The Agentic OS for Software Engineering

AutomatedEv positions itself as an agentic operating system for software engineering, aiming to handle the entire lifecycle from idea intake to merged pull requests. The platform emphasizes a deterministic control plane where code execution remains within the user's own network, ensuring that proprietary data does not exit the organization's walls. It supports a variety of AI providers, including Claude Code, Copilot, and Codex, while allowing users to bring their own API keys for greater flexibility. Key features include a self-repairing loop that automatically retries build and test failures, isolated sandboxes for each run to prevent collisions, and integrated security scanning. The system integrates with existing tools like GitHub, GitLab, Postgres, and Docker, suggesting a seamless fit into current engineering stacks. It offers a console for monitoring autonomous runs, with human gates for approval and detailed observability of agent actions. The platform also maintains shared knowledge and memory across the team to preserve context, aiming to reduce the cognitive load on engineers by automating repetitive tasks while keeping them in control of critical decisions through a live stream of agent activities and easy-to-use gating mechanisms.

Having ideas, defects, implementation, and testing live in one console significantly reduces context switching for the engineering team. The platform’s ability to plug into existing tools like GitHub, GitLab, and Vault allows it to integrate seamlessly into our current stack without requiring a complete overhaul of our infrastructure. The shared memory feature, which remembers decisions and keeps a living map of the codebase, appears to solve the common problem of agents losing context between sessions. While the interface looks robust, one should verify that the real-time event streaming and command palette perform consistently under high-load scenarios before committing to a full deployment, as the latency could impact the human-in-the-loop gating process.

The ability to run the entire agentic OS within your own walls is a decisive feature for security-conscious engineering teams. Knowing that zero data exits the network while maintaining deterministic control over the planning and building phases provides the necessary confidence to automate complex workflows. The live pipeline demonstration confirms that the system is functional, not just conceptual, offering a reliable path from idea to merged pull request with full observability at every stage.

The platform looks incredible and the self-hosted model is fantastic, yet the pricing structure remains delightfully mysterious for enterprise buyers seeking clarity.

The Agentic OS presents a compelling architecture for software engineering teams seeking automation without sacrificing control. The distinction between a copilot and a full platform is well-articulated, particularly the emphasis on a deterministic control plane where logic lives in code rather than fragile prompt chains. The self-hosted option is a significant advantage, ensuring that proprietary code never leaves the network, which addresses major data sovereignty concerns for enterprise clients. The six-phase loop—from intake to shipping a PR—seems comprehensive, covering planning, building, verifying, and securing. However, while the feature set is impressive, the specific integration capabilities with existing third-party tools beyond the listed GitHub, GitLab, and Vault connections are not fully detailed. For teams with highly customized workflows, the ability to extend the platform beyond the standard skills hub remains somewhat unclear. Nevertheless, the core promise of closing the loop autonomously while keeping humans in the gate is technically sound and visually demonstrated effectively.