The Tiny Team era is here (www.businessinsider.com)

The “Tiny Team” era describes a wave of AI-first startups—often fewer than 10 full-time employees—using large language models and agent tools to multiply output and cut costs. Founders and engineers at companies like Arcads AI, Aragon AI, Oleve and BoldVoice report that AI assistants (e.g., LLMs and tools such as Cursor for “vibe coding”) handle tasks from code optimization, debugging and data fetching to content generation, research and review. Teams say a single AI-augmented engineer can do the work of two-to-three people, and many workflows are now 40%+ AI-augmented, enabling much faster sprints, earlier profitability and smaller headcounts to reach scale. Technically and operationally, this shifts hiring and skill priorities: reading code and “commanding” AI agents matter more than narrow hard skills, and firms increasingly hire specialists to be amplified by AI. Practically, startups automate repeatable processes and use contractors seasonally, but limitations remain—AI doesn’t fully replace domain expertise, outputs must be vetted, and the pace creates real burnout and heightened pressure. The net implication for AI/ML is a new startup operating model that favors orchestration, human-in-the-loop oversight, prompt/agent design skills, and tighter candidate vetting over sheer manpower.