Technology is moving at lightning speed, and with it comes a wave of new terms, acronyms, and buzzwords that can feel overwhelming. From AI breakthroughs to real-time communication tools, the language of modern tech is constantly evolving.
This glossary is designed to cut through the noise. We’ve broken down 20 frequently used terms into clear definitions, simple explanations, and real-world examples. Whether you’re a developer, a business leader, or simply curious about the future of technology, this guide will help you make sense of the words shaping today’s digital world.
Agentic AI (noun)
Definition:
A type of artificial intelligence designed to operate autonomously, making decisions, taking actions, and achieving goals with minimal human intervention. Unlike passive AI that only responds to prompts, agentic AI can plan, adapt, and act proactively.
Um, what?:
Agentic AI is like a smart robot that doesn’t need much help from people to get things done. Imagine a self-driving car that figures out the best route and handles traffic on its own, or a virtual assistant that not only answers your questions but also anticipates what you might need next, like reminding you to take an umbrella when it’s about to rain.
In a sentence:
“CometChat brings agentic AI into conversations, enabling intelligent agents that don’t just respond, but act, connecting knowledge, workflows, and humans in real time.”
AI Agent (noun)
Definition:
An AI agent is a software program that can perceive its environment, understand inputs (like text, voice, or data), make decisions, and take actions to achieve a specific goal. Unlike general AI systems, an AI agent is usually focused on a defined task such as answering customer questions, recommending products, or managing workflows.
Um, what?
Think of an AI agent like a digital team member with a job title. One might be the “FAQ guy” who only answers common questions, another might be the “translator” who jumps in whenever two people speak different languages. Each agent has its own specialty like tiny superheroes in your chat app, swooping in exactly when they’re needed.
In a sentence:
“With CometChat’s AI Agents, a customer support bot can instantly recognize a refund request, provide the right information, or escalate the issue to a human agent if needed.”
Multi-Agent System (noun)
Definition:
A multi-agent system is a setup where multiple AI agents operate together, either by collaborating on a shared goal or by interacting independently within the same environment. Each agent may have its own knowledge, role, and abilities, but when combined, they can tackle complex tasks more effectively than a single agent could.
Um, what?
Imagine your group chat has a whole squad of digital teammates. One’s the bouncer keeping things safe, another’s the translator helping everyone understand each other, and another’s the note-taker summarizing what’s said. That’s a multi-agent system, not just one bot, but a team of bots, each doing their job so the conversation flows smoothly.
In a sentence:
“Using a multi-agent system within CometChat, one bot can moderate harmful language while another provides instant translations, creating a safer and more inclusive chat experience.”
Conversational AI (noun)
Definition:
A branch of artificial intelligence that enables machines to understand, process, and respond to human language in a natural, human-like way. It powers chatbots, virtual assistants, and AI agents that can engage in dialogue, answer questions, and assist with tasks through text or voice.
Um, what?
Conversational AI is like teaching computers how to talk and listen. Imagine chatting with a customer service bot that understands your question and gives a clear answer, or asking Alexa to play music and it just does it. It’s about making interactions with technology feel more like a real conversation.
In a sentence:
“CometChat’s Conversational AI makes it easy for businesses to add natural, human-like interactions to their apps, so users get answers and support instantly without waiting for a human.”
LLM - Large Language Model (noun)
Definition:
Short for Large Language Model, an advanced type of AI trained on massive amounts of text data. LLMs use deep learning to understand context, generate human-like responses, and perform tasks such as answering questions, summarizing information, writing content, or reasoning through problems.
Um, what?
Think of an LLM as a super-smart autocomplete. It has read a huge amount of books, articles, and websites, so when you ask it something, it predicts the most useful answer based on patterns it has learned. It doesn’t “think” like a human, but it’s great at mimicking natural language and solving tasks through conversation.
In a sentence:
“CometChat connects directly with LLMs like OpenAI and Anthropic, letting developers and businesses power their chat experiences with human-like intelligence out of the box.”
Context Window (noun)
Definition:
The maximum amount of information (measured in tokens, or chunks of text) that a large language model (LLM) can “see” and use at once when generating a response. A larger context window allows the model to remember more of the conversation, documents, or instructions during processing.
Um, what?
A context window is like an AI’s short-term memory. If the window is small, it’s like the AI can only remember a few pages of a book at a time. If it’s large, it can recall whole chapters, making its answers more relevant and less repetitive.
