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<h3>TLDR: AI terms like LLM, diffusion model, and foundation model can seem impenetrable. This guide explains them in plain language, shows why they matter for business, and offers practical ways to start using AI tools without technical expertise.</h3><h2>What is AI in plain terms?</h2>Artificial intelligence is about building computer systems that can perform tasks normally requiring human intelligence — things like analysing data, answering questions, or creating content. In business, AI is most valuable when it saves time, improves accuracy, or supports better decision-making.The challenge? Much of the language around AI is filled with technical shorthand that can make practical use feel out of reach.<h2>Key AI terms every business professional should know</h2><ul><li>Artificial Intelligence (AI) – The broad field of making systems that can solve problems, make decisions, or understand human-like tasks. </li><li>Machine Learning (ML) – A type of AI where systems learn from data to spot patterns and make predictions. </li><li>Generative AI – Tools like ChatGPT or Claude that create new text, images, or code from learned patterns. </li><li>Artificial General Intelligence (AGI) – A still-theoretical form of AI with human-level intelligence across all tasks. </li><li>Bias – When AI outputs reflect the prejudices in the data it was trained on, sometimes producing unfair results. </li><li>Hallucinations – When AI produces confident but incorrect or nonsensical answers. Often even doubling down on a wrong answer...watch for this carefully.</li></ul><h2>What are AI models?</h2>AI models are trained systems that power most AI tools you use today. They differ by the type of data they work with and how they process it:<ol><li>Large Language Models (LLMs) – Specialise in understanding and producing text. Power chat-based tools like GPT or Claude. </li><li>Diffusion Models – Used for image and media generation by adding and removing noise to produce a final, high-quality output. </li><li>Foundation Models – General-purpose models trained on vast datasets, forming the base for many AI applications without needing major retraining. </li><li>Frontier Models – Marketing term for cutting-edge models with greater capability and, often, increased governance and safety concerns. </li></ol>Knowing which model a tool is built on helps you understand its strengths, weaknesses, and potential risks.<h2>Why should business leaders care about AI terminology?</h2>The terms are not just technical jargon (we try) they signal how a tool works, what it can do, and where it might fail. If you’re clear on the basics, you can:<ul><li>Have informed conversations with vendors and colleagues. </li><li>Spot overhyped claims. </li><li>Identify realistic use cases for your workflows. </li></ul>Example: Understanding that a tool is a “diffusion model” for images means you know it can’t analyse text, while an LLM won’t create original images.<h2>How to start applying AI in your work today</h2>You don’t need to overhaul your business to start benefiting from AI. Begin with small, controlled experiments:<ul><li>Identify a repetitive task – Drafting customer emails, summarising reports, or preparing meeting agendas. </li><li>Select the right tool – Use a text-based model like ChatGPT for writing or an image generator for visual material. </li><li>Test and review – Run a real task, review the output, and adjust prompts to improve results. </li><li>Document what works – Keep a simple log of prompts and successful workflows for reuse. </li></ul>Hands-on use makes the terminology clearer and helps you judge the value of each tool for your specific context.&nbsp; Turning knowledge into action<ul><li>Focus on practical gains: Where can AI save you time or reduce errors? </li><li>Try a few low-risk pilots before scaling. </li><li>Keep learning through real examples: case studies in your industry are often more useful than general AI news. </li></ul>This approach keeps adoption low-cost and builds capability without overwhelming your team.<h2>FAQ</h2>Q: Do I need to understand every AI term to use it effectively? A: No, but knowing the basics helps you choose the right tools and set realistic expectations.Q: Which is safer to start with — text or image AI? A: Text tools like ChatGPT are often easier for beginners because they fit naturally into existing workflows.Q: How do I avoid bias or inaccuracies? A: Always fact-check important outputs and avoid using sensitive data without checking a tool’s privacy policy.If you want to go beyond definitions and actually test AI tools in your own workflows, our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclass</a> gives you a step-by-step process to evaluate tools, build prompt libraries, and make confident adoption decisions.

