Lessons from Scott Wu

Scott Wu, a prominent figure in the world of competitive programming and the co-founder and CEO of the AI company Cognition, has shared numerous insights throughout his journey. From his early days as a math prodigy to leading a company at the forefront of AI development, his perspectives on learning, problem-solving, and the future of technology are highly sought after.

On Learning and Problem-Solving

On the core of competitive programming: "Competitive programming is simply the art of telling the computer what you want it to do." [1][2]
On improving coding skills: To improve coding mechanics and algorithmic knowledge, one must "read some problems, solve some of them, give up on the hard ones, think about them, do some research, read them again, repeat." [3]
On tackling new problems: "Don't try to program for the sake of programming. Instead, come up with an actual problem you want to solve. Having a problem to solve will immediately give you structure." [3]
On getting stuck: A user on a forum referenced Scott Wu's advice, stating that if you're stuck on a problem for more than 15 minutes, you should look up the solution immediately. This allows for more efficient learning. [4]
On self-improvement: A key takeaway from his competitive experience is "the willingness to be very brutally honest with yourself... the ability to to just examine your own flaws." [5]
On the value of competitions: His background in math and programming competitions framed his approach to business challenges, viewing them as "math puzzles." [6]
On the path to mastery: After not winning a prize in his first middle school math competition in second grade, he was "really upset about it" and "trained a bunch." The next year, he won. [5]
On the nature of intelligence: Referencing Andrej Karpathy, he highlights the concept of "jagged intelligence" in AI, where it can be superhuman in some areas and poor in others. This underscores the value of human-AI collaboration. [7]
On the importance of fundamentals: He notes that computer science classes often teach "how do you think about breaking down logical problems... how do you think about the model of a computer and what a computer can and cannot do," which are foundational skills. [7]
On working backwards: "The best advice I can offer is to analyze and work backwards from the desired result... It's actually applicable to so many teams... because it helps leaders and teams figure out what their desired end state is." [8]

On Artificial Intelligence and the Future of Software Engineering

On the future of software engineering: "The future of software engineering is you telling your computer 'Here's exactly what you need to build,' and it just happens." [7]
On the role of AI: He sees AI technology not as replacing programmers, but as democratizing software creation. [1][2]
On the evolution of programming: "We talk about programming languages and architectures and all these things, but at the end of the day, you know, the whole point of software engineering is just to tell your computer what to do." [7]
On the impact of AI on productivity: With tools like Devin, "we can do not just like 10% or 20% gains, but more like 10x." [7]
On the timeline for AI advancement: Scott Wu predicts that AI will surpass the world's best competitive programmer within 1-2 years. [1][2]
On human-AI interaction: "Humans plus AI really is the way to go at least for for for the foreseeable future." [7]
On the adoption of AI: He believes there will be a "much smoother curve of call it AI adoption" rather than a sudden shift. [6]
On the nature of AI agents: He describes Devin, their AI software engineer, as a "junior engineer" that can handle tasks asynchronously, much like an intern. [9][10]
On the current state of AI: He notes that AI models are not yet at a point where you can "shove the entire code base and the history of everything that ever happened in the context and then you know the model decides what to do." [6]
On the importance of data: "I think AI will generally be able to to kind of get to like like peak human capabilities or even above human capabilities... by setting up the right synthetic data loops." [5]
On the development of AI: "A lot of what happens next is really just like understanding and really defining the benchmark." [7]
On why coding is a prime use case for AI: "One of the reasons that code is growing so quickly is because you have this really great feedback loop of success or failure... in code you can run the code." [7]
On the future role of engineers: He believes there will still be a role for deeply technical people who can "iterate with the computer better." [7]
On the creative potential of AI: "We've been spending our whole lives in Minecraft survival mode, and now we're going to get to play Minecraft creative mode." [7]
On the vision for Devin: His vision is to "revolutionize software development by having Devin work alongside human engineers, automating tasks and enabling teams to achieve more ambitious goals." [11]

On Leadership and Building a Company

On the mindset of a founder: He felt he wanted to start his own company from a young age, even telling his fourth-grade math teacher he would hire him as a software engineer one day. [7]
On building a team: The Cognition AI team has a high concentration of former founders, which "gives you a lot of fire... to just be like you know this this is the one you know we're going to make this the really really big one." [7]
On the importance of a "big picture" view for IT teams: "IT teams have to start thinking bigger... IT teams are typically built for a single purpose: to react to customer issues, and then fix them." [8]
On scaling IT: "The only way break-fix teams have been able to scale, historically, is by hiring more and more people... One way they can adapt and better prepare for the future is to look into automation and root cause analysis." [8]
On the value of technical founders: "I think it's even better now than ever to be you know a very technical founder because not only is the product that you're building technical but all of the decisions that you're making are obviously heavy heavily technical as well." [6]
On communicating the 'why': "Being able to communicate their 'why' to the business helps IT leaders design more effective solutions." [8]
On creating a learning environment: He advocates for using public channels for AI and human collaboration to create better learning environments for both. [10]
On institutionalizing AI: A key to adoption is "institutionalizing Devin as first line of response." [9]
On the founding of Cognition AI: The company was co-founded in 2023 with the goal of building powerful AI systems that can write code like humans. [12]
On the talent at Cognition AI: The founding team has an "unparalleled concentration of elite competitive programming expertise." [12]

On Personal Philosophy and Drive

On his competitive nature: "I was always very very competitive as a kid." [5]
On his early life: Math and programming competitions "were kind of my uh my whole life honestly like as a kid." [5]
On his identity: "I am I am actually American and an optimist." [7]
On perseverance: His journey from a disappointing first competition to becoming a champion showcases his dedication. [5][7]
On the entrepreneurial spirit: His early declaration of wanting to start a company demonstrates a long-held ambition. [7]
On the impact of his work: He believes his contributions to AI are having a "significant impact on the software industry and the broader economy." [12]
On the relentless pursuit of knowledge: His story is described as one of "innovation, perseverance, and the relentless pursuit of knowledge." [12]
On the future of his work: He and his team are "far from done" and the future of Cognition AI looks promising. [12]
On the importance of hard work: His success is a testament to the power of focused effort and training. [5]
On the value of early talent: His story is an example of "how early talent can blossom into something truly amazing." [12]
On the transition from academia to industry: He chose to work at Addepar for a year and a half before college to gain real-world experience. [7]
On the intensity of his work: He feels like the last year and a half at Cognition has been a continuous "hackathon." [7]
On the heretical view of AGI timelines: "I'm not sure that an AGI timeline actually really matters" for practical AI adoption. [6]
On the human experience of time: He finds it interesting how time can feel like it's passing "really fast in the moment but then it also clearly like passes really slowly in the sense that you know there's a lot happening on a daily basis." [6]
On the core of his thinking: "A lot of my kind of my framing has always been rooted in terms of math math and and these kinds of math puzzles is almost how I describe it you know it's like even when we're going and doing a sale or something or when we're uh figuring out product strategy like in my head it all actually like maps to just like doing math questions." [6]

Learn more:

Lessons from Scott Wu

On Learning and Problem-Solving

On Artificial Intelligence and the Future of Software Engineering

On Leadership and Building a Company

On Personal Philosophy and Drive

Written by Antoine Buteau

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