Agentic AI
Agentic AI is a general term for AI systems that interpret goals and autonomously repeat the cycle of planning, executing, and verifying actions without requiring step-by-step human instruction.
Asking a chatbot a question and receiving an answer — this was the core of AI utilization in 2023–2024. Agentic AI lies beyond that. Rather than answering questions, it completes tasks. Karpathy coined this shift "Agentic Engineering" in early 2026. At its core is a workflow called the PEV loop — a cycle that AI itself runs through Plan → Execute → Verify. In coding, for example, an agent first analyzes the task and formulates an execution plan, writes the code, runs tests to verify the results, and makes corrections if problems arise. Humans provide approval and course corrections at checkpoints along the way. Looking at real numbers: at Stripe, an internal agent called "Minions" is merging over 1,000 pull requests per week. Zapier reported that 89% of the entire organization has integrated AI into their work. This is no longer an experimental phase. The infrastructure supporting Agentic AI is also being developed. MCP for tool connectivity, A2A for inter-agent communication, and Agent Skills as the unit of task execution capability — these are combining to enable the automation of complex workflows that were impossible with standalone AI models.
Related Terms
A2A (Agent-to-Agent Protocol)
A2A (Agent-to-Agent Protocol) is a communication protocol that enables different AI agents to perform capability discovery, task delegation, and state synchronization, published by Google in April 2025.
Agent Skills
Agent Skills are reusable instruction sets defined to enable AI agents to perform specific tasks or areas of expertise, functioning as modular units that extend the capabilities of an agent.
Ambient AI
Ambient AI refers to an AI system that is seamlessly embedded in the user's environment, continuously monitoring sensor data and events to proactively take action without requiring explicit instructions.
