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9 repository-uri

Awesome GitHub RepositoriesAI Software Engineering

Automation of the complete software development lifecycle using AI agents.

Distinct from AI Software Engineering: Candidates are either benchmarking sets or general lists, not the actual capability of end-to-end engineering automation.

Explore 9 awesome GitHub repositories matching artificial intelligence & ml · AI Software Engineering. Refine with filters or upvote what's useful.

Awesome AI Software Engineering GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • openai/symphonyAvatar openai

    openai/symphony

    25,622Vezi pe GitHub↗

    Symphony is an agentic workflow manager and autonomous software implementation engine. It serves as an orchestrator for large language model coding agents, converting high-level project requirements and task board items into verified pull requests. The system manages an autonomous development workflow by delegating implementation runs to agents that handle end-to-end feature development and bug fixes. It generates automated pull requests backed by proof-of-work verification, ensuring that code contributions are validated before human review. The platform coordinates a cycle of planning, codi

    Uses large language models to handle end-to-end feature implementation and bug fixes without constant supervision.

    Elixir
    Vezi pe GitHub↗25,622
  • claude-code-best/claude-codeAvatar claude-code-best

    claude-code-best/claude-code

    20,272Vezi pe GitHub↗

    Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

    Autonomously writes code, debugs issues, and manages Git workflows using LLMs via a command-line interface.

    TypeScript
    Vezi pe GitHub↗20,272
  • smol-ai/developerAvatar smol-ai

    smol-ai/developer

    12,188Vezi pe GitHub↗

    This project is an AI software engineering tool and framework for building autonomous coding agents. It provides a system for automating program synthesis and bug fixing by integrating large language models with codebase analysis and iterative refinement loops. The framework features an agentic development server that exposes task execution interfaces to remote agents through a structured protocol. This allows for the remote execution of development tasks and the embedding of autonomous program synthesis capabilities into external software projects. The toolset covers AI-driven project scaff

    Provides a comprehensive system for automating the software development lifecycle via AI-driven program synthesis and bug fixing.

    Python
    Vezi pe GitHub↗12,188
  • sweepai/sweepAvatar sweepai

    sweepai/sweep

    7,703Vezi pe GitHub↗

    Sweep este un sistem automatizat de inginerie software care utilizează modele de limbaj mari (LLM) pentru a rezolva issue-uri pe GitHub. Acesta funcționează ca un inginer software AI care transformă descrierile issue-urilor din limbaj natural în modificări concrete de cod și pull request-uri. Sistemul se integrează cu webhook-urile GitHub pentru a declanșa fluxuri de lucru bazate pe crearea de issue-uri sau actualizarea etichetelor. Utilizează o buclă de feedback iterativă care analizează erorile de compilare și rezultatele testelor pentru a rafina codul generat și a corecta bug-urile. Instrumentul acoperă o gamă de capabilități de mentenanță, inclusiv remedierea automată a bug-urilor, implementarea de funcționalități și refactorizarea bazei de cod. Încorporează analiză statică și prompting conștient de context pentru a se asigura că respectivul cod generat respectă standardele de tipizare, logare și arhitectură specifice proiectului. Securitatea este gestionată prin reguli de protecție și restricții de acces care împiedică agentul să modifice fișierele sau directoarele protejate.

    Automates the end-to-end software development lifecycle from issue analysis to code application.

    Jupyter Notebook
    Vezi pe GitHub↗7,703
  • agentwrapper/agent-orchestratorAvatar AgentWrapper

    AgentWrapper/agent-orchestrator

    7,637Vezi pe GitHub↗

    This project is an LLM coding agent orchestrator and AI software engineering platform designed to manage fleets of agents that autonomously solve issues, handle pull requests, and fix CI failures. It functions as an agentic CI/CD automator and parallel workflow manager, coordinating the end-to-end development lifecycle from initial ticket tracking to final code merging. The system is distinguished by its modular plugin framework and isolated worktree management, which allow multiple agents to work on separate coding tasks simultaneously without file system conflicts. It utilizes role-based mo

    Automates the end-to-end development lifecycle from issue tracking and coding to review and merging.

