AI Briefing[AWS Summit Seoul 2026] A New Development Methodology for the Generative AI Era: AI-DLC (AI-Driven Development Lifecycle)
Key point
To overcome the limitations of existing AI tools, the AI-DLC methodology has emerged, systematically defining the roles of AI and humans.
Details
Recently, AI development tools have evolved beyond code auto-completion into a multi-agent era, but in the field, a productivity paradox is being observed. This is because AI usage is confined to the coding domain, failing to increase productivity across the entire SDLC (Software Development Lifecycle).
Individual AI tool usage causes context disconnection (silo phenomenon) between teams and variance in output quality, which leads to increased maintenance costs. The existing AI-Managed approach has reliability issues, and the AI-Assisted approach has the limitation of not fundamentally solving the burden of human intellectual labor.
As an alternative to solve this, AI-DLC (AI-Driven Development Lifecycle) has been proposed. This is an AI-native development methodology that clearly separates the roles of AI and humans to build an organic workflow.
- AI's Role: Document generation, code writing, proposing various alternatives, and coordination
- Human's Role: Review, judgment, final decision-making, and responsibility based on business context
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