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Implement secure software development lifecycle practices

Setup and integrate security into DevOps pipelines

Integrate security testing and checks into CI/CD pipelines for automated security feedback

Comprehensive security training for development teams

Establish secure code review processes and practices for development teams

Secure dependencies, SBOM, provenance, signing, and build integrity across the software supply chain

Harden infrastructure-as-code and container build pipelines with policy-as-code and image security controls

Validate AI-generated code and secure AI-assisted development workflows with expert-led, AI-augmented review

Define policies and guardrails for safe use of AI coding tools across engineering teams

Design and build secure LLM, RAG, and AI systems from the start with AI-specific engineering controls

Secure autonomous AI agents, tool-calling, and MCP integrations with permission models and action approval workflows

Embed and scale secure engineering practices inside development teams through a structured security champions program

Dedicated secure engineering pod delivering ongoing SDLC, DevSecOps, supply-chain, and AI-native development security on a managed program basis