Easy AI: First Steps
🎯 How to Prompt: Getting AI to Work for You
Think of prompting as giving clear instructions to a smart intern. The better your request, the better the result. AI isn’t mind-reading—it’s pattern-matching. Here’s how to guide it:
Start with context – Tell it who you are and what you need. (“I’m a small business owner creating a customer email…”)
Be specific, not vague – “Write a 3-paragraph summary for my weekly team update” works better than “Summarize this.”
Set style and tone – Use phrases like “Make it professional but friendly” or “Write for busy executives who scan quickly.”
Break down big tasks – Instead of “Make me a marketing plan,” try:
- Outline the steps.
- Suggest budget ranges.
- Write sample ad copy.
Iterate and refine – If the first answer isn’t perfect, ask the AI to “shorten this,” “make it more persuasive,” or “explain like I’m new to this.”
What is AI
🌪️ The ‘Perfect Storm’ That Brought AI to Life
Why is AI suddenly everywhere? It’s not magic. It’s the result of three major breakthroughs converging all at once:
- Super-fast, high-capacity computers – They process and store massive amounts of information quickly.
- Smarter algorithms and coding techniques – They make sense of patterns in language, images, and behavior.
- Huge amounts of data from the internet – Every web page, YouTube video, article, and book became AI’s training ground.
Together, this “Perfect Storm” created the foundation for GPTs (Generative Pretrained Transformers)—the technology behind ChatGPT, Claude, Gemini, and Llama.
Artificial Intelligence: What we know as AI came about when ChatGPT was released November 2022.
Try Prompting these AI Models
GPT-5
OpenAI’s most advanced AI model
GPT-5 offers state-of-the-art performance in reasoning, creativity, and accuracy—featuring improved writing, reduced hallucinations, agentic coding, multimodal capabilities, and advanced research tools for complex problem-solving.
Opens in a new tab. OpenAI account required.
Nano Banana
Google’s AI image editor
Nano Banana is Google’s cutting-edge AI model for natural-language image editing. It allows you to transform photos with simple text prompts—changing backgrounds, enhancing details, or creatively reimagining entire scenes—directly in Google AI Studio.
Opens in a new tab. Google account required.
Suno
AI-powered music creation
Suno lets anyone create original songs in seconds using AI—no instruments or prior music experience needed. Generate full tracks, lyrics, and melodies directly from your ideas.
Opens in a new tab. Free and paid plans available.
Try more models in the ReadAbout AI Playground
🧬 From GPT-1 to ChatGPT: A Quick Timeline
- 2018: GPT-1 launched by OpenAI. AI began understanding language in new ways.
- 2022: ChatGPT debuts—giving people a conversational way to interact with an AI.
- 2023–2025: Rapid evolution. These models can now create not just text, but also images, audio, and even video.
- August 2025, and OpenAI has unveiled GPT-5—its smartest, fastest, and most capable AI model yet. This isn’t just an upgrade—GPT-5 is a strategic leap forward, combining advanced reasoning, multimodal input, and task execution into a unified, intelligent system.
That’s like going from typewriters to smartphones—in three years.
📖 Mini-Glossary: Terms You’ll See Everywhere
Generative AI – A type of AI that doesn’t just analyze—it creates. It can draft emails, generate images, write code, or even make music.
LLM (Large Language Model) – The brains behind tools like ChatGPT. Trained on huge amounts of text, LLMs can understand and generate human-like language.
ChatGPT – OpenAI’s conversational AI. Popular for answering questions, drafting content, and brainstorming.
Claude – Anthropic’s AI assistant. Known for its “constitutional AI” approach, emphasizing safety and reliability.
Google (Gemini) – Google’s family of AI models (rebranded from Bard). Strong in search, productivity, and multimodal tasks.
Llama (Meta) – Meta’s open-source LLM family. Widely used by developers and startups because it’s free to adapt.
Grok 4 – X (formerly Twitter)’s AI assistant, built by Elon Musk’s xAI. Integrated into the social platform with a more irreverent tone.
