The Rise of AI-Augmented Solo Founders: Redefining Team Structures in Early-Stage Startups

This preprint reports findings from 107 semi-structured interviews with “AI-augmented solo founders” across 15 countries (June–Nov 2025). Using thematic analysis (Braun & Clarke) and a Gioia-style coding structure (inter-coder reliability κ = 0.84), we examine how founders use AI tools to substitute for the early team functions of engineering, design, marketing, and operations and identify boundary conditions where augmentation breaks down (compliance, strategic judgment, trust, and relationship-heavy work). We propose the “Orchestrator Model”—tool-stack design, spec/prompt discipline, and evaluation loops—as an emerging capability enabling solo execution at early stages. The PDF includes a note clarifying that quantitative ranges are self-reported and indicative, as well as appendices with the interview protocol, codebook excerpt, coded transcript excerpts, and a stratified audit-log sample. This is an independent research project; creator affiliations reflect individual backgrounds and do not imply institutional sponsorship. We thank Geoffrey A. Moore and Prof. Poh Kam Wong for feedback on research framing and interpretation; any errors remain our own.