Welcome! This sheet is a companion to the podcast episode “Ai at Work: A Beginner’s Guide to Tools & Terminology.” Use it as a quick-reference guide to understand the key terms and concepts discussed.
Why Ai Now?
Artificial Intelligence (Ai) is transforming how we work by automating routine tasks, generating creative content, and analysing complex data. The goal is not to replace humans but to augment our skills, freeing us to focus on strategic thinking, creativity, and human connection.
Ai Jargon Buster: Key Terms Explained
Term
Definition & Simple Analogy
Artificial Intelligence (Ai)
What it is: A broad field of computer science focused on creating machines or software that can perform tasks typically requiring human intelligence (like learning, problem-solving, and recognizing patterns).
Analogy: The overarching concept of “vehicles” includes everything from bicycles to rockets.
Generative Ai
What it is: A type of Ai that can create new, original content—like text, images, music, code, or video—from a simple prompt or request.
Analogy: A creative chef who can invent a new recipe from a list of ingredients you provide.
Prompt
What it is: The instruction or question you give to an Ai tool. The quality of the output heavily depends on the clarity and detail of your prompt.
Analogy: Giving directions to a driver. “Turn left at the next light” is clearer and gets better results than just saying “drive.”
Large Language Model (LLM)
What it is: The powerful engine behind many Generative Ai tools (like ChatGPT, Claude, Gemini). It’s an Ai model trained on a massive amount of text data to understand and generate human-like language.
Analogy: A hyper-advanced autocomplete that has read a significant portion of the internet and can write paragraphs, not just the next word.
Hallucination
What it is: When an Ai model generates information that is incorrect, nonsensical, or not based on its training data. It “confidently” states falsehoods.
Analogy: A student who didn’t study for an exam and makes up a plausible sounding but entirely wrong answer.
Fine-Tuning
What it is: The process of further training a pre-existing Ai model on a specific, narrower dataset to make it an expert in a particular domain (e.g., legal documents, medical journals, your company’s writing style).
Analogy: Taking a general personal trainer and giving them special training to become an expert in rehabilitating knee injuries.
Multimodal
What it is: An Ai model that can understand and process more than one type of input, such as text, images, and audio.
Analogy: A multilingual person who can understand speech, read a book, and describe a painting, all with equal skill.
Deeper Dive: Two Important Concepts
1. What is an “Ai Model”?
Think of it as a “Digital Brain”: An Ai model is a computer program (a file) that has been trained to recognize specific patterns. This training involves analysing vast amounts of data.
It’s Not a Database: It doesn’t just store information. Instead, it learns the underlying patterns from the data. For example, a model trained on thousands of cat photos learns the general “pattern” of a cat (ears, whiskers, fur) rather than memorizing each photo. This allows it to identify a cat in a picture it has never seen before.
Different Models for Different Tasks: Some models are for generating text (LLMs), some for recognising speech, and some for predicting sales trends. The podcast host likely refers to these as the “tools” or “engines” powering the applications you use.
2. What does “Agentic” Mean? (Key Takeaway)
Beyond Simple Commands: An Ai tool that is “agentic” (or an Ai Agent) can perform multi-step tasks autonomously to achieve a goal you set. Instead of just answering a single question, it can plan, execute, and adapt.
It has a goal and takes action: You give it a high-level objective, and it figures out the steps needed, uses tools (like web browsers, calculators, or software), and completes the job.
Work Example:
Non-Agentic (Simple Ai): “Draft an email about the project update.” (It does one task).
Agentic (Ai Agent): “Manage the project update. Find the latest status report in our shared drive, summarize the key progress and blockers, draft an email to the client, and schedule a check-in meeting with the engineering team for next week.” (It plans and executes a multi-step workflow).
In short: Agentic Ai is a proactive, goal-oriented assistant, not just a reactive tool.
Getting Started: Tips for Using Ai at Work
Start with Low-Stakes Tasks: Use Ai for brainstorming, drafting first versions, or summarising long articles.
Write Clear Prompts: Be specific about your goal, context, and desired format (e.g., “Function as a marketing manager and write a 3-sentence tweet about our new eco-friendly product, aimed at young professionals. Use an enthusiastic tone.”).
Always Review and Edit: You are the expert. Never blindly trust Ai output. Always fact-check, edit for tone, and add your unique human insight.
Follow Company Policy: Be aware of your company’s guidelines on using Ai, especially concerning confidential and client data. Never input sensitive information into public Ai tools.
Enjoy exploring how Ai can make your work life easier and more productive!
This document was created to accompany the podcast “Are you being Served?” with guest Asitha Rodrigo. For more resources, please visit smartresourcesolutions.com
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