Agentic AI – AI that doesn’t just respond, but can take actions: planning steps, calling tools, or running tasks on your behalf.
Prompts – The instructions you give an AI (“Write a summary of this report in three bullet points”). Clear prompts = better results.
Prompt Engineering – The skill of designing prompts strategically to get consistent, high-quality outputs. A growing must-have skill in business.
Multimodal AI – AI that works across text, images, audio, and video (not just words). The newest models combine these seamlessly.
Hallucination – When AI generates an answer that sounds confident but is factually wrong. Important to watch out for in business use.
RAG (Retrieval-Augmented Generation) – A technique where AI looks up real information (e.g., from your files or the web) before generating answers. Increasingly common in business tools.
Fine-Tuning – Custom-training an AI on your company’s data so it “speaks your language” and fits your needs.
Tokens – The chunks of text (pieces of words) that AI reads and writes. Token limits determine how long your inputs and outputs can be.
AI Ethics / Responsible AI – Frameworks and principles guiding the safe, fair, and transparent use of AI. Often discussed in regulations and corporate policies.
More AI terms in the ReadAboutAI.com Executive AI Glossary
🏢 Key AI Companies You’ll See Everywhere
AI isn’t built in a vacuum—it’s driven by some of the world’s most powerful companies. Many of them you already know—Google, Amazon, Apple—but what’s easy to miss is that these giants are also AI companies at their core. From the chips that power AI to the apps you use every day, these firms shape how AI shows up in business and daily life.
OpenAI – Creator of ChatGPT and GPT-5. A research-driven AI company that brought generative AI into the mainstream.
Google (Alphabet) – Powering Gemini (its family of AI models) and weaving AI into Search, Gmail, Docs, and YouTube.
Amazon – Beyond retail, Amazon runs AWS, the world’s leading cloud platform—and a backbone for training and running AI models.
Apple – Focused on embedding AI into devices and services (Siri, iPhone, Mac). Often called a “quiet giant” in AI because of its scale and ecosystem.
NVIDIA – The hardware king. Its GPUs (graphics processing units) are the engines that power nearly every modern AI model.
Meta (Facebook) – Developer of Llama, a major open-source AI model. Heavy investor in AI for social platforms and metaverse projects.
xAI – Elon Musk’s AI venture, best known for Grok, integrated into X (Twitter). Positions itself as a challenger to OpenAI and Google.
Oracle – Enterprise software and cloud powerhouse. Recently entered the AI spotlight through partnerships (including with OpenAI) to power business AI infrastructure.
Microsoft – A cornerstone player through its deep partnership with OpenAI (integrating GPT into Office, Teams, and Azure). For most executives, AI in Word, Excel, and Outlook is their first daily contact point.
IBM – Longstanding enterprise AI player with Watson and newer AI governance / enterprise services. Still a trusted brand for regulated industries.
Anthropic – The company behind Claude. Strong emphasis on “constitutional AI” and safety, now considered one of OpenAI’s closest peers.
Salesforce – Embeds AI (“Einstein AI”) directly into CRM and marketing tools that many SMBs already use.
Adobe – A leader in generative design and media tools (Firefly for Photoshop, Illustrator). Essential for creative/marketing departments.
OpenAI, Google, Amazon, Apple, NVIDIA, Meta, xAI, Oracle
👥 Key People in AI News
Behind every breakthrough AI tool are the leaders who fund, build, and debate its future. These names appear constantly in the news — understanding who they are helps you follow the conversation around AI’s direction, risks, and opportunities.
Sam Altman – CEO of OpenAI, the company behind ChatGPT. Central to both AI innovation and policy debates.
Elon Musk – Founder of xAI and outspoken AI critic/supporter. Positions AI as both a transformative tool and a global risk.
Mark Zuckerberg – CEO of Meta, driving investment in Llama open-source AI models and AI-powered social platforms.
Tim Cook – CEO of Apple, overseeing the integration of AI into iPhones, Macs, and services with a focus on privacy.
