How To Get AI Startup Ideas

The hosts share advice for technical people who see promise in AI but have not found an idea they want to pursue. Jared Friedman warns that founders often gravitate toward ideas they can build in a weekend, while promising ideas may take more effort. Gary Tan recommends looking deeply into your own experience or going out to learn how other people and industries work.

Diana Hu describes founders who found problems through specialized experience: Salient's founder saw manual loan collection work at Tesla, and Diode Computer's founders combined hardware and software knowledge to build a circuit board copilot. The hosts also discuss Spur, whose founder saw front-end testing challenges at Figma, and Datacurve, whose founder drew on an internship at Cohere to build data tools for AI. They recommend looking for problems close to expertise built through jobs, research, or internships.

The hosts suggest visiting workplaces, shadowing people, or taking a job to understand tasks that software could improve. Examples include S&S Health, which built an AI back office for dental practices after a founder observed insurance administration, and Sweetspot, which automated government contract discovery after a founder's friend described the manual process. They also point to outsourced and temporary remote jobs as places to investigate repetitive computer work.

The hosts encourage founders to use emerging technology and talk with people who build at the frontier, so they can notice problems others have not solved. PreDB found a database and search opportunity through conversations with technical founders, while Reducto learned about document extraction needs from builders working on retrieval applications. Juicebox's founders also developed user knowledge while building a freelancer marketplace, which led them to PeopleGPT, a search product for recruiters.

Founders should not rule out an idea just because competitors exist, the hosts argue. Giga moved from fine-tuning models to customer support and won an enterprise opportunity by delivering on a difficult technical problem. The hosts note that it took about a year to find the right idea, and say changing AI capabilities can create new opportunities over time.