How to incorporate AI into the SDLC

Incorporating AI into the Software Development Life Cycle (SDLC) involves using AI tools across various phases such as planning, development, testing, review, deployment, and operations. AI tools can be classified based on their level of involvement: assistive tools, which suggest and require human execution, and agentic tools, which can autonomously plan and execute tasks. This integration requires different infrastructures depending on the AI's involvement level, with assistive tools needing less infrastructure change while agentic tools require isolated execution and controlled release paths. Northflank provides the necessary infrastructure to support AI involvement in the SDLC by offering microVM-backed sandboxes, Git-based builds, preview environments, and RBAC, which ensure secure and efficient execution of AI-generated code. AI tools enhance productivity and efficiency across all phases of the SDLC by aiding in tasks like code generation, test creation, and incident summarization, while maintaining the need for human oversight, particularly in high-risk execution phases.

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