Factory has been most useful for me not so much in the “pair with me while I code” sense, but as a way to push certain classes of work into the background. Once a task is scoped clearly enough, a Droid can take it on: explore the relevant parts of the repo, make the changes, run checks, and leave a PR or other result for review. Being able to trigger that from the CLI or our existing workflows, rather than living inside one specific IDE, fits how our team already works.<br><br>The model flexibility helps as well. We can route heavier reasoning to stronger models while keeping routine work cheaper. For recurring or well-defined engineering chores, it cuts down on the number of small tickets that would otherwise interrupt deeper work.

The biggest difference is that Droids don’t stop at suggestions. I can hand off a real task — refactor a module, fix a failing test suite, or implement a small feature from a ticket — and the agent will explore the codebase, edit multiple files, run commands/tests, and open a PR. It works in the places I already live (terminal, IDE, Slack), so there’s no forced switch to a new interface. Model routing is useful too; I can lean on stronger models for harder reasoning and cheaper ones for routine work without changing how I interact with the agent. For mid-sized, well-scoped engineering work it feels closer to pairing with a junior developer who can actually push code than using a pure autocomplete tool.

It sits directly inside the helpdesk we already use. We didn’t have to migrate tools or retrain the team on a new interface. The whole deployment felt additive rather than disruptive, which made adoption much smoother than other AI tools we evaluated.