Mike Vizard talks with Teana Baker-Taylor, CEO of BasedAI, about why many enterprise AI projects remain stuck in costly experiments rather than delivering measurable business outcomes. Baker-Taylor explains how token shock, frontier model costs, data privacy, context engineering, agent permissions and workflow architecture all determine whether AI becomes useful infrastructure or expensive theater. The conversation also covers open source models, human-in-the-loop governance, AI workers, model flexibility, agentic payments and why organizations need to match the right model and agent workflow to the right business problem.