At 22, Anderson Chen put $80,000 into an industrial AI startup

Chen started Operon during his first gap year while studying chemical engineering and business at Nanyang Technological University. The San Francisco-based company develops AI tools to automate work traditionally done by operators and specialists in manufacturing, oil and gas, and construction. Chen said Operon grew exponentially toward the end of that first year, leading him to take another year off.

He initially expected to finish his degree, and said leaving college was frightening: a bachelor’s degree is considered the Asian standard, and his parents first worried he was struggling at school. His expenses during the gap year were covered by a fellowship, he said. His parents have since accepted his decision. Chen also believes rapid progress in AI is changing the value of a degree. He recalled a fluid dynamics professor telling him during his sophomore year that a version of the Navier–Stokes problem was unsolvable; he later saw OpenAI solve a version of it.

Chen said internships at manufacturing companies and conversations with manufacturers and founders in Taiwan helped reveal a gap: engineers were feeding technical PDFs into ChatGPT, but leading AI models could not interpret confidential documents they had not been trained on. Operon is building a context layer to organize heavy-industry information and support AI workflows, he said.

In May, Operon received Y Combinator backing as part of a $700,000 pre-seed round with other investors, which Chen said closed in about three days. The startup has about 20 clients, ranging from proof-of-concept projects to full contracts. Its five-person team is all under 30; the oldest member is 26 and the youngest is 16. Chen said he is not drawing a salary, though the company pays its employees. He earned the money he invested through earlier ventures, including sneaker sales, Amazon dropshipping and a tutoring agency he built while in college.