Your 5 Minute AI Cheat Sheet for Business

OpenAI ChatGPT and Anthropic Claude mobile APP icons on screen. Assorted AI chatbots

<h3>TLDR:&nbsp; Claude 3 can manage projects, create tailored outputs, and support creative work when you give it clear instructions and the right context. This guide explains how to use it for task planning, brainstorming, workflow automation, and visual data presentation so you can get accurate, usable results.</h3><h2>What is Claude 3 and why use it for task management?</h2>Claude 3, from Anthropic, is an AI assistant designed to handle both structured and creative work. For business professionals, its strength lies in organising complex tasks into actionable steps and delivering outputs in formats you can use immediately.If you’re managing a project, planning an event, or coordinating a team, Claude can create schedules, reminders, and action plans — provided you supply enough detail about<figure id="figure-r1dtni8dsm5q0iao1"><img id="r1dtni8dsm5q0iao1" src="https://cdn.durable.co/getty/338xxaeAql5VJ8BTmbd3qUi0ASVdFSd8plEBUY0DXFDDHhDPB4ME00pc6SA0rM8A.jpeg" alt="AI technology" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/338xxaeAql5VJ8BTmbd3qUi0ASVdFSd8plEBUY0DXFDDHhDPB4ME00pc6SA0rM8A.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>How to plan and organise tasks with Claude 3</h2>Claude works best when you break large projects into smaller components. Start by giving it:<ul><li>A clear goal for the task or project. </li><li>Any deadlines and milestone dates. </li><li>Supporting documents or images. </li></ul>Example: For an event launch, upload the programme outline, budget sheet, and key deadlines. Claude can then create a task list, assign priority levels, and prepare a timeline you can share with your team.<h2>How to use Claude 3 for brainstorming and problem-solving</h2>Claude isn’t limited to task lists, it can expand ideas and approach problems from different angles. You can:<ul><li>Share initial concepts and ask for alternative approaches. </li><li>Request lists of pros and cons for specific decisions. </li><li>Generate personalised resources, such as checklists or calculators. </li></ul>For content work, Claude can also:<ul><li>Suggest SEO keywords for blog articles. </li><li>Optimise text for clarity and tone. </li><li>Analyse meeting or call transcripts to extract key decisions and next steps. </li></ul>This makes it a useful partner for both creative development and operational follow-through.<figure id="figure-bcs0uo6emmm5q0ilfa"><img id="bcs0uo6emmm5q0ilfa" src="https://cdn.durable.co/getty/2eWSHe0W0rkPzqWlf9KIMGl1mlMQXBoCXYd6TsCQ5ToS7dj52ZaEem753Tn0EbxJ.jpeg" alt="beginner tips" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/2eWSHe0W0rkPzqWlf9KIMGl1mlMQXBoCXYd6TsCQ5ToS7dj52ZaEem753Tn0EbxJ.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>How to customise Claude for your workflow</h2>Claude can adapt to your style of working if you give it explicit guidelines. That includes:<ul><li>Setting tone and format requirements. </li><li>Combining multiple requests in a single prompt to reduce back-and-forth. </li><li>Automating repetitive tasks, such as generating weekly status reports. </li></ul>For example, you might instruct Claude to always return project updates in a three-column table (Task, Owner, Deadline). Over time, this consistency reduces the time you spend editing or reformatting outputs.<h2>How to bring data to life using Claude </h2>Claude’s visual capabilities are particularly useful for professionals who need to simplify complex information. You can ask it to:<ul><li>Create charts and infographics from your data. </li><li>Design slide layouts for presentations. </li><li>Build interactive dashboard concepts for dynamic reporting. </li></ul>This is valuable when presenting results to stakeholders who need quick, clear takeaways rather than raw data tables.<figure id="figure-o7yuxhjlmm5q0ivye"><img id="o7yuxhjlmm5q0ivye" src="https://cdn.durable.co/getty/0QGYaRkSyE6TUhcHOaWpDz6dftc6NVVGQpPan2NDRBbAoKR4qZzsfTEWQrkSG7IL.jpeg" alt="project integration" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/0QGYaRkSyE6TUhcHOaWpDz6dftc6NVVGQpPan2NDRBbAoKR4qZzsfTEWQrkSG7IL.