Factory.ai

Factory.ai is an AI project builder tool. Factory's AI Project Manager turns Linear and Jira tickets into autonomous coding work: assign an issue or mention @Factory, and a Droid extracts context, implements a fix and prepares a pull request with traceability back to the ticket.

Factory's AI Project Manager connects project management tools to autonomous coding agents called Droids. Rather than opening a separate chat window and pasting context, a team member assigns a ticket to Factory or mentions @Factory in a comment, and an agent picks up the work. The agent reads the issue body, the discussion thread, linked references and related tickets, then implements a solution and produces a diff that can be reviewed and turned into a pull request without leaving the tracker. The practical value is in the handoff. A product manager can write a feature request in plain language and let the implementation start on its own, while bug reports and customer feedback can be routed to agents automatically through triage rules that key off labels, priority or custom criteria. Because the pull request keeps its connection back to the originating ticket, there is a traceable path from reported problem to merged code, which matters for teams that need an audit trail or work under compliance constraints. Factory positions Droids as persistent across the workflow. The same agent knowledge can follow a team from the terminal and IDE into the browser, Slack, Jira and a command line interface, so context is not rebuilt every time the tool changes. The intended adoption path is deliberately incremental: start inside the IDE, then extend into design documents, review automation and ticket assignment as confidence grows. The tool fits engineering and product organisations already standardised on Linear or Jira and comfortable letting agents write code against their repositories. It is not a general chat assistant and it does not replace human review; it shortens the distance between a written requirement and a reviewable change. Teams wary of sending proprietary code into unspecified models will want to examine Factory's security model first, since one published testimonial centres on exactly that concern for a fintech customer.