The industry is struggling with managing source code for AI agents, as traditional Git backends are not designed for their scale. Agents face issues like the "clone tax," where they download entire repositories for small tasks, leading to massive data transfer and slow setup times. They also cause concurrency collapse due to thousands of sessions overwhelming systems built for human users. Furthermore, a lack of isolation means agents share accounts and branches, making it difficult to track actions or discard abandoned work. GitLab is addressing these problems with its next-generation source code management (next-gen SCM). This new system maintains Git compatibility but features a redesigned backend and interfaces optimized for agents. Agents can now query the repository server-side for specific data, avoiding full clones and significantly reducing network traffic and processing time. The architecture separates intelligence and compute layers, allowing for on-demand scaling and elastic object storage. Purpose-built APIs enable agents to fetch data and commit changes efficiently, supporting thousands of concurrent experiments. This solution is designed to work both in the cloud and on-premise, catering to various infrastructure needs, including air-gapped environments. Internal testing shows dramatic improvements, with up to 50x faster execution and 1,000x less network traffic. Beyond just a faster Git backend, next-gen SCM integrates provenance and full lifecycle management of agent actions. This ensures auditability and adherence to policies, seamlessly incorporating agent work into existing governed production pipelines.