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>How to make Claude easier to use daily </h2>A tool is only as good as your ability to access and apply its outputs. Claude’s interface allows you to:<ul><li>Organise and rename chat sessions for quick retrieval. </li><li>Adjust visual settings for a comfortable workspace. </li><li>Save screenshots of key responses for documentation. </li></ul>Using natural, conversational prompts helps keep interactions efficient — especially if you’re still building confidence with AI tools.<h2>How to keep improving your results with Claude</h2>The more you use Claude, the better you can adapt it to your needs. Strategies to try:<ul><li>Assign “roles” in your prompt, e.g., “Act as a project manager” or “Act as a copy editor”. </li><li>Use follow-up prompts to refine ideas rather than starting over. </li><li>Switch between Claude’s different models to match the task — some excel at analysis, others at creative expansion. </li><li>Tracking which approaches give you the most useful outputs helps build a repeatable process.</li></ul><figure id="figure-9ble9h9os5m5q0j3ya"><img id="9ble9h9os5m5q0j3ya" src="https://cdn.durable.co/getty/bXkJlI3PRfM9UdVjfR4lqxF6Y6CwdTrLq0kxU7PtDG3Amo2w6huAs2g4BF7IXzKY.jpeg" alt="continuous learning" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/bXkJlI3PRfM9UdVjfR4lqxF6Y6CwdTrLq0kxU7PtDG3Amo2w6huAs2g4BF7IXzKY.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>FAQ</h2>Q: What’s the fastest way to get value from Claude 3? A: Start with one high-impact task you repeat often, like weekly reporting, and optimise that first.Q: Can Claude 3 work with my existing project management tools? A: Yes, you can export its outputs into spreadsheets, documents, or dashboards for integration.Q: How much detail should I give Claude? A: More is better. The more context and constraints you provide, the more precise the result.If you want to identify where Claude or similar AI tools can slot into your real workflows, our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclass</a> gives you a step-by-step testing process,&nbsp; so you choose tools based on results, not guesswork.<h2>.</h2>

Mastering Claude 3: A Beginner's Guide

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<h3>TLDR: AI can handle everyday tasks like drafting emails, summarising reports, and preparing presentations, freeing professionals to focus on higher-value work. This guide explains how to start small, build confidence, and apply AI to real business challenges without needing technical expertise.</h3><h2>How can business professionals use AI without a technical background?</h2>You don’t need coding skills to make AI work for you. The most effective starting point is to treat it as a tool for routine tasks. Tools like ChatGPT can summarise documents, generate meeting agendas, or provide first drafts of reports. These are practical, low-risk uses that deliver value quickly.The key is to focus on applications that save time or improve accuracy — not just novelty. For example:<ul><li>Drafting customer responses in a consistent tone. </li><li>Creating presentation outlines from bullet points. </li><li>Turning lengthy meeting notes into short, clear summaries.</li></ul><figure id="figure-6y9d00byhinm5owedku" class=""><img id="6y9d00byhinm5owedku" src="https://cdn.durable.co/blocks/22jsRu2aK02OVrBlg9lmchXnVpSfRUXhiTtGeYaZtrzqFwZtOo5AWEjP8xddQoYu.png" alt="business AI" title="business AI" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="null" data-positiony="null" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/22jsRu2aK02OVrBlg9lmchXnVpSfRUXhiTtGeYaZtrzqFwZtOo5AWEjP8xddQoYu.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure><h2>What makes AI a practical business tool?</h2>AI works best when it removes repetitive, low-value work from your day. Instead of replacing roles, it supports better decision-making by speeding up preparation and reducing admin load.Examples that work for non-technical teams:<ul><li>Marketing – Generate social media post drafts from campaign themes. </li><li>Operations – Summarise performance reports for quick stakeholder updates. </li><li>Training – Turn policy documents into interactive quizzes for staff. </li></ul>Each of these keeps you in control of the final output while cutting the time it takes to get there.<h2>How can you learn AI through real work?