This is going to be the most promising technology in human history. AI is capturing the essence of cognition. In 2024 and 2025, coding became possible. And now we're starting to find that agents that do things end to end in other areas of knowledge work are possible. And even more recently, we're starting to see that fundamental discoveries in areas like biology and mathematics and physics are becoming possible. If humans can use AI to cure cancer, an evil human can use AI to make a bioweapon or do a cyber attack. We cannot succeed if we don't address these risks. And we are absolutely determined to get this right because this is why I and this is why many people who work at Anthropic, this is why we work on this technology.
Intelligence is now something humans can build. The implications of this are profound. We believe it will make every person far more capable and expand the world's capacity for cognitive work, transforming every industry and every discipline. This enormous economic impact begins with frontier intelligence, with what Claude can do. In 2024, Claude could answer a question, retrieve information, or summarize a document. By the end of 2025, Claude could do deep research and multi-step projects like refactoring an entire codebase, the type of task that required hours or even days of human work. Today, Claude can take on complex open-ended projects that once took months or years of research, analysis, and execution by many people and complete them in days. In the near future, we see potential for frontier AI to drive some of humanity's greatest breakthroughs and open entirely new markets.
Our success thus far emerges from five core advantages. These are our mission and focus, talent and culture, frontier research and safety work, our approach to compute, and our enterprise strategy. All of this begins with our mission: the responsible development and maintenance of advanced AI for the long-term benefit of humanity. It's an organizing force and key to our focused execution. We manage a universe of finite resources: compute, talent, and research capacity. The mission is how we create clarity for the team and deploy those resources to maximum effect at challenging moments that call for hard choices. Our mission sharpens our decision-making. It led us to deploy models like Mythos exclusively to cyber defenders. It also led us to commit to keep Claude free of advertising. This mission and focus continued to attract the very best talent in the industry. That's been true since our founding. Our seven co-founders include the originators of ideas that now make up the foundation of the AI industry. This concentration of top talent extends to all levels of the organization, and we lead the industry in attracting and retaining the brightest minds in the field.
Why do I work at Anthropic? Why do I work at... Why do I work? Yeah, why do I work at Anthropic?
Because I'm an optimist. I want to save a better world for my family and for humanity.
Three years ago, my older brother died of a brain tumor at the age of 42, which is the age that I am now. And I believe deeply that through our mission and this technology, there will be a situation where people like my brother don't have to die. Somebody has to carry the weight of getting this right, and I really didn't want to watch from the sidelines.
People here ask, "Is this the right thing to do?" before they ask, "Can we do it?" It's a rare combination of a group of people who care deeply about making AI go well and also care deeply about competence, coherence, integrity, qualities that actually make an organization effective. These benefits and these risks, this light and this shade, precisely why I chose to come to work at Anthropic.
The work we do to make our models safe and reliable is the same work that makes them more capable. We care about useful intelligence: how effectively a model handles a real-world task and the value this delivers to customers. We're relentlessly focused on answering the question: what can Claude do for me that other models can't? Compute is the critical infrastructure that enables this work. We've built a differentiated advantage here, not just in how we build our compute capacity, but in how we make the most of this capacity through the discovery of compute multipliers. We are the leading AI lab that has been focused on building for the enterprise from day one. We train our frontier models to address knowledge work. As a result, our customers get the best of both capability and value. These customers have enabled our historic growth, and they span industries across financial services, technology, pharma, healthcare, government, manufacturing, and more.
And this is also where our public benefit mission and safety focus find natural alignment. Enterprises care that the frontier is safe, trustworthy, and useful as much as we do. As frontier intelligence grows more capable, our dedicated focus on safety research becomes that much more important. It's critically important to our customers and necessary for realizing AI's full potential, and Anthropic is fully committed to doing this work with excellence. Our public benefit mission is what brought us to this point, and it will continue to shape our work, including at the governance level. In addition to our executive leadership and our board of directors, Anthropic is advised by the Long-Term Benefit Trust, an independent, financially disinterested body that selects a majority of our board. The LTBT's role is to help Anthropic plan for and fulfill our public benefit mission as we grow. We believe AI's future should be shaped and led by democratic societies. We want to be good partners in helping governments adapt to the changes that come with AI's rising capability. We do this at the executive level through the work of our policy team and through efforts like the Anthropic Institute, which shares research on how frontier AI shapes how we live our lives. We are still early in what we believe will be the biggest transformation of the human experience in the modern age, not just the profound economic potential, but in all the ways in which we believe AI can help humanity flourish, from curing diseases to accelerating growth to helping people live more fulfilled and abundant lives.
So if you think about our Claude model family, it's designed to deliver value across all the goals you might have. Whether you're optimizing for cost or speed or intelligence, at the top end, Mythos and Fable push the frontier forward. We see customers use it to harden cyber infrastructure or make new scientific discoveries. At the other end, we have models that are extremely capable and highly cost-effective, and businesses can rely on them at scale for well-defined routine tasks. A key thing we think about is how everyone can get the benefit of that whole spectrum of models. Because even as model capability increases exponentially, what most people do with the models doesn't change that fast. We think about three principles as we build. The first is meeting customers where they are. There's a few ways to use Claude. First is through our own applications like Claude Code or the Claude desktop or mobile app. But Claude is also available in enterprise applications like Word and Excel. We go deep into verticals and try to understand what does an expert in this domain need to be successful immediately. For instance, if you're a lawyer, we have a Claude for Legal bundle which connects directly to the tools you need. This is something we think about for every domain. We have bundles for healthcare, financial services, life sciences, and more.
