11 posts
Enabling multi-agent conversations with code execution and human-in-the-loop — Microsoft's AutoGen framework for production-grade orchestration.
Orchestrating role-based AI agents for complex workflows with local model support — the most popular multi-agent framework with 12.7M monthly downloads.
Running thousands of agents on a single core via the virtual actor model — transparent distribution across machines for scale-out orchestration.
Google's open-source distributed agent runtime — designed for scalable, distributed agent execution across cloud and edge environments.
LangChain's framework for building stateful, multi-actor agent applications — supporting cycles, branching, and persistent state in agent workflows.
Microsoft's unified agent framework that succeeds both Semantic Kernel and AutoGen — with dedicated migration guides, 160+ contributors, and GA release v1.0.0.
A TypeScript-native multi-agent framework that decomposes goals into runtime task DAGs — runs fully offline on quantized models via Ollama with just 4-8GB VRAM.
An infrastructure-as-code orchestration runtime for multi-agent AI systems — treating agents as YAML resources with manifests, routing, and lifecycle.
A Pydantic-powered agent framework leveraging Pydantic's validation and schema capabilities for type-safe, structured AI agent outputs.
Microsoft's lightweight SDK for integrating AI into applications — with plugins, planners, and memory for building intelligent apps.
Combining project management with AI agents for automated task assignment and workflow orchestration — an AI-native task management platform.