</h2>Confidence comes from use, not theory. Start with small, repetitive tasks that already frustrate you — the ones that eat time without adding strategic value.Begin with a three-step approach:<ol><li>Pick one task – e.g., generating a weekly project update. </li><li>Test an AI tool – Ask it to draft the update using your notes or a document. </li><li>Review and improve – Edit for accuracy, then adjust the prompt next time for better results. </li></ol>Over a few weeks, you’ll identify more workflows that can be supported by AI without disruption. <figure id="figure-btec54yc4m5owembq"><img id="btec54yc4m5owembq" src="https://cdn.durable.co/getty/38wy52dWS1V7x7UvPWS1KeiGcl5d3uALSIhFTC4Cq5cCSA1N1FKKV3qnPHn77R63.jpeg" alt="AI communication" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/38wy52dWS1V7x7UvPWS1KeiGcl5d3uALSIhFTC4Cq5cCSA1N1FKKV3qnPHn77R63.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>What are real-world examples of AI in business today?</h2>AI is already being applied across industries in ways that directly improve productivity:<ul><li>Customer service – Chatbots handle repetitive queries, freeing staff for more complex requests. </li><li>Healthcare – Automated transcription of patient notes and structured analysis of medical data. </li><li>Data analysis – Pulling insights from multiple spreadsheets or reports without manual collation. </li></ul>The common thread is that AI reduces friction in getting from raw information to a usable output.<h2>How can professionals address common AI concerns?</h2>For many, the hesitation comes from fear of job loss or misuse of AI-generated content. These are valid concerns — and they’re best addressed through transparency and training.<ul><li>Decision support, not replacement – AI should feed into your work, not make final calls without oversight. </li><li>Upskilling – Short workshops or tutorials can build capability quickly, even for those with no prior exposure to AI. </li><li>Misinformation awareness – Always fact-check AI outputs, especially for client-facing or public content. </li></ul>Example: An experienced HR manager can use AI to draft a training outline but still apply their own expertise to finalise the material.<figure id="figure-4y70uwhrr6m5oweurk"><img id="4y70uwhrr6m5oweurk" src="https://cdn.durable.co/getty/8Ru8ssbDbEI7gs85T1HLPBF2SYU7ZWeHEHQBvHRFt6alYU1hTuJJxsbOQ2Sy8JPX.jpeg" alt="data analysis" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/8Ru8ssbDbEI7gs85T1HLPBF2SYU7ZWeHEHQBvHRFt6alYU1hTuJJxsbOQ2Sy8JPX.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>How do you start using AI in your daily work?</h2>Getting started doesn’t require a full-scale project. The best entry points are repetitive tasks that:<ul><li>Follow a clear format. </li><li>Don’t require sensitive or confidential information at first. </li><li>Have a clear “good enough” version you can build on. </li></ul>Practical starting actions:<ul><li>Identify three recurring tasks you could automate. </li><li>Test one AI tool, like ChatGPT, for each task. </li><li>Measure time saved or improvements in clarity. </li><li>Expand use once you see consistent value. &nbsp;</li></ul><h2>Why now is the right time to learn AI</h2>AI tools are becoming more accessible, cheaper to use, and better at handling general business tasks. Waiting until they’re “perfect” means missing the easiest time to build familiarity, when the stakes are low, and the learning curve is gentle.By starting now, you’re building habits that will pay off when your organisation begins to scale AI use across teams and processes.<figure id="figure-0fycyoepicm5owi882"><img id="0fycyoepicm5owi882" src="https://cdn.durable.co/getty/2dygOLSvLHU3xNdlEpey8DR85MpclZBLHl4PCgBM7U2Q1f85hpI1AaMnNWloWY6E.jpeg" alt="AI integration" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/2dygOLSvLHU3xNdlEpey8DR85MpclZBLHl4PCgBM7U2Q1f85hpI1AaMnNWloWY6E.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>FAQ</h2>Q: Can I use AI without any training? A: Yes, but short training sessions speed up adoption and reduce mistakes.Q: How do I know if a task is suitable for AI? A: If it’s repetitive, follows a clear structure, and doesn’t need subjective judgement, it’s a good candidate.Q: Will AI replace my role? A: AI replaces tasks, not entire roles. The value is in combining AI efficiency with human judgement.If you want a clear, beginner-friendly plan for testing AI in your own work, our<a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" data-mce-selected="inline-boundary"> AI Fundamentals Masterclass</a> gives you the tools, prompts, and examples to integrate AI quickly

