Swytchcode

Agno

High-performance multimodal AI agent framework with native memory and speed

Agno (formerly Phidata) is a lightweight, ultra-fast Python framework engineered for building production-grade autonomous multi-agent systems with native memory, knowledge retrieval, and multimodal reasoning capabilities. It is designed to replace bloated agent frameworks with a pure, pythonic developer experience. Agno agents operate up to 10x faster than legacy orchestration libraries by eliminating unnecessary abstractions. With built-in support for vector databases (PgVector, Qdrant, Pinecone), structured output schemas, and agent-to-agent delegating protocols, developers can build complex autonomous assistants with under 20 lines of clean code.

Smolagents

Lightweight, code-first multi-agent framework by Hugging Face

Smolagents is an ultra-lightweight, code-first Python framework created by Hugging Face for building, orchestrating, and executing autonomous AI agents in minimal lines of code. Rejecting the bloated, multi-layered abstractions of legacy agent libraries, Smolagents emphasizes 'Code Agents'—agents that express their reasoning and tool actions directly in executable Python code rather than rigid JSON string payloads. By letting LLMs write executable Python logic, Smolagents achieves vastly superior composability for data manipulation, mathematical operations, and complex loops while cutting prompt token overhead by up to 30%.

Anthropic Console

Enterprise-grade AI for developers

The developer gateway to Claude models, offering advanced controls like prompt caching and Artifacts rendering via API.

Langfuse

Open source LLM observability, tracing, and evaluation platform

Langfuse is an open-source LLM engineering and observability platform built for teams developing production-grade generative AI applications and autonomous multi-agent pipelines. It captures granular traces across token usage, prompt versions, latency bottlenecks, and retrieval accuracy, giving developers complete visibility into model behavior at runtime. By integrating seamlessly with major AI frameworks such as LangChain, LlamaIndex, LiteLLM, and the OpenAI SDK, Langfuse eliminates the guesswork from debugging complex agent execution trees. Developers can monitor production cost metrics, identify hallucinated responses, and run rigorous continuous evaluation suites on live traffic.

Shadow AI

On-device AI workspace that sees, hears, and executes actions

Shadow is an intelligent, privacy-first desktop AI assistant for macOS engineered to seamlessly observe your workflow, capture meeting context, and execute action items without intruding as an awkward meeting bot. Instead of inviting a bot to your Zoom or Google Meet calls, Shadow records audio and visual context locally from system hardware. By combining low-latency on-device speech transcription with multimodal screen intelligence, Shadow turns unstructured work conversations into clean summary memos, follow-up email drafts, Jira tickets, and calendar invites with a single click.

Relevance AI

Build and deploy custom AI agents and workflows

Relevance AI is a platform designed to create AI workforces by combining LLM agents, tasks, and data pipelines. It provides an intuitive low-code workspace to build autonomous agents that execute multi-step operations.