Devin

Devin Desktop is a unified desktop application designed for developers and engineering teams who need to orchestrate multiple autonomous AI agents across both local and cloud environments. At its core, the tool provides a single surface where users can create, monitor, and manage fleets of software agents that perform complex development tasks—from code refactoring and model training to pull request reviews and deployment coordination. The application is built around a session-based workflow: each agent operates inside a dedicated session, which records the entire history of actions, outputs, and decisions. Users can inspect the real‑time status of every agent, see whether it is currently working, waiting for conditions, or has completed a task. The interface includes a board and list view for sessions, allowing teams to visualize the progress of multiple parallel workflows, filter by status (e.g., “Working”, “PR is ready”, “Waiting for CI”), and drill into the details of each step. One of the key features is the ability to delegate tasks to agents without leaving the editor environment. For example, a developer can ask an agent to “widen the model hidden dimension” or “switch the MLP activation to GELU” for a machine learning project. The agent will then execute the change, run the necessary experiments, and return the results. Another agent might be tasked with tuning hyperparameters—like increasing the Muon matrix learning rate or adding a learning rate warmup phase—and automatically generate a pull request once the change is ready. The agent can also trigger CI pipelines and wait for the outcome, providing a seamless feedback loop. The platform supports multiple types of agents: some are focused on code editing and refactoring, others on infrastructure management (e