Practical AI Applications for Business Professionals

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<h3>TLDR: ChatGPT works best for customer interactions, content creation, and quick drafting. Claude is better for processing long documents, analysing data, and generating structured recommendations. This guide explains what each does, the work they’re suited to, and how to decide based on your real business priorities.</h3><h2>What is the difference between ChatGPT and Claude?</h2>At first glance, they look similar: both are conversational AI tools you can chat with. But the design focus is different.ChatGPT (from OpenAI) is tuned for smooth, natural dialogue and generating text that reads like a person wrote it. Claude (from Anthropic) is tuned for understanding and interpreting longer, more complex inputs, then producing structured, insight-rich outputs. For a business starting out, the difference comes down to whether you need an on-demand writer or an on-demand analyst.<figure id="figure-ektjm3bcw9m5nblzmk"><img id="ektjm3bcw9m5nblzmk" src="https://cdn.durable.co/getty/21qlaOWj6XU1ssZJRnZMACJCoUPQlxbqDipNW7gvSd6RxMpdbmw23lc2SFOvLlb3.jpeg" alt="artificial intelligence comparison" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/21qlaOWj6XU1ssZJRnZMACJCoUPQlxbqDipNW7gvSd6RxMpdbmw23lc2SFOvLlb3.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>When is ChatGPT the right choice?</h2>For small teams and first-time AI users, ChatGPT offers a low learning curve and quick wins:<ul><li>Customer support – Handles common questions with brand-consistent tone. </li><li>Content drafting – Produces first versions of marketing copy, blog posts, or emails. </li><li>Light research – Summarises sources and compiles basic insights. </li></ul>Why it matters:<ul><li>Cost – Affordable entry point for SMEs. </li><li>Speed – Produces usable outputs quickly, with minimal setup. </li><li>Integration – Connects easily to tools like email, chat widgets, or CRM platforms. </li></ul>Example: A small online retailer uses ChatGPT to write product descriptions, answer customer questions, and draft seasonal campaign emails — freeing up staff for higher-value work.<h2>When is Claude the better choice?</h2>Claude is built for more analytical and structured work:<ul><li>Data analysis – Reads and summarises long reports or multiple sources. </li><li>Forecasting – Identifies trends and projects outcomes. </li><li>Compliance and documentation – Processes complex text for key requirements. </li></ul>Why it matters:<ul><li>Advanced analytics – Handles large or multi-document input without losing context. </li><li>Custom outputs – Adapts tone, depth, and structure to your industry. </li><li>Decision support – Produces summaries or insights you can take directly to a planning meeting. </li></ul>Example: A logistics company uses Claude to process route performance data, flag cost inefficiencies, and produce a report with recommendations for optimisation.<h2><img id="tf3ly6ffedm5nbnkm5" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="font-family: Lato, sans-serif; font-size: 18px; aspect-ratio: 16 / 9;" src="https://cdn.durable.co/getty/10kmuhvTyvk2FpLZbWawPDqcfcPQwapD362PM1pJImtYGT6W5tcwSSBIQKr4Os5v.jpeg" alt="business analytics" data-mce-src="https://cdn.durable.co/getty/10kmuhvTyvk2FpLZbWawPDqcfcPQwapD362PM1pJImtYGT6W5tcwSSBIQKr4Os5v.jpeg" data-mce-style="aspect-ratio: 16/9;"></h2><h2>How to choose between ChatGPT and Claude </h2>Before you trial either tool, clarify:<ul><li>Primary goal – Is your main task communication or analysis? </li><li>User type – Who will use it daily: customer service staff, analysts, marketers? </li><li>Data type – Are you working with short messages or long, detailed documents? </li><li>Budget – Factor in usage over time, not just initial cost. </li><li>Testing process – Run the same real-world task in both and compare accuracy, tone, and fit. &nbsp;</li></ul><h2>Can you use both together?</h2>Yes. We and many teams we work with do. ChatGPT can create outbound content or customer responses, while Claude works in the background on analysis that informs those outputs.Example: A consultancy uses Claude to summarise research reports, then passes the key points to ChatGPT to draft client-facing presentations.