    TypeScriptagent-fleetagent-swarmclaude-code
    Vezi pe GitHub↗7,637
  • phodal/auto-devAvatar phodal

    phodal/auto-dev

    4,508Vezi pe GitHub↗

    auto-dev este un instrument de inginerie software AI-native și o platformă de dezvoltare multi-agent concepută pentru a automatiza întregul ciclu de viață al dezvoltării software. Funcționează ca un orchestrator autonom care gestionează codarea, testarea și configurarea infrastructurii bazate pe AI prin lanțuri de agenți declarativi. Proiectul este construit pe un framework AI Kotlin Multiplatform, permițând logicii agenților să ruleze în medii diverse și interfețe de dispozitive. Platforma implementează Model Context Protocol pentru a schimba instrumente și informații despre proiect cu servicii AI externe. Se distinge prin utilizarea unui pipeline de retrieval-augmented generation și grafuri de cod bazate pe arbori, care analizează arborii de sintaxă abstractă și lanțurile de apeluri pentru a comprima contextul proiectului și a reduce halucinațiile. O pânză de dezvoltare interactivă oferă sincronizarea în timp real a diagramelor UML, specificațiilor OpenAPI și diff-urilor de cod. Domeniile de capabilități acoperă dezvoltarea software autonomă, inclusiv planificarea dinamică a sarcinilor, repararea iterativă bazată pe teste și migrarea codului legacy. Sistemul gestionează, de asemenea, automatizarea infrastructurii ca cod pentru Docker și configurații CI/CD, revizuiri de cod bazate pe AI și coordonarea persoanelor AI partajate și a specificațiilor de prompt între echipe. Logica de bază este implementată folosind Kotlin Multiplatform pentru a asigura o implementare consistentă a agenților cross-platform.

    Automates the complete software engineering lifecycle including code generation and legacy system refactoring.

    Kotlinaigcgenaigenaistack
    Vezi pe GitHub↗4,508
  • zai-org/glm-4.5Avatar zai-org

    zai-org/GLM-4.5

    4,210Vezi pe GitHub↗

    GLM-4.5 is a multimodal large language model and advanced reasoning system. It functions as an AI coding assistant, an autonomous AI agent, and a multimodal content generator capable of processing and generating text, images, audio, and video within a single unified system. The project is distinguished by its deep reasoning capabilities, utilizing chain-of-thought processing to solve complex mathematical, logical, and technical problems. It features an agentic architecture that allows for autonomous task execution, long-horizon goal planning, and the ability to interact with external tools an

    Automates the full development lifecycle from requirement analysis and code generation to debugging and performance optimization.

    Pythonagentglmllm
    Vezi pe GitHub↗4,210
  • neomjs/neoAvatar neomjs

    neomjs/neo

    3,137Vezi pe GitHub↗

    Neo is an autonomous engineering platform and multi-agent orchestration framework designed to build, review, and maintain production codebases. It coordinates a swarm of multiple language models through a messaging and event system to automate complex software development workflows without manual intervention. The platform utilizes a semantic knowledge graph manager to distill session logs and documentation into a queryable topology, preserving project history and context across AI interactions. It supports multi-tenant deployment of agent swarms that employ persistent memory and structured m

    Launches multi-tenant swarms of models that autonomously build and maintain codebases using persistent memory.

    JavaScriptai-agentsapplication-enginearchitecture
    Vezi pe GitHub↗3,137
  • datawhalechina/vibe-vibeAvatar datawhalechina

    datawhalechina/vibe-vibe

    3,126Vezi pe GitHub↗

    vibe-vibe is an LLM agent engineering framework and toolchain optimizer designed for orchestrating multi-agent systems. It serves as a comprehensive guide and methodology for transforming conceptual ideas into deployed applications through agentic software engineering. The project focuses on the orchestration of specialized AI agent roles with defined collaboration boundaries and iterative feedback loops. It provides frameworks for toolchain optimization, including the selection and evaluation of protocols that extend model capabilities and the design of standardized tool interfaces. The sys

    Provides analysis on how AI reshapes engineering roles and identifies high-leverage future skills for developers.

    agentagentic-aiai
    Vezi pe GitHub↗3,126
  1. Home
  2. Artificial Intelligence & ML
  3. AI Software Engineering

Explorează sub-etichetele

  • Engineering Role AnalysisEvaluations of how AI transforms software engineering roles and delivery models. **Distinct from AI Software Engineering:** Distinct from AI Software Engineering as it focuses on the strategic analysis of industry trends and skill shifts rather than the automation of the development lifecycle.
  • Multi-Tenant DeploymentsIsolated deployment of autonomous engineering teams for multiple distinct tenants or projects. **Distinct from AI Software Engineering:** Focuses on the multi-tenant orchestration of agent swarms rather than a general AI software engineering lifecycle.