Warp Factories нь програм хангамж хөгжүүлэлтийн үйл явцыг автоматжуулах дэд бүтцийн шийдэл бүхий платформыг нэвтрүүллээ.
Хиймэл оюун ухааны салбарт програм хангамж хөгжүүлэлтийн үйл ажиллагааг оновчтой болгох зорилгоор Warp компани “Warp Factories” системийг мягмар гарагт танилцууллаа. Энэхүү шийдэл нь хөгжүүлэлтийн уламжлалт үе шатуудыг агент дээр суурилсан автоматжуулалтын аргаар гүйцэтгэхэд зориулагдсан дэд бүтцийн давхарга юм.
Warp-ын гүйцэтгэх захирал Зак Ллойд уг системийг бие даан хөгжүүлэх нөөц бололцоо багатай жижиг компаниудад зориулан бүтээснээ онцолсон байна. Тус систем нь програм хангамжийг эрэмбэлэх, тодорхойлох, хэрэгжүүлэх, хянах болон баталгаажуулах зэрэг үндсэн үе шатуудыг автоматжуулж, хөгжүүлэлтийн ажлыг хялбарчлах боломжийг олгодог.
Хэрэглэгчид өөрсдийн сонгосон кодчилолын загвар болон хэрэгслүүдийг ашиглах боломжтой бөгөөд уг систем нь Codex, Claude Code зэрэг технологиудтай бүрэн нийцдэг. Мөн Linear, Jira, Slack, Teams зэрэг ажлын урсгалын удирдлагын системүүдтэй нэгтгэгдсэн нь багийн хамтын ажиллагааг сайжруулахад чиглэжээ.
Warp Factories нь зөвхөн код бичихээс гадна менежерүүдэд гүйцэтгэлийг хянах, зарцуулалтыг тооцох, үйл явцыг оновчтой болгох боломжийг олгодог. Гэвч энэхүү систем нь инженерүүдийг бүрэн орлох бус, харин хиймэл оюун ухааны агентуудтай хамтран ажиллах нөхцөлийг бүрдүүлэхэд чиглэж байгааг тус компани тодотголоо.
Дэлгэрэнгүйг эх сурвалжаас харах
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Companies are still grappling with exactly how software development should work in the AI area, but one early answer is the so-called software factory. Essentially an agent loop that’s built around the traditional stages of software development, the software factory approach has become a popular way for companies to remake their engineering organizations for the AI era.
Now, a system from Warp could make that transition a lot easier. On Tuesday, the AI coding company introduced Warp Factories, a new system designed to make building and operating AI software factories as easy as possible.
Operating as an infrastructure layer, Warp Factories gives companies a simple environment for deploying agents and a roadmap for how to use them.
To be clear, many companies are already having success with the factory model without any help from Warp. Stripe has been particularly public about its technical progress, developing a “minions” system to automate development within its own codebase. Ramp has made similar progress, developing a background agent that can monitor its own code after it is deployed.
As Warp CEO Zach Lloyd sees it, the target market for Warp Factories will be smaller companies without the resources to develop a system from the ground up.
“[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.
In Warp Factories, the architecture is already built out of the box, with many of the most difficult decisions already made. Warp’s system is based on the standard phases of software development (triage, specification, implementation, review, and verification) but the agentic approach means any of those steps can be automated.
Users can choose their own coding model and harnesses as necessary; the system works as well with Codex as Claude Code. It also integrates with ticketing systems like Linear and Jira, and messaging systems like Slack and Teams, in an effort to plug in seamlessly to existing workflows.
Beyond just shipping code, Warp Factories will also give managers the tools to track how well the factory is performing. With all the agents running in the same environment, it’s easy to compare performance metrics for different configurations, and to keep an eye on the overall token spend. Warp Factory also allows for self-improvement loops to optimize the overall system, automating management of the process itself.
Even so, Warp Factories is not built to completely replace software engineers — just give them an easier way to collaborate with the new agentic workforce. In Lloyd’s own experience, there are still a lot of tasks that require a human at the wheel.
“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.”
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