<h2>The future: keeping your choice relevant</h2>Both tools are updated regularly with new features. What fits now may not be the best fit in a year. Build a review cycle into your AI use, even quarterly checks can reveal if you should switch tasks between tools or adopt new capabilities.<figure id="figure-d36tvtoo2fm5nbnu04"><img id="d36tvtoo2fm5nbnu04" src="https://cdn.durable.co/getty/1dmJaTCWuFW34Qjekhu9gGC2d4B6Rgjop4K7IcqJJqUll6PjbmhXSZnYY9Jb891E.jpeg" alt="digital transformation" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/1dmJaTCWuFW34Qjekhu9gGC2d4B6Rgjop4K7IcqJJqUll6PjbmhXSZnYY9Jb891E.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>FAQ</h2>Q: Which is easier for a complete beginner?A: ChatGPT usually feels more natural because it’s built for conversational flow.Q: Which is safer for sensitive data? A: Both offer enterprise-grade security options. Check vendor compliance before sharing confidential information.Q: Can I integrate these into my existing workflows?A: Yes. ChatGPT integrates with many CRM, helpdesk, and marketing platforms. Claude can connect to analytics tools and document systems.&nbsp; If you want to test either tool in the context of your own business, our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" data-mce-selected="inline-boundary">AI Fundamentals Masterclass</a> gives you a structured process for hands-on evaluation — so you can make a confident, cost-effective choice without trial-and-error.Ultimately, the right choice between ChatGPT and Claude depends on your specific business needs and goals. By carefully evaluating the capabilities of each platform, you can make an informed decision that optimizes your operations and drives success.

ChatGPT vs Claude: Choosing the Right AI for Your Work

<h3>TLDR: Good results from AI don’t come from “hacking” prompts — they come from knowing how to ask the right way. This post breaks down five prompting techniques that help non-technical users guide AI tools like Claude and GPT. You’ll learn what works, how to refine, and how to avoid the most common mistakes that waste time and return fluff.</h3><h2>Still Getting Generic AI Output?&nbsp;</h2>Most people think AI is underperforming. It’s not. You’re just not briefing it properly.If you ask vague questions, you get vague answers. If you give no structure, the AI makes it up. But the good news: once you learn to frame a task clearly, AI becomes far more useful.Prompt design isn’t a technical skill. It’s a thinking skill. And with a few techniques, you can turn average results into real outputs you can use.<figure id="figure-ijf2uu05ukm5m0c0i7"><img id="ijf2uu05ukm5m0c0i7" src="https://cdn.durable.co/getty/22GeJwW5Z5ELhFYevI6z2uKyQImE3ZbFMfX1wYa6h25K7C3qJ0fjMSIJSikm6DiE.jpeg" alt="prompt design" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/22GeJwW5Z5ELhFYevI6z2uKyQImE3ZbFMfX1wYa6h25K7C3qJ0fjMSIJSikm6DiE.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>Context First: What the Model Needs to Know to Help You</h2>AI doesn’t know who you are, what your role is, or what tone you need unless you tell it.&nbsp; That’s where contextual priming comes in. Instead of asking:“What strategies should we use to grow market share?” Try:“We’re a mid-sized B2B services firm. Competitors have started undercutting us with self-service tools. What strategies should we use to protect revenue and retain clients?” Now you’re guiding the model. You’re giving it your world to work in. This one change often improves output dramatically.&nbsp;<h2>Refine, Don’t Restart: Prompting Is an Iterative Process </h2>Very few good outputs happen on the first try. And they don’t have to.Here’s how to improve fast:<ul><li>Review the response — what’s off? What’s close? </li><li>Adjust your prompt — clarify, simplify, or focus the task </li><li>Resubmit — don’t retype from scratch </li><li>Ask follow-ups — request revisions on just one section or point </li></ul>This is how pro users work with AI, like editing a junior colleague, not restarting from zero every time.