how startups can succeed in this field, and how the upcoming "agent economy" will disrupt our world, this interpretation offers you a firsthand feast of ideas.

Market Opportunities: Why AI is a Trillion-Dollar Wave

At the beginning of the speech, Pat Grady raised several key questions: What is AI? Why is it important? Why now? And what should we do? This framework comes from the legendary founder of Sequoia Capital, Don Valentine, who uses these questions to evaluate every emerging market.

At last year's AI Ascent conference, Sequoia presented a comparison chart, with one line showing cloud computing transformation and the other line showing AI transformation. Now, cloud computing has become a massive industry worth $400 billion, larger than the entire market when the software market was just starting out. By this analogy, the starting market for AI services should be at least an order of magnitude larger, that is, ten times the early cloud computing market. In the next 10 to 20 years, this market could become extraordinarily large, far beyond our imagination.

This year, Sequoia updated their perspective, believing that AI is not only consuming the service market's cake but is also eating into the software market's cake. We have seen many companies start with simple software tools and gradually become smarter, evolving from the "co-pilot" mode to the almost fully automated "autopilot" mode. These companies are shifting from selling tools to selling outcomes, moving from competing for software budgets to seizing human resources budgets. AI is simultaneously impacting these two huge markets.

Every technological revolution in history has been larger than the previous one, and AI is coming faster than any previous technological revolution. Pat explains why this is the case with a simple analysis: to analyze the physical laws of technology propagation, you only need three conditions – people must know your product, they must want your product, and they must be able to get your product. Compared to when cloud computing was just starting out, AI is gaining popularity at an astonishing rate. Marc Benioff, the founder of Salesforce at the time, had to resort to various "guerrilla" marketing tactics to attract attention, and as soon as ChatGPT was released on November 30, 2022, the eyes of the world immediately focused on AI. At the same time, there has been a significant increase in channels for sharing information, with Reddit and Twitter alone now ( rebranded X) with 1.2 billion to 1.8 billion monthly active users. Internet users have also grown from 200 million that year to 5.6 billion today, covering almost every home and business in the world.

"This means that the infrastructure is already in place, and when the starting gun goes off, there are no barriers to adoption," Pat explained, "This is not a phenomenon unique to AI; it is a new reality of technology distribution, and the physical rules have changed. The tracks have been laid."

Application is the high ground of value: How to win in the AI era

Looking back at several major technological revolutions in history, whether it is personal computers, the internet, or mobile internet, most of the companies that have truly achieved over a billion dollars in revenue are concentrated in the application layer. Sequoia firmly believes that the AI field will also follow the same rule: the real value lies in the application layer.

But now the situation is different. With the advancement of large models, they have been able to penetrate deep into the application layer through inference capabilities, tool usage, and communication between agents. If you're a startup, how do you deal with that? Pat suggests starting from the customer's needs, focusing on specific verticals, focusing on specific functions, and solving complex problems that may require people in the ring. That's where the real competition comes in, and that's where the value comes in.

What is special about building an AI company? Pat stated that 95% of the content is no different from building an ordinary company - solving important problems, finding unique and attractive ways, and attracting top talent to join. Only 5% is unique to AI, and he specifically emphasized three points:

First, be wary of "vibe revenue" (vibe revenue). Pat explains that many entrepreneurs like "vibe revenue" because it feels good, and the company seems to be growing rapidly, but in reality, this may just be customers testing the waters, rather than a real change in behavior. He advises founders to closely examine user adoption rates, engagement, and retention to see what people are actually doing with the product. Don't deceive yourself into thinking you have real revenue when it's just "vibe revenue"; this will ultimately harm you.

"At the current stage of development, trust is more important than your product. Pat emphasized, "Products will gradually improve, and if customers trust that you can make it better, you're fine; if they don't trust you, you're in trouble."

Secondly, gross margin. Pat stated that they do not necessarily care about the current gross margin of the startup, as the cost structure in the AI field is changing rapidly. Over the past 12 to 18 months, the cost per token has decreased by 99%. If entrepreneurs successfully shift from selling tools to selling outcomes and move upstream in the value chain, the price points will also rise. Although the current gross margin may not be ideal, the company should have a clear pathway to a healthy gross margin.

Third, the data flywheel. Pat asked the entrepreneurs in the audience: "Who has a data flywheel? What business metrics can this data flywheel drive improvement in?" He pointed out that if this question cannot be answered, then the so-called data flywheel may just be a fantasy. It must be linked to specific business metrics; otherwise, it is meaningless. This is particularly important because the data flywheel is one of the most powerful moats that startups can build.

At the end of the speech, Pat used an interesting metaphor: "Nature abhors a vacuum." He said that there is a tremendous "pull" for AI in the market right now, and all the macroeconomic noise, such as tariffs and interest rate fluctuations, is irrelevant. The upward trend of technology adoption completely overshadows any fluctuations in the market. "There is a huge pull in the market, and if you don't seize the opportunity, others will. So, regardless of what we talked about earlier regarding moats, indicators, and the like, you are now in an industry where you need to run desperately. It's time to go all out and keep moving at maximum speed at all times."

