October 2026 Summaries

Factory’s Droid and Cognition’s Devin are compared as enterprise coding agents that support both interactive engineer-guided work and delegated tasks, using a dependency migration example to emphasize the importance of preserving compatibility, updating tests, and producing reviewable handoffs. Droid is available through Factory’s App, CLI, editor integrations, Missions, persistent Droid Computers, and non-interactive Droid Exec for CI, while Devin offers managed sessions, CLI, Desktop, parallel workflows, and reusable guidance through Skills in Plugins after deprecating Knowledge. The comparison argues that teams should assess how each product handles reviewer corrections, test failures, task coordination, persistent instructions or environments, permissions, model configuration, and reproducibility rather than relying on polished interfaces or completion claims. It recommends evaluating equivalent tasks in isolated repository copies, recording setup effort, model and compute costs, test outcomes, regressions, reviewer effort, and the ability for another engineer to resume work after failure. Different workflows may suit different organizations, so selection should be based on reviewed patches, validated test results, and actual operational requirements.

Factory’s Droid and Cognition’s Devin both offer enterprise coding-agent capabilities, but selecting between them requires evaluating identity, ownership, provisioning, policy enforcement, command permissions, isolation, and audit evidence rather than code-generation quality alone. Factory documents SAML/OIDC, SCIM, organization roles, and service accounts that can own automated jobs independently of departed employees, while Cognition offers custom roles and RBAC that may better support fine-grained application access. Factory emphasizes a hierarchy of hard organization controls and local preferences for model access, custom endpoints, autonomy, MCP tools, and session settings, whereas both platforms require real-world testing of command, file, repository, and tool permissions, including attempted overrides and alternate command formats. Administrative audit logs should be assessed separately from engineering execution records such as code diffs, test results, and reviewer decisions. The recommended evaluation is a controlled pilot using synthetic data and disposable repositories that tests denied actions, offboarding, unattended automation ownership, and evidence retention, with the final decision based on whether a specific product configuration demonstrably meets organizational requirements at an acceptable administrative cost.

Factory’s Droid and Cognition’s Devin are coding agents that can operate on private repositories, but evaluating them requires tracing all copies of engineering data created through local file access, model requests, sessions, telemetry, logs, and support processes rather than relying on deployment labels alone. Factory documents cloud-managed, hybrid, regional, and airgapped options, with its dedicated Airgap Mode removing Factory sign-in, cloud synchronization, telemetry, and managed model access while placing responsibility for internal models, infrastructure, artifacts, Git access, and network isolation on the customer; its private routing capabilities may also vary by build and preview status. Devin offers Enterprise Cloud, customer-dedicated deployments, and airgapped CLI configuration checks, while its enterprise commitments regarding tenant storage, retention, model processing, and support access should be confirmed for the selected configuration. The comparison emphasizes keeping no-training policies, model-provider retention, application-session retention, telemetry exports, and network isolation as separate controls, since each affects different data copies and destinations. Organizations are advised to obtain contractual details on deletion, backups, and access, restrict outbound connections, test representative but non-sensitive repositories and synthetic telemetry, verify both permitted and denied network paths, and select the deployment boundary they can demonstrably operate and audit.