<figure id="figure-vh2r80kk4um5m0cadm"><img id="vh2r80kk4um5m0cadm" src="https://cdn.durable.co/getty/2fPmCjKLBEmJot569ul8onu7xyn36opk1bRE61zW8PWTjNHduGB34VtTO0ZEADxb.jpeg" alt="contextual cues" class="object-cover bg-gray-100 rounded-2xl md:rounded-3xl lg:rounded-4xl" style="aspect-ratio: 16/9;" data-mce-src="https://cdn.durable.co/getty/2fPmCjKLBEmJot569ul8onu7xyn36opk1bRE61zW8PWTjNHduGB34VtTO0ZEADxb.jpeg" data-mce-style="aspect-ratio: 16/9;"></figure><h2>Five Prompting Techniques That Make a Real Difference </h2>Chain of Thought Prompting This technique breaks down complex problems into smaller, sequential steps, guiding the AI model through a logical progression. The result is a more coherent and comprehensive response.Example: For a mid-life fitness guide, instead of asking, “What should somebody in their fifties do to improve flexibility and balance?”, use structured steps:Describe common problems related to flexibility and balance for people in their fifties. Outline potential solutions. Evaluate the pros and cons of each solution. This approach encourages detailed and well-rounded answers, moving beyond basic lists to comprehensive guidance.Few-Shot PromptingFew-shot prompting involves providing examples within the prompt to help the model understand the desired format and output.Example:For a meeting summary:Basic prompt: “Summarise the meeting based on the transcript.” Few-shot prompt: *“Here are two examples of meeting summaries: The team discussed project timelines and assigned tasks. Key points included budget adjustments and resource allocation. Now summarise this meeting based on the uploaded transcript.”*The examples act as a guide, improving the AI’s ability to produce accurate and relevant summaries.Meta PromptingMeta prompting uses a two-step process where the AI first generates a secondary, more specific prompt, which is then used to create the final output. This enhances accuracy and contextual understanding.Example: Instead of directly asking, “Provide a travel guide for London,” a meta prompt could start with:“What’s a popular travel destination in Europe?” Once “London” is identified, the AI creates a more targeted travel guide. This dynamic process ensures the AI focuses on the most relevant context before delivering the output.Contextual PrimingAdding relevant background information to a prompt helps the model generate responses better aligned with specific needs.Example:OK: “What strategies should our company adopt to maintain its market share?” Better: “Given recent market trends and increased competition, what strategies should our company adopt to maintain its market share?” The additional context sets the stage for a tailored and insightful response.ReAct (Reasoning and Acting) ReAct combines reasoning and action steps in the prompt, encouraging the model to explain its answers while providing actionable recommendations.Example: For sustainable energy solutions:“Consider environmental impact and cost efficiency. Recommend a solution and explain why it’s the best option.” This structured approach ensures the response is both actionable and well-justified.<h2>Why This Matters for Business&nbsp; </h2>Most people still think prompting is a trick — or that it’s for engineers.It’s not. Prompting is now a business skill. If your team knows how to:<ul><li>Frame problems clearly </li><li>Guide tone and structure </li><li>Revise iteratively</li></ul>...they’ll get more from every tool they use. ChatGPT, Claude, Gemini: all of them.That’s exactly what we teach in our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclass.</a> No fluff. Just smart use of tools you already have taught with real business tasks in mind.<h2>FAQ</h2>Q: Do I need to learn prompt frameworks like a script? A: No. Just learn how to give the model context, structure, and a clear goal. That’s 80% of it.Q: What’s the difference between a good and bad prompt? A: A good prompt includes who you are, what you want, and how it should be delivered. A bad prompt leaves the model guessing.Q: Can I use these techniques with any AI model? A: Yes. These work across Claude, GPT-4, Gemini, and others — though output quality still depends on the model.Q: Isn’t this just basic communication? A: Exactly. Prompting is structured communication with software. The better you brief, the better the output.Q: Where can I learn how to do this properly? A: The AI Fundamentals Bootcamp gives you hands-on practice using real prompts in real workflows — built for non-technical professionals.

