Awesome GitHub RepositoriesProblem Solving Methodologies

BMAD-METHOD is a multi-agent orchestration framework designed to automate the entire software development lifecycle. It functions as a programmable engine that coordinates autonomous agents to handle complex tasks, ranging from initial requirement elicitation and project planning to code generation and system maintenance. By embedding architectural constraints into a central context file, the system ensures that all automated actions remain aligned with project goals and organizational standards. The platform distinguishes itself through an adversarial review process, where a dual-agent syste

PUA is an agentic workflow orchestrator and behavioral governance tool designed to enhance the reliability and autonomy of AI coding assistants. It functions as a prompting framework and extension that implements strict engineering standards and verification requirements to prevent hallucinations and premature task completion. The project distinguishes itself through high-agency enforcement mechanisms, including escalating prompt pressure and failure-driven recovery loops that automatically pivot problem-solving strategies after repeated errors. It utilizes a diagnosis-first workflow that man

HowToBeAProgrammer is a comprehensive software engineering career guide and professional development framework. It serves as a curated-knowledge repository and handbook designed to help programmers acquire technical habits and social competencies necessary for professional advancement. The project distinguishes itself by integrating technical craftsmanship with a detailed manual for technical leadership and organizational navigation. It provides specific strategies for career progression, such as compensation negotiation, promotion readiness, and the management of professional boundaries to p

This project is a research-oriented repository that serves as a centralized database for system-level prompts and internal behavioral instructions extracted from various large language models. Its primary purpose is to provide a transparent, accessible reference for researchers and developers to study how artificial intelligence models are configured, constrained, and governed. The repository distinguishes itself by cataloging the hidden directives and operational guidelines that define model personas and safety boundaries. By archiving these instruction sets, it enables comparative analysis