Warp, the AI-focused terminal and coding-agent company, launched Warp Factories in closed beta, an infrastructure layer designed to let engineering teams run and manage groups of AI coding agents working through a structured pipeline rather than interacting with agents one prompt at a time. The system frames software development as a repeatable "software factory" process: a coding agent picks up a ticket, drafts a technical spec, implements the change, runs a review pass, verifies the result against tests, and hands off monitoring, with humans supervising the pipeline rather than driving each individual step. This is a meaningful shift in framing from where AI coding tools started. Early tools were essentially smarter autocomplete or single-turn chat assistants bolted onto an editor; more recent products from OpenAI, Anthropic, Google, Cursor, and others increasingly behave like autonomous contributors that can read a whole repository, make multi-file changes, run and debug tests, and iterate toward a working solution without constant hand-holding. Once agents can do that, the bottleneck stops being "can the agent write good code" and starts being "how do we assign work to a dozen agents at once, control what each one is allowed to touch, review what they produced, audit what happened when something breaks, and keep them from stepping on each other or on production systems." That's the specific problem Warp Factories targets: permissioning, orchestration, and observability for agent fleets, rather than underlying model quality. For engineering leaders evaluating whether and how to scale agentic coding beyond individual-developer use, this points to a fast-emerging category, agent orchestration and governance tooling, that's likely to become as consequential to real-world AI coding adoption as the coding models themselves, since most of the risk and cost in deploying agents at scale comes from process and permissions, not raw capability. Being in closed beta, the practical impact will depend on how quickly Warp opens access and how the tooling handles real production codebases rather than demo repositories.