Luke Shiels

Luke Shiels
Occupation	Founder and CEO of Interfere
Known for	Interfere, a self-healing software platform

Luke Shiels is a design engineer and entrepreneur who is the founder and CEO of Interfere, a software company developing what it describes as the "self-healing layer of the internet." Interfere is an AI-powered platform that automatically detects, triages, and fixes user experience bugs in software products before users are significantly affected.

Career

Before founding Interfere, Shiels worked at several technology companies. He was a founding member of Delphi, where he helped build digital representations of the human mind. He also held roles at Tabs and Structure. Shiels has described himself as a "0 to 1 design engineer and advisor" focused on next-generation product interfaces and user interaction. Prior to his career in technology, he trained as a commercial airline pilot in Europe.

Shiels has written about his early interest in design, describing it as a "happy accident" that began in childhood. He taught himself interface design through observation, and developed an interest in calligraphy and logo design as a young person. He publishes a weekly Substack newsletter called Standard Aesthetics, covering the intersection of design, taste, and technology.

Interfere

Shiels founded Interfere and launched the company as part of Y Combinator's Summer 2025 (S25) batch. The company secured approximately $1.7 million in funding from Y Combinator, Worldbuild Ventures, Soleio, and other investors. Interfere positions itself as an "experience layer for modern product teams," offering automated detection and resolution of software bugs and UX issues. The platform monitors deployed software for anomalies — such as spikes in error rates following a deployment — and can suggest or implement fixes without requiring human intervention.

The company is based in New York City. Shiels has described the product's mission as building software that "never breaks," aiming to reduce the burden on engineering and product teams by automating the identification and correction of issues that would traditionally require manual debugging and triage.