From speculation to real value: AI's user engagement has significantly increased.

Next, Sonya Huang reviewed the significant progress in AI applications over the past year. She shared an exciting piece of data: in 2023, the ratio of daily active users to monthly active users for native AI applications was (DAU/MAU) very low, indicating that users were curious to try them but did not use them frequently, with hype far exceeding actual value. However, the situation has dramatically reversed. The daily/monthly active ratio of ChatGPT has been climbing steadily and is now approaching the level of Reddit.

"This is great news," Sonya said excitedly, "which means that more and more of us are deriving real value from AI, and we are all learning together how to integrate AI into our daily lives."

This usage has both a relaxed and fun side, as well as profound practical value. Sonya admits that she personally burned an astonishing number of GPUs to try "Ghibli-izing" various images. But beyond these interesting applications, what is even more exciting are those deeper applications, such as in the advertising field where incredibly precise and aesthetically pleasing ad copy can be created, in the education field where new concepts can be visualized instantly, and in the healthcare field with applications like OpenEvidence that can better assist in diagnosis.

"We have only just scratched the surface of possibilities," Sonya said, "As the capabilities of AI models continue to improve, the things we can do through this 'front door' will become increasingly profound."

The breakthrough of voice technology and the explosion of programming: two key areas

In 2024, there are two particularly noteworthy breakthroughs in the field of AI. The first is voice generation technology. Sonya refers to it as the "Her moment" in the realm of voice, citing the story in the movie "Her" where Joaquin Phoenix falls in love with an AI assistant. Voice generation technology has completely crossed the "uncanny valley" from being "almost mature" and has reached a level that is almost indistinguishable from reality.

At the scene, Sonya played a voice demonstration that sounded so natural that it was difficult to distinguish whether it was human or AI. "The gap between science fiction and reality is closing at an astonishing speed, and it feels like the Turing test has quietly arrived at our doorstep."

The second key breakthrough is in the programming field. Sonya pointed out that this area has reached a "screaming product market fit" (screaming product market fit). Since the release of Anthropic's Claude 3.5 Sonnet last fall, there has been a rapid "vibe shift" (vibe shift) in the programming field. People are now achieving impressive results with AI programming, such as someone creating an alternative to DocSend using "vibe coding".

"Whether you are an experienced '10x engineer' or someone who knows nothing about programming, AI is fundamentally changing the accessibility, speed, and cost-effectiveness of software creation," Sonya explained.

From a technical perspective, although the progress of pre-trained models seems to be slowing down, the research ecosystem is looking for new breakthroughs. The most significant advancement is OpenAI's reasoning capabilities, while technologies such as synthetic data, tool usage, and AI agent orchestration (AI scaffolding) are also rapidly developing. These factors combine to create artificial intelligence capable of completing increasingly complex tasks.

Where value is generated: The battlefield at the application layer is heating up.

Sonya recalled the debates she once had with her colleagues about the value creation of AI. She admitted that she had been skeptical about GPT packaged applications at the time, while her partner Pat firmly believed that value would be generated at the application layer. It seems now that Pat was right. From the perspective of actual value creation, companies like Harvey and OpenEvidence, which focus on customer needs, have indeed created tremendous value.

"We firmly believe that the application layer is where value ultimately converges," Sonya said, "and as foundational models increasingly penetrate this layer, the battlefield is becoming more and more intense."

Of course, she jokingly pointed out that the real winner might be NVIDIA's CEO Jensen Huang, whose company has reaped enormous profits from AI chip sales.

Sonya believes that the first batch of "killer applications" of AI has already emerged. In addition to well-known applications such as ChatGPT, Harvey, Glean, Sierra, and Cursor, there is a new wave of companies rising in various professional fields. She specifically mentioned that many new companies will be "agent-first" ( agent-first ), and the agents they sell will evolve from simple, makeshift prototypes into truly powerful products.

Vertical agents: AI agents specialized in specific domains

In the smart agent market of 2025, Sonya is particularly optimistic about the development of vertical agents (vertical agents). This provides excellent opportunities for entrepreneurs who are deeply engaged in a specific field. These vertical agents are trained end-to-end for specific workflows, using reinforcement learning techniques that include synthetic data and user data, enabling AI systems to perform exceptionally well on very specific tasks.

There have been exciting early cases. In the security field, Expo demonstrated that their AI could surpass human penetration testers; in the DevOps field, Traversal created AI troubleshooters that are better than the best human troubleshooters; in the networking field, Meter's AI has also outperformed network engineers.

Although these cases are still in the early stages, they give us reason to believe that vertically trained intelligent agents for solving specific problems can outperform today's best human experts.

