Security scans generate hundreds of findings. Security teams manually triage each one while developers wait for approval to deploy. Most findings are false positives or low-risk issues, but identifying the real threats requires expertise and time. AI can prioritize findings by actual exploitability and auto-remediate common vulnerabilities, allowing security teams to focus on the threats that matter.
10 AI prompts to speed your team’s software delivery… But when development teams use coding agents with GitLab, the agents draw on the issues, pipelines, and security policies already in the platform, catching problems and remediating them within the developer flow. …
… Review code for security issues Complexity : Intermediate Category : Security Agent : Duo Security Analyst Prompt from library : @security analyst Review this code for security issues: PASTE CODE Check for: 1. …
… The agentic AI ecosystem AI-driven code analysis: The new frontier in code security DevOps automation & AI agents AI-augmented software development: Agentic AI for DevOps Best practices for implementing agentic AI Implementing effective guardrails for AI agents — Discover essential security guardra… …
… Here's what we announced and demonstrated: Next-generation source code management , a Git engine rebuilt for agent-scale concurrency, now in private beta GitLab Orbit , our context graph for the full software lifecycle, now in public beta Agents for security and governance for agents , identity, po… …
… It analyzes logs and changes to pinpoint errors, and could even explain security issues or predict bottlenecks. …
… The Tanuki IoT Platform uses a root-level file, and specific sub-directory files and instructions for sensors and the backend. tree -P AGENTS.md --prune . ├── AGENTS.md ├── backend │ └── rust-metrics-store │ └── AGENTS.md └── sensors ├── arduino-iot-collector │ └── AGENTS.md ├── c-file-monitor │ └─… …
… Orbit builds on data GitLab already captures: issues, merge requests, pipelines, code, security findings, deployments, and incidents. You get value from day one with no new instrumentation. Agents on GitLab Duo Agent Platform query the graph natively. …
… What's emerging now is different: agents that participate across the work, not for a fixed moment. …
… Creating the custom agent Next, we create a new blank project called application-agents . This project will manage our custom agents, including who can administer them and where they can run. Follow these steps: From AI Agents , we select the Managed tab. …
… By integrating AI-powered assistance throughout the development lifecycle, it helps increase productivity, improve code quality, and enhance security. Developers can write code faster, understand complex codebases more easily, and catch potential issues earlier in the development process. …