Warp Launches Factories to Help Companies Build AI Software

Warp has launched Factories, a new infrastructure system designed to help companies deploy and manage AI coding agents across the traditional stages of software development without having to build the underlying framework themselves.

The system is aimed particularly at smaller companies that may lack the resources to develop their own AI software factory. Warp Factories provides a shared environment for running agents and a framework for integrating them into existing engineering workflows.

Warp Factories automates software development stages

Warp’s system follows the standard software development phases of triage, specification, implementation, review and verification. Companies can automate individual stages with AI agents while keeping human engineers involved where needed.

The platform supports different coding models and agent harnesses rather than requiring customers to use a single AI system. Warp says Factories can work with tools including OpenAI’s Codex and Anthropic’s Claude Code.

It also integrates with existing workplace software, including Linear and Jira for ticket management and Slack and Microsoft Teams for communication. The goal is to let companies introduce agent-based development without replacing their existing workflows.

Warp targets the infrastructure behind coding agents

Warp CEO Zach Lloyd said operating agents at scale involves more than simply selecting an AI coding model. Companies also need infrastructure to run agents in the cloud, steer their work, transfer results to local environments, maintain memory across agents, and evaluate their performance.

Some larger technology companies have already developed similar systems internally. Stripe has created a “minions” system to automate development work within its codebase, while Ramp has built a background agent to monitor code after deployment.

Warp is positioning Factories as an out-of-the-box alternative for organisations that do not want to build comparable infrastructure themselves.

Managers can track performance and AI spending

Factories also provides tools for measuring how different agent configurations perform. Because agents operate within the same environment, teams can compare performance metrics and monitor overall token spending.

The system supports self-improvement loops intended to optimise the software factory’s operations. Warp is not presenting the technology as a replacement for engineers, however. Lloyd said Warp currently automates about 30% to 35% of its tasks in a typical week, with humans still required for many parts of the development process.