In a sentence:
“CometChat optimizes how agents use the LLM’s context window, ensuring conversations stay coherent even when users share long documents or extended chats.”
RAG: Retrieval-Augmented Generation (noun)
Definition:
Short for Retrieval-Augmented Generation, a technique in AI that combines large language models (LLMs) with external knowledge sources. Instead of relying only on what the model was trained on, RAG fetches relevant, up-to-date information from a connected database, API, or document store before generating a response making answers more accurate and grounded.
Um, what?
RAG is like giving an AI a library card. The model can “look up” fresh information before replying, instead of just guessing from memory. For example, if you ask about your company’s latest policy, a RAG-powered agent won’t hallucinate it will search your company docs and then explain it correctly.
In a sentence:
“CometChat’s platform enables RAG so your AI agents can ground conversations in your own knowledge base, delivering accurate, trusted answers every time.”
Vector Database (noun)
Definition:
A specialized database designed to store, index, and search vector embeddings- numerical representations of data such as text, images, or audio. Unlike traditional databases that work with rows and columns, vector databases enable similarity search, helping AI systems quickly find the most relevant information.
Um, what?
Think of a vector database as a giant “memory palace” for AI. Instead of flipping through books page by page, the AI can instantly jump to the most similar piece of information it has stored. For example, if you ask about a policy in your company handbook, the AI doesn’t guess, it looks up the closest match in its vector database and answers accurately.
In a sentence:
“CometChat integrates with vector databases so your AI agents can search and retrieve the right knowledge instantly, grounding conversations in trusted, up-to-date information.”
Embeddings (noun)
Definition:
Numerical representations of data like text, images, or audio encoded into multi-dimensional vectors. Embeddings capture the meaning, context, or similarity of information so that AI systems can compare and retrieve related items efficiently.
Um, what?
Embeddings are like turning words or images into GPS coordinates on a map. Things with similar meanings end up close together. For example, “dog” and “puppy” would be near each other, while “car” would be farther away. This lets AI figure out which pieces of data are most alike.
In a sentence:
“CometChat uses embeddings to let AI agents understand context and match user questions with the most relevant knowledge from your data.”
Real-Time Messaging (noun)
Definition:
A communication method where messages are delivered instantly between users, applications, or systems with minimal delay. It enables live, interactive conversations and powers chat apps, notifications, and collaborative tools.
Um, what?
Real-time messaging is like talking face-to-face, but online. When you send a message, the other person sees it almost immediately—like WhatsApp, Slack, or multiplayer game chats. No waiting, no refresh button.
In a sentence:
“CometChat provides real-time messaging as the foundation, so AI agents and humans can collaborate instantly within the same conversation.”
WebSockets (noun)
Definition:
A communication protocol that enables persistent, two-way connections between a client (like a web browser or app) and a server. Unlike traditional HTTP requests, WebSockets keep the connection open, allowing data to flow back and forth instantly.
Um, what?
WebSockets are like keeping a phone call open instead of sending letters back and forth. Once the line is connected, both sides can talk freely without reintroducing themselves every time making chats, notifications, and live updates feel instant.
In a sentence:
“CometChat uses WebSockets under the hood to power seamless, real-time messaging between users, agents, and apps.”
SDK (noun)
Definition:
Short for Software Development Kit, an SDK is a collection of tools, libraries, documentation, and sample code that helps developers quickly integrate specific functionality like chat, payments, or AI into their apps.
Um, what?
An SDK is like a ready-made toolkit. Instead of building everything from scratch, developers get prebuilt parts they can plug in. Imagine putting together furniture with an instruction manual and all the screws included that’s what an SDK does for software.
In a sentence:
“CometChat’s SDK gives developers everything they need to drop real-time messaging and AI agents into their apps with just a few lines of code.”
Chatbot (noun)
Definition:
A chatbot is a conversational program powered by rules or artificial intelligence that interacts with people through text or voice. Modern chatbots use natural language processing (NLP) and large language models (LLMs) to understand user intent, provide accurate answers, and even complete tasks such as booking tickets or resolving customer issues.
Um, what?
Think of a chatbot as a digital receptionist or support agent that never sleeps. You type or speak to it, and it responds in real time sometimes in simple scripted ways, but increasingly with human-like understanding thanks to AI.
