This research introduces SDLC-Agent, a novel approach that harnesses community knowledge to improve structured reasoning in code generation tasks.

• Creates high-quality reasoning datasets from Stack Overflow discussions
• Develops specialized agents for different software development phases
• Demonstrates superior performance over existing methods without requiring reinforcement learning
• Provides a scalable framework for improving LLMs' multi-step logical reasoning

For engineering teams, this approach offers a pathway to more reliable automated coding assistants that can handle complex tasks requiring step-by-step reasoning, potentially accelerating development cycles and reducing errors.

Think Like Human Developers: Harnessing Community Knowledge for Structured Code Reasoning