There’s currently a growing race in Silicon Valley to automate knowledge work, with startups racing to build systems that promise to handle more and more of the tasks typically managed by people.
But while automation can be powerful in theory, many of the tools built so far struggle to integrate into the natural rhythms of how employees actually work, leaving a gap between what this technology could achieve and what people actually experience in their daily productivity.
Nineteen-year-old Aidan Guo, co-founder of Attention Engineering, is working to close that gap. Rather than pursuing automation for its own sake, his company is focused on building an assistant that supports people directly in the context of their everyday workflows. The platform watches what’s happening on a user’s screen, giving it the context to step in when needed and reducing the time needed for routine tasks so that attention can be spent on higher-value thinking.
Learning How To Apply Technology To Entrepreneurship
Aidan Guo’s entrepreneurial instincts first began early. At thirteen, he began reselling limited-edition sneakers, waking early to stand in lines outside stores before turning to software to gain an edge.
By sixteen, he’d moved beyond reselling alone and started exploring how technology could help him scale. He created a Discord group that taught others how to automate sneaker purchasing, generating more than $300,000 in revenue with virtually no overhead.
The experience convinced him that his future lay neither in traditional education nor in traditional sales, but in the freedom that came with building systems that could scale far beyond what one person could do alone.
After a short stint at Carnegie Mellon University, he dropped out. The pace of classrooms felt sluggish compared to the momentum he found online, where new features like GitHub’s Copilot and the different iterations of GPT were empowering regular users to speed up their creative process, whether it was for creative work like writing or drawing, or for more technical tasks like coding. Aidan quickly realized this technology could serve as an accelerant, something that could let ambitious young builders leapfrog ahead of older, slower institutions.
How Attention Engineering Automates Tedious Work
Aidan’s leap into full-time entrepreneurship sharpened when he crossed paths with his co-founder, Julian Windeck, an Cambridge grad student with a background in distributed systems. The two began experimenting with side projects, one of which (an early jailbreak of Apple’s MacOS 26 Liquid Glass Beta) briefly went viral on Twitter. That early success crystallized their decision to launch a company together.
In mid-2025, the pair launched Attention Engineering, a startup that focuses on the growing friction in digital workspaces. Knowledge workers (whether they’re scientists, designers, mathematicians, or editors) spend hours jumping between tools, retyping the same context, and manually tracking conversations across disparate and disconnected platforms, wasting valuable time on mundane tasks instead of higher-priority work.
Attention Engineering solves this by providing a proactive, desktop-based assistant. Unlike chatbots that require prompts, their platform watches each user’s screen to build a searchable, contextual memory of their workflow. By understanding what tasks are underway, it can step in to handle routine follow-ups (summarizing a business meeting, drafting emails, or pulling up relevant files at the right moment) without requiring the user to switch between apps or re-enter information.
Their approach addresses a growing disconnect between how AI is sold and how it’s implemented: most startups built on this technology promise automation, but few deliver meaningful day-to-day value. By building for the practical needs of computer users, Attention Engineering avoids the trap of abstract demos that look impressive but fail to integrate into real workflows.
The partnership between Aidan and Julian gives the company both vision and execution. Aidan’s main focus is on distribution, capital, and bringing people on board, while Julian mostly handles the technical architecture and product development. The clear division of roles allows them to move at a steady pace, with Aidan steering direction and Julian ensuring the baseline technology can support it.
Aidan’s Vision For AI That Puts Humans First
Within weeks of launching, Aidan and Julian secured $1.25 million in early funding for Attention Engineering, drawing investors like Village Global, Worldcoin’s Max Novendstern, and Sequoia scouts DeepMind and Cognition. Many of the first checks came from mentors/friends of Aidan and Julian personally, with their initial backing creating momentum that larger investors quickly followed.
Aidan sees the backing as a reflection of two forces: Silicon Valley’s willingness to bet on young founders taking big swings, and the appeal of his underlying message. He frames Attention Engineering’s work as part of a larger argument about the direction of AI. In his view, the industry risks treating human savviness and expertise as expendable, chasing automation as an end in itself. His vision runs in the opposite direction: agents acting as amplifiers, helping people move faster and with greater precision while leaving judgment and decision-making in human hands.
In practical terms, this means that future assistants would essentially feel like capable junior colleagues rather than full replacements. A lawyer might rely on the software to draft follow-up notes after a client call, but it remains the lawyer’s responsibility to refine and approve them. To Aidan, this approach represents the most valuable and sustainable path to guarantee that this technology continues to meet practical use cases.
As he continues expanding Attention Engineering, Aidan Guo’s ambition reflects a long-term seriousness: a desire to grow a company that reshapes how people interact with their computers, without ever making people obsolete.