4 Repos
Structured systems that guide LLMs through the software development lifecycle from requirements to execution.
Distinct from LLM Development Frameworks: Existing candidates are either too generic (general LLM frameworks) or focused on deployment rather than the development lifecycle orchestration.
Explore 4 awesome GitHub repositories matching artificial intelligence & ml · AI Software Development Frameworks. Refine with filters or upvote what's useful.
This project is an AI agent workflow orchestrator and software development framework designed to transform high-level feature descriptions into executable implementation steps for AI assistants. It provides a structured system of prompt templates that guides large language models through the transition from product drafting to technical planning and code execution. The framework focuses on a methodology for decomposing product blueprints into sequenced lists of technical sub-tasks. It employs a system of prompt engineering to standardize outputs, ensuring that abstract requirements are conver
Provides a structured framework of prompt templates for guiding LLMs from requirements to technical task execution.
Vibe-coding is an agentic workflow manager and AI coding orchestrator designed to guide autonomous agents through software development. It serves as a development framework that organizes the process of building software using large language models through structured planning, iterative validation, and a defined cycle of implementation. The project distinguishes itself through a focused context management system and project memory bank, which uses dedicated files to maintain consistent architectural context across sessions. It employs constraint-based guidance to enforce project-specific codi
Offers a structured system that guides LLMs through the entire software development lifecycle from requirements to execution.
Agent-OS is an LLM multi-agent orchestration framework and AI software development lifecycle tool designed to coordinate specialized agents through shared workspaces and structured task lists. It functions as an agentic application bootstrapper and technical specification engine, providing the infrastructure to guide the process from product requirements to automated coding and deployment. The system distinguishes itself through spec-driven development, using detailed technical specifications and layered context injection to ensure generated code aligns with project standards. It employs a ma
Guides the full development process from requirements and technical specifications to iterative coding, debugging, and deployment.
This project is an agentic development framework and autonomous software engineering system. It utilizes a coordinated network of specialized LLM agents to automate the full software development lifecycle, from codebase exploration and architectural planning to implementation and automated refactoring. The system is distinguished by an agentic memory system and a test-driven development orchestrator. It maintains project continuity across sessions by capturing architectural learnings and state in a persistent semantic database and enforces code quality through an automated cycle of generating
Coordinates specialized AI agents to automate the full software development lifecycle from requirements to execution.