Jensen Huang – CEO of NVIDIA, maker of the GPUs powering nearly every major AI system. Often called the “arms dealer” of the AI boom.
Satya Nadella – CEO of Microsoft, who championed the OpenAI partnership and integrated GPT into Office and Teams.
Demis Hassabis – CEO of Google DeepMind, pioneer in reinforcement learning and scientific AI breakthroughs like AlphaFold.
Sundar Pichai – CEO of Google/Alphabet, leading the company’s “AI-first” strategy through Gemini and cloud services.
Dario Amodei – CEO of Anthropic, building Claude with an emphasis on safety and reliability.
Daniela Amodei – Co-founder and President of Anthropic, shaping its governance and responsible AI approach.
Mustafa Suleyman – Co-founder of DeepMind, now CEO of Microsoft AI, focused on bringing advanced AI into enterprises.
Fei-Fei Li – Stanford professor and computer vision pioneer. Former Google AI lead and strong advocate for human-centered, ethical AI.
Geoffrey Hinton – Deep learning pioneer, Turing Award winner, and early neural networks champion. Recently left Google to warn of AI risks.
Yoshua Bengio – Turing Award–winning researcher in deep learning, active voice for ethical AI development.
Yann LeCun – Chief AI Scientist at Meta and Turing Award winner. Strong advocate for open research and accessible AI.
Reid Hoffman – LinkedIn co-founder and early OpenAI investor. Influential voice in AI funding and responsible adoption.
Emad Mostaque – Founder of Stability AI (Stable Diffusion), leading open-source generative image tools.
Arvind Krishna – CEO of IBM, guiding Watson and enterprise AI applications for business.
Andrew Ng – Co-founder of Google Brain, founder of deeplearning.ai, one of AI’s most prominent educators.
Richard Socher – Former Salesforce Chief Scientist, now CEO of You.com, building an AI-powered search engine.
⚠️ Risks & Pitfalls to Keep in Mind
AI is powerful, but it’s not perfect. These are the common warnings you’ll see repeated in the news, research, and business conversations.
Hallucinations – AI can make up facts that sound right but aren’t true. Always double-check.
Bias in Data – If the training data has bias, the AI may reinforce stereotypes or unfair outcomes.
Privacy Concerns – Sensitive company or customer data should never be pasted into a public AI tool.
Over-Reliance – AI is a great assistant, not a replacement for human judgment.
Intellectual Property Risks – Some AI-generated text, code, or images may raise copyright or ownership issues.
Security Risks – Prompt injection and malicious use are emerging ways bad actors can manipulate AI.
Cost Creep – Free tools are limited; enterprise-grade AI usage can scale costs quickly if unchecked.
Job Disruption – AI will change workflows; some roles may shrink, but new ones will also emerge.
Regulatory Uncertainty – Governments are drafting AI laws fast. What’s allowed today may be restricted tomorrow.
Ethics & Trust – Using AI without transparency can harm brand reputation and customer trust.
🤖 What Is AI, Really?
At its core, Artificial Intelligence is pattern recognition at scale. AI systems learn from massive amounts of data—text, images, sound, video—and then use those patterns to generate answers, make predictions, or create new content.
Unlike traditional software that follows fixed rules, AI adapts. Give it an instruction, and it draws on what it has “seen” in its training to produce something new: an email draft, a financial forecast, a marketing slogan, even a product design.
Think of AI as a toolbox of smart assistants. Each assistant has different skills—some write, some analyze data, some generate images or voices. When you learn how to guide them (through prompting), AI becomes less about mystery and more about leverage for your business.
Closing: 🚀 First Steps, Big Possibilities
AI can feel overwhelming at first, but with the right mindset it becomes less about mystery and more about leverage. By learning the basics — what AI is, who’s building it, the key terms, and how to prompt effectively — you’ve already taken the most important first step.
The next step is simple: try it. Experiment with prompts, test out tools, and see where AI adds value in your business or daily work. The more you practice, the more natural it becomes.
This isn’t about replacing human intelligence — it’s about amplifying it. And you’ve just opened the door.