Software development's difficulty lies not in knowing what to do, but in replicating complex multi-step processes consistently. Currently, chat-based solutions and homegrown scripts fall short by requiring manual intervention at each step and failing to update with system changes. This leaves crucial team workflows stuck as uncodable runbooks. GitLab 19.2 introduces Custom Flows into general availability, offering AI-powered workflows definable once and triggered by native GitLab events. These flows can automate entire sequences, such as self-healing pipelines, reducing manual handoffs. Additionally, Foundational Flows in GitLab Duo Agentic Chat can now be initiated by requests matching specialist work, like implementing an issue or fixing a pipeline. Users approve the recommended flow and can track its progress directly within the conversation. This moves beyond single-turn chat, allowing teams to automate trusted sequences triggered by events or chat while retaining human approval at key stages. Custom flows are now production-ready, enabling automation of tasks like self-healing pipelines and event-driven follow-ups. They can be triggered by various GitLab events and run with composite identity for security and attribution. Users can start specialist work directly from chat, approving handoffs and observing progress inline. Code review automation is also enhanced with exclusion rules and custom instructions to tailor review processes. Custom flows can be created from a project or the AI Catalog, with triggers for GitLab events and human-in-the-loop checkpoints. Foundational Flows in Agentic Chat now route requests to the right specialist flow after user approval. Teams can start encoding their trusted paths with Custom Flows, translating tribal knowledge into predictable automation beyond single-turn chat.