OpenAGI
OpenAGI is a developer-focused framework designed to help teams build autonomous, human-like AI agents capable of planning, reasoning, and executing tasks independently. It bridges the gap between traditional LLM applications and fully autonomous agents by offering tools for decision-making, continual learning, and long-term task execution. The platform allows developers to create specialized agents for real-world use cases across industries such as education, finance, healthcare, and software development. With its flexible architecture, OpenAGI supports sequential, parallel, and dynamic communication patterns between agents. Developers can choose automated configuration generation or manually tailor every detail for complete customization. OpenAGI represents an early but significant step toward making powerful, adaptive agent technology accessible to everyone.
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Lux
Lux is a powerful computer-use AI platform that enables agents to operate software just like a human user—clicking, typing, navigating, and completing tasks across any interface. It offers three execution modes—Tasker, Actor, and Thinker—giving developers the ability to choose between step-by-step precision, near-instant task execution, or long-form reasoning for complex workflows. Lux can autonomously perform actions such as crawling Amazon data, running automated QA tests, or extracting insights from Nasdaq’s insider activity pages. The platform makes it possible to prototype and deploy real computer-use agents in as little as 20 minutes using developer-friendly SDKs and templates. Its agents are built to understand vague goals, execute long-running operations, and interact naturally with human-facing software instead of relying solely on APIs. Lux represents a new paradigm where AI goes beyond reasoning and content generation to directly operate computers at scale.
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Agent Builder
Agent Builder is part of OpenAI’s tooling for constructing agentic applications, systems that use large language models to perform multi-step tasks autonomously, with governance, tool integration, memory, orchestration, and observability baked in. The platform offers a composable set of primitives—models, tools, memory/state, guardrails, and workflow orchestration- that developers assemble into agents capable of deciding when to call a tool, when to act, and when to halt and hand off control. OpenAI provides a new Responses API that combines chat capabilities with built-in tool use, along with an Agents SDK (Python, JS/TS) that abstracts the control loop, supports guardrail enforcement (validations on inputs/outputs), handoffs between agents, session management, and tracing of agent executions. Agents can be augmented with built-in tools like web search, file search, or computer use, or custom function-calling tools.
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Swarm
Swarm is an experimental, educational framework developed by OpenAI to explore ergonomic, lightweight multi-agent orchestration. It is designed to be scalable and highly customizable, making it suitable for scenarios involving a large number of independent capabilities and instructions that are challenging to encode into a single prompt. Swarm operates entirely on the client side and, like the Chat Completions API it utilizes, does not store state between calls. This stateless nature allows for the construction of scalable, real-world solutions without a steep learning curve. Swarm agents are distinct from assistants in the assistants API; they are named similarly for convenience but are otherwise completely unrelated. It includes examples demonstrating fundamentals such as setup, function calling, handoffs, and context variables, as well as more complex scenarios like a multi-agent setup for handling different customer service requests in an airline context.
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