Our second principle is that we build models and products side by side. We develop products for tomorrow's models, not just today's. Claude Code is a great illustration of why that matters. A couple of years ago, we could see that our pre-release models were getting better at understanding code. Couldn't quite do it all yet, but we could see the trend line. We built a product around that thinking, and Claude Code was launched just a few months later, that introduced people to an entirely new way of coding and of understanding what AI can do. This flywheel between model and product is a durable advantage in how we build. The model gets better. We develop new features powered by those advancements. Then we train the models to get even better at what people are trying to do, which reinforces the whole system. And we do that in coding and beyond.
Our third principle is that we close the gap between the frontier and customers' day-to-day. Most people still think about their AI tools as a replacement for search or a simple Q&A tool. And it can be those things, but that understates the power of what people can really do with this intelligence. This is where product becomes a meaningful competitive differentiator. Without a strong product, the difference between growing intelligence and where users are just keeps compounding. We think the future will involve making Claude feel as simple and natural as possible, so people everywhere can just treat Claude the same way you'd treat a colleague and get high-quality output every time. We think these three principles are how we bring frontier intelligence to everyone. This is what we mean when we say we want to give people superpowers. Claude starts by helping you do what you need to better and faster. Then it takes on the things you never would have tried because they were just too hard. And in the future, it means all of us doing what used to be impossible, so we can all live better, fuller lives.
When we discovered scaling laws in AI, we realized that AI capabilities could improve very fast. That's why we founded Anthropic: to ensure that if AI became a transformational technology, it would be safe and beneficial. Our fundamental bet is that AI would make tremendous progress this decade. These transformational capabilities are why research and safety must advance together. It's the only way we'll realize the benefits of the technology. We assess our models across three dimensions: capability, efficiency, and safety. We optimize our models to be able to plan and complete complex work accurately across hours and even days. A good example is Opus 5.5. One of our users was able to complete a 680K line code migration in less than a day. This would have taken an engineering team weeks just a few years ago. We think our models are the very best at this long-horizon work where accuracy really matters.
The capability begins in the model training process. In the pre-training phase, a model learns from the totality of human knowledge: text, images, scientific papers, code. This phase is where it comes to understand human concepts and ideas. The second phase is reinforcement learning. This is where Claude learns to be helpful, honest, and harmless. It's where we draw out useful capabilities in coding, knowledge work, and science. As models have moved from conversational assistance to autonomous agents, reinforcement learning has evolved into one of the largest areas of research investment, one that really matters to our customers. In 2021, I wrote an internal memo outlining how our most likely product might be an aligned AI programmer. I wrote a lot of other things, too, but this one turned out to be pretty accurate. Claude's training process is integral to Anthropic's mission. We need to understand how to train frontier intelligence and how to make it safe, and this is how we deliver the benefits of AI.
We think that AI will help us reduce the time to do a clinical trial by 20 to 30%. If you get a drug to market two or three years sooner, those are either cures or treatments that patients that actually don't have solutions can have sooner. So we think it's actually a huge win for patients, and it's also a huge win for BMS.
We chose Anthropic for a couple of reasons. One is they had the most mature enterprise capabilities. So it's one thing to have a chatbot that you can use. It's a whole different thing to actually put it in an environment where you're giving it access to some of the company's most confidential information, and you're able to do observability, manage the security, manage the fine-tuned controls of what you give users. So there's like the enterprise controls that you'd often see that IT organizations really value a lot. We rolled it out across all 30,000 of our employees. This is the fastest, most well-adopted AI tool in the history of what we've rolled out. So now you can ask a very, very complicated question, and it will go through, it will figure out which database or databases, because it can actually cross those databases, can be queried, and then it will produce a report that actually has the context of the epidemiology built right into it. So that takes you from what would have typically taken one to two months to get a simple question answered to being able to get it in four to five minutes. And we're now finally at a stage, both with high-throughput computation but also large language models, where you're able to scale up your computation, your analytics to match the better scale of biology that can help the way that you inform and change the standard of care.
Consider all the reasons a frontier AI lab needs to use compute efficiently. We use it at every stage of the research and model training process. It's how we serve models to customers and how we use Claude at scale internally. By training what we believe to be the most efficient models, we can do more of all these things with the same amount of compute. It's also how we drive down costs both for customers as well as our own underlying costs. We're accelerating these efficiency gains through our research process. Our pace of discovery is speeding up, and a lot of that acceleration comes from Claude itself. When you deploy frontier models, safety is critical. This idea brought the co-founders together, and it's been at the foundation of Anthropic from the beginning. Excellence in safety is how you manage organizational and systemic risk. It's how you safely enable frontier capabilities in fields like coding and medicine. And it's valued by our customers. It gives them the trust they need to point AI at important work. We build safety in at every stage. Through alignment training, we train models to follow user intent and avoid taking harmful actions. And we build in the right safeguards aimed at preventing misuse. We also pioneer fields like interpretability, which gives us insight into what's happening inside the model's brain. Within Anthropic, we increasingly turn frontier models back on improving our own processes. We call this closing the loop, and it drives forward all three of our research priorities. Claude is increasingly our equal partner here. The better Claude gets, the more it helps us with all of our work. It improves our security. It makes training and inference more efficient. It drives safety work. It helps us try out more research ideas more quickly. And it makes the whole organization more effective. Our most important work is still ahead. If we keep research and safety advancing together, we believe that we can help bring about some of the most significant breakthroughs in human history.