In a sentence:
“CometChat enables companies to launch AI-powered chatbots that handle FAQs, guide customers, and resolve requests instantly without human wait times.”
Prompt Engineering (noun)
Definition:
Prompt engineering is the process of designing and refining the instructions given to large language models (LLMs) to produce more reliable, accurate, and contextually appropriate responses. It involves structuring input text, adding constraints, or giving examples so the AI understands exactly what is expected.
Um, what?
It’s like crafting the perfect question to get the best answer. If you just say, “Tell me about space,” the AI might ramble. But if you ask, “Explain space travel to me like I’m 12, focusing on rockets,” the response is clear, tailored, and useful.
In a sentence:
“CometChat simplifies prompt engineering so developers and business users can control how their AI agents sound, behave, and respond.”
Function Calling (noun)
Definition:
Function calling is a capability in modern AI models where the model can detect when a task requires external action and then invoke a function, API, or tool to complete it. Instead of only producing text, the AI can fetch live data, trigger workflows, or execute commands, making it far more practical in real-world apps.
Um, what?
Imagine asking an AI, “What’s the weather in New York right now?” A basic AI might just guess, but with function calling, it knows to query a weather service and bring back the actual forecast.
In a sentence:
“CometChat supports function calling so your AI agents can not only chat but also act like retrieving data, updating systems, or completing transactions seamlessly.”
Guardrails (noun)
Definition:
Guardrails are the safety systems, policies, and checks that keep AI agents operating responsibly and within defined boundaries. They filter out harmful or biased responses, block unsafe user input, and enforce compliance or brand standards, ensuring AI doesn’t go off-track.
Um, what?
Think of guardrails as bumpers on a bowling lane or seatbelts in a car. Even if the AI veers off course or if someone tries to trick it guardrails keep interactions safe, professional, and aligned with company values.
In a sentence:
“CometChat’s built-in guardrails protect both sides of a conversation, shielding users from harmful outputs and preventing malicious inputs from breaking the system.”
User Presence (noun)
Definition:
User presence refers to the live indicators that show whether a person is online, offline, typing, or active in a chat. It creates a sense of immediacy and human connection by letting participants know who is available, engaged, or responding in real time.
Um, what?
It’s like seeing the green dot on Instagram or Slack that tells you your friend or colleague is active, or the familiar “typing…” bubble that makes conversations feel alive.
In a sentence:
“CometChat includes user presence features so conversations feel more human, transparent, and interactive.”
Message Moderation (noun)
Definition:
Message moderation is the process of scanning, filtering, and managing chat messages to prevent harmful, offensive, or unsafe content from being delivered. It uses rules, AI models, and contextual analysis to maintain safety, compliance, and trust in conversations.
Um, what?
Think of it as a smart security guard at the door of every conversation. It doesn’t just block obvious profanity it also detects spam, scams, harassment, or attempts to bypass platform rules.
In a sentence:
“CometChat’s AI-driven message moderation ensures every chat stays respectful, compliant, and safe for all users.”
Co-Pilot (noun)
Definition:
A co-pilot is an AI assistant designed to work alongside humans, augmenting their abilities rather than replacing them. It can suggest content, automate repetitive tasks, provide real-time recommendations, and help guide users through complex processes.
Um, what?:
Imagine working with a helpful colleague who sits beside you- drafting your email, suggesting edits, or pulling up relevant documents before you even ask. That’s what an AI co-pilot does inside digital tools.
In a sentence:
“CometChat enables AI co-pilots that sit inside your chat, helping users with personalized, proactive guidance in real time.”
Orchestration Layer (noun)
Definition:
The orchestration layer is the system that coordinates and manages interactions between multiple AI models, tools, databases, and workflows. It ensures everything runs smoothly together handling input, routing requests, combining outputs, and managing context.
Um, what?
It’s like the conductor of an orchestra, making sure every instrument whether it’s a database, an API, or an LLM comes in at the right time to create a seamless experience. Without it, you’d just hear noise instead of music.
In a sentence:
“CometChat provides the orchestration layer that ties LLMs, RAG, workflows, and moderation together into a single, reliable chat experience.”
Understanding the language of technology is key in today’s fast-paced world. This glossary equips you with clear definitions from AI to real-time chat helping developers, product managers, and curious learners navigate, communicate, and stay ahead in an ever-evolving tech landscape.
Shrinithi Vijayaraghavan
Creative Storytelling , CometChat