Warp Launches Software Factory for AI-Powered Development

AI is changing how companies build software, but many engineering teams are still figuring out the best way to organize development around increasingly capable coding agents.

One approach gaining traction is the idea of a software factory — essentially an automated workflow where AI agents handle different stages of software development, from identifying tasks to writing, reviewing and testing code.

Now, AI coding company Warp wants to make it easier for companies to build one.

On Tuesday, Warp introduced Warp Factories, a new system designed to provide the infrastructure companies need to deploy and manage AI agents across the software development process.

Rather than asking every company to build its own agent infrastructure from scratch, Warp Factories provides a ready-made environment for running agents, coordinating their work and measuring how well they perform.

Warp CEO Zach Lloyd believes the product could be particularly useful for smaller companies that don’t have the engineering resources to build such systems internally.

“If you look at things like running your agents in the cloud and steering those agents as they run, or bringing the work that they’re doing into your local environment, or setting up memory that goes across those agents, or setting up evals that go across those agents — it’s actually a huge infrastructure undertaking to do this right,” Lloyd told TechCrunch.

Turning the software process into an AI workflow

Warp Factories is built around familiar stages of software development, including triage, specification, implementation, review and verification.

The difference is that AI agents can be assigned to automate some or all of those steps.

The system comes with much of the underlying architecture already in place, meaning companies don’t have to make every infrastructure decision themselves before getting started.

That approach could help businesses move faster as they experiment with agent-based development.

Warp is not the first company to explore the software factory model. Some larger technology organizations have already built their own systems.

Stripe, for example, has publicly discussed its “minions” system, which uses coding agents to automate development work within the company’s codebase. Ramp has also built a background agent capable of monitoring its own code after deployment.

Warp’s pitch is that companies shouldn’t necessarily need Stripe-sized engineering teams to achieve something similar.

Companies can choose their AI models

Warp Factories is designed to work with different coding models and agent harnesses, giving users flexibility instead of locking them into a single AI system.

The platform can work with tools such as Codex and Claude Code. It also connects with popular workplace tools, including Linear and Jira for ticket management and Slack and Teams for communication.

That means companies can potentially add AI agents to workflows they already use instead of rebuilding their entire development process around a new platform.

The system also focuses on what happens after agents begin working.

Managers can monitor how different agent configurations perform, compare results and track overall token spending. Because the agents operate within the same environment, companies can collect performance data and use it to determine which setups are producing the best results.

Warp Factories also includes self-improvement loops, allowing the system to optimize parts of its own operation over time.

Humans are still part of the process

Despite the push toward greater automation, Warp isn’t positioning Factories as a complete replacement for software engineers.

Instead, the company sees the system as a way to help developers work alongside an increasingly capable AI workforce.

Lloyd said Warp currently automates roughly 30% to 35% of its tasks each week. He expects that figure to rise as AI models become better and systems gain more context and improved agent harnesses.

“We automate like 30% of our tasks, 30 to 35% on a weekly basis,” Lloyd told TechCrunch. “And as models improve, as the context improves, as the harness improves, I think that that number is going to go up over time.”

For companies looking to experiment with AI-driven development without building an entire software factory themselves, Warp is betting that an out-of-the-box infrastructure layer could make the transition significantly easier.

Also read : Wispr Raises $280M at $2B Valuation as AI Dictation Expands