// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Agentic AI
Refers to AI systems designed to act autonomously, make decisions, and pursue goals in dynamic environments, often by interacting with tools or other systems.
TECHNICAL DEFINITION
Agentic AI describes artificial intelligence systems that exhibit autonomous behavior, goal-directed reasoning, and the ability to interact with their environment, tools, or other agents to achieve complex objectives, often employing planning, memory, and self-reflection mechanisms.
BACKGROUND
Prompt engineering is the process of structuring natural language inputs to produce specified outputs from a generative artificial intelligence (GenAI) model. Context engineering is the related area of software engineering that focuses on the management of non-prompt contexts supplied to the GenAI model, such as metadata, API tools, and tokens.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- AI agents
- Autonomous AI
- Goal-oriented AI
- Intelligent agents
USAGE NOTE
Agentic AI is a key concept in developing more sophisticated and independent AI applications.
DEVELOPERS
Organizations developing technology related to Agentic AI.
Developer of 'Devin', the world's first AI software engineer, an agentic AI system capable of autonomously planning and executing complex software engineering tasks.
Focused on building a 'universal AI assistant' that can collaborate with humans and operate any software tool or API, a direct application of agentic AI principles.
Creator of foundational large language models (LLMs) like GPT-4, which provide the core reasoning and generation capabilities for sophisticated agentic systems, often augmented with tools and function calling.
A leading AI research lab advancing the state of the art in areas like reinforcement learning, multi-agent systems, and planning, all critical for developing autonomous agentic AI.
Driving innovation in agentic AI through initiatives like Microsoft Copilot, which embeds AI agents into various productivity tools, and research into autonomous systems.
Develops large language models such as Claude, with a strong emphasis on steerability, safety, and Constitutional AI, providing robust and reliable foundations for agentic systems.
An open-source framework designed to simplify the creation of applications powered by large language models, including autonomous agents that can reason, observe, and act.
An open-source data framework that enables LLM applications to ingest, index, and query private or domain-specific data, crucial for building agents with enhanced knowledge and reasoning capabilities (RAG).