Term tag: AI Agents

Agent Communication Protocol (ACP)

ACP is the horizontal link between AI agents, where MCP is the vertical link to tools. IBM's REST spec, merged into A2A in August 2025.

Agent Memory

Agent memory is how an AI agent stores, retrieves, and summarizes information so it works across long tasks and sessions without overflowing its context window.

Agent2Agent Protocol (A2A)

An open standard, governed by the Linux Foundation, that lets independent AI agents discover each other and delegate tasks across vendors and frameworks.

Agentic Commerce

Buying where an AI agent handles discovery, comparison and checkout. Two rival protocols split the market: ACP behind ChatGPT, UCP behind Google.

Agentic Workflow

An agentic workflow is a design pattern where an LLM plans, uses tools, and iterates in a loop to solve a task, instead of answering in a single shot.

AI Agent

An AI agent is an LLM-powered system that plans, calls tools, and acts autonomously in a loop to finish multi-step tasks — not just answer questions.

AI Architecture

How a production AI system is assembled: retrieval, context assembly, the model call, tool execution, validation, logging and evaluation.

API

An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate and share data seamlessly.

Computer Use (GUI Agents)

How AI operates software by reading screenshots and issuing clicks and keystrokes: the perception-action loop, why grounding is hard, and what OSWorld measures.

Context Engineering

Deciding what enters a model's context window each turn and what gets evicted — the discipline that took over from prompt engineering once agents arrived.

Error Handling in AI Systems

Ordinary code fails by raising an exception. A model fails by returning a confident, well-formed, wrong answer that nothing catches. What to do about it.

Function Calling (Tool Calling)

The model never runs your function. It emits a structured request; your code decides whether to honour it, executes it, and hands the result back.

Guardrails

A guardrail is a deterministic check around a model that can block, rewrite, or force a retry — external code you can test, unlike prompting a model to behave.

llms.txt

A proposed Markdown file at /llms.txt that gives AI systems a clean map of a site. Google ignores it; coding agents and doc tools use it heavily.

Model Context Protocol (MCP)

An open standard that connects any AI app to any tool over one JSON-RPC interface, turning M clients x N tools from M x N custom connectors into M +…

Multi-Agent Systems (MAS)

A multi-agent system coordinates two or more AI agents, each with its own role and tools, to solve tasks a single agent would handle worse or not at all.

Policy

In reinforcement learning, a policy is the function that maps a state to an action — it is the agent's behavior, the thing training optimizes.

Prompt Injection

Prompt injection is when text an AI was meant to read gets obeyed as an instruction. Direct vs indirect, why it is unfixable, and what actually contains it.

Reinforcement Learning (RL)

How an agent learns to act by trial and error: it takes actions in an environment, earns rewards or penalties, and adjusts to maximize long-term reward.