Sonya also proposed the concept of "abundance era" (abundance era). Taking programming as an example, what happens when labor becomes cheap and abundant? Will we end up with a lot of low-quality content generated by AI? What happens when "taste" (taste) becomes a scarce asset? The answers to these questions will indicate how AI will change other industries.

Intelligent Agent Economy: The Next Important Phase of AI

In the final part of the speech, Konstantine Buhler looked forward to the next important phase of AI - the "agent economy" ( agent economy ). A year ago, the AI Ascent conference had already begun discussing agents, at a time when these machine assistants were just starting to form business models. Today, these networks of machines known as "agent swarms" ( agent swarms ) have played an important role in many companies, becoming a key part of the AI technology stack.

Konstantine predicts that in the coming years, this will further develop into a smart agent economy. In this economy, agents not only transmit information; they can also transfer resources, conduct transactions, record behavior mutually, understand trust and reliability, and possess their own economic systems.

"This economic system does not exclude humanity; it is entirely centered around humans," Konstantine explained. "Intelligent agents cooperate with people, and people collaborate with intelligent agents, together forming this intelligent agent economy."

Three major technological challenges in building the agent economy

To achieve this grand vision, we face three key technical challenges:

The first challenge is persistent identity (persistent identity). Konstantine explains that persistent identity actually encompasses two aspects. First, the agent itself needs to maintain consistency. If you are dealing with a business person who changes every day, you are unlikely to have a long-term collaboration. The agent must be able to retain its own personality and understanding. Second, the agent needs to remember and understand you. If your partner knows nothing about you, or can hardly remember your name, this will also pose a challenge to trust and reliability.

Current solutions such as RAG (, retrieval-augmented generation ), vector databases, and long context windows are all attempting to address this issue, but there are still significant challenges in achieving true memory, memory-based self-learning, and maintaining agent consistency.

The second challenge is seamless communication protocols. "Imagine what personal computing would be like without TCP/IP and the internet," Konstantine said, "we are only just beginning to build the protocol layer between agents." He specifically mentioned the development of the MCP ( Model Collaboration Protocol ), which is just one of a future series of protocols aimed at achieving information transfer, value transfer, and trust transfer.

The third challenge is security. When you cannot communicate face-to-face with partners, the importance of security and trust becomes even more prominent. In the agent economy, security and trust will be more important than in the current economy, giving rise to a complete industry centered around trust and security.

From Determinism to Randomness: A Fundamental Shift in Thinking

Konstantine believes that the arrival of the agent economy will fundamentally change the way we think. He proposed the concept of "stochastic mindset" which is completely different from traditional deterministic thinking.

"Many of us fell in love with computer science because it is so certain, " he explained, "you program the computer to do something, and it will do it, even if the result is a segmentation fault. Now, we are entering an era where computation will have randomness."

He used a simple example to illustrate: if you ask a computer to remember the number 73, it will remember it tomorrow, next week, and next month. But if you ask a person or an AI to remember it, they might remember 73, or they might remember 37, 72, 74, or the next prime number 79, or even forget it entirely. This shift in thinking will have profound implications for how we handle AI and intelligent agents.

The second change is the management mindset (management mindset). In the agent economy, we need to understand what agents can and cannot do, which is similar to the process of transitioning from independent contributor to manager. We will need to make more complex management decisions, such as when to halt certain processes, how to provide feedback, and so on.

The third major change is the combination of the first two: we will have stronger leverage, but the certainty will significantly decrease. "We are entering a world where you can do more things, but you must be able to manage this uncertainty and risk," Konstantine said, "In this world, everyone present is very well suited to thrive."

The Ultimate of Leverage Effect: Reshaping Work, Companies, and Economy

A year ago, Sequoia predicted that various functional departments within organizations would begin to possess AI intelligences and gradually integrate, ultimately leading to entire processes being completed by AI intelligences. They even boldly predicted the emergence of the first "one-person unicorn company."

Although the "one-person unicorn" has not yet been realized, we have already seen companies expand at an unprecedented speed, using fewer people than ever before. Konstantine believes that we will reach an unprecedented level of leverage.

"Ultimately, these processes and agents will merge to form a network of neural networks," he envisioned, "this will change everything, reshape individual work, restructure company structures, and reshape the entire economy."

The three partners of Sequoia outlined a clear path for the evolution of AI from its current development to potential future changes through this speech. From a macro analysis of market opportunities to insights on application layer value, and then to the vision of the intelligent agent economy, they not only explained the What and Why, but more importantly, indicated the How - how to seize the initiative and create value in this trillion-dollar opportunity.

For entrepreneurs, this is not only a feast of ideas but also a guide to action: seize the value of the application layer, build real revenue rather than an "atmosphere," establish a data flywheel, prepare for the upcoming intelligent economy, and always remember — now is the time to go all out and maintain maximum speed forward.