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the runtime your coding agents live on
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
AI coworker with memory and collaboration
Trigger.dev – build and deploy durable AI agents and workflows
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
⛓️RuleGo is a lightweight, high-performance, embedded, next-generation component orchestration rule engine framework for Go.
a fast, GPU-accelerated, full-featured IDE and terminal multiplexer, suitable both for automatic and manual programming.
The .NET library to build AI agents with 30+ built-in connectors.
The ai agent workflow tool that scales from small, simple projects to large, complex codebases.
Let AI agents message, watch, and spawn each other across terminals. Claude Code, Codex, Antigravity CLI, Cursor CLI, OpenCode, Kilo, Pi, Kimi
Autonomous desktop intelligence with MCU Ultron persona, mood-aware workspace orchestration, cyber security sentry, and full PC control.