Demos often showcase coding agents generating pull requests quickly, but fail to address post-commit issues like CI/CD failures. These failures often stem from lack of platform context, leading to rework instead of accelerating delivery. Integrating coding agents with platforms like GitLab, which provides issue, pipeline, and security policy context, helps avoid failures. GitLab tutorials demonstrate how increasing an agent's context improves code quality, security, and review cycles. Agents benefit from repository, issue, and merge request context to align with team standards and plan.When agents work inside merge requests, review cycles shorten and time to merge improves. Platform teams define agent access and verification processes, making the platform, not the agent, the key to safe code delivery. As agents produce more code, security becomes more crucial, shifting the bottleneck from vulnerability discovery to fix approval. Agents with context can prioritize vulnerabilities by real exposure. Custom instructions in AGENTS.md files improve agent output quality by standardizing project structure and expectations. The structured and relevant context delivered by platforms like GitLab outperforms raw data dumps due to context window limitations. Agents accelerate revision by addressing review feedback in merge requests while maintaining existing controls. To start with agentic coding, fix a real bug, document with AGENTS.md, and focus on efficient context delivery.