Writing Better AI Prompts Starts With Thinking Clearly

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<h3>TLDR: AI doesn’t read minds. If your results feel off, the problem is probably your prompt. This post breaks down how modern AI models respond to instructions, what makes a good prompt, and why effective prompting is a business skill, not a technical one. If you want better output, start with better input — and learn how to guide AI clearly.</h3><h2>&nbsp;If You’re Still Guessing with Prompts, You’re Wasting Time</h2>Most people write prompts like they’re asking a search engine or writing a riddle. Then they get annoyed when the results are vague, off-topic, or just flat wrong.The fix? Treat prompt writing like briefing a colleague. Be clear about the task, give context, show examples, and don’t overcomplicate it.That’s the heart of prompt engineering — not tricks, not templates, but effective communication.<h2>&nbsp; What Prompt Engineering Actually Means</h2>Prompt engineering is the skill of asking AI the right way. It’s not technical. It’s about writing instructions that AI can understand and act on — in a structured, focused way.The goal is to shape the output. You’re guiding the model to:<ul><li>Use the right tone </li><li>Follow the right structure </li><li>Prioritise the right information </li></ul>A vague prompt like “Write something about strategy” invites fluff. A better one: “Write a 3-paragraph summary for consultants explaining why strategy execution fails more often than strategy design. Use plain English.”<h2>&nbsp; Use Frameworks That Fit the Task</h2>Prompt frameworks help you stay consistent. Here’s how to structure your prompts for better results:1. State the role or audience “As a product manager at a mid-sized SaaS company...”2. Clarify the task “Write a LinkedIn post that explains why most AI pilots don’t scale.”3. Give format and length “Make it 3 paragraphs max, punchy tone, no jargon.”4. Add an example if needed “Here’s the kind of voice we like: short, sharp, no waffle.”Frameworks aren’t templates. They’re clarity tools.<h2>&nbsp; Model Choice Matters but Prompting Still Leads</h2>Yes, GPT-4 and Claude 3 are more advanced. They can reason, analyse, and follow complex instructions better than lighter models.But even the best model can only work with what you give it. Garbage in still equals garbage out.A few rules of thumb:<ul><li>Use advanced models for deep research, writing strategy documents, or building product workflows </li><li>Use lighter models for summaries, quick drafts, or formatting tasks </li><li>Don’t micromanage. Tell it the goal, not every step &nbsp; Examples: Better Prompts in Practice Instead of: "I need help with marketing analytics. It’s confusing."</li></ul>Try: "I’m the marketing lead for a B2B SaaS firm. I need a dashboard outline to track Q4 campaign performance. Prioritise conversion rates and cost per acquisition."Or:Instead of: "Write a blog about remote work trends."Try: "Write a 500-word blog in a conversational tone for HR professionals explaining three trends in hybrid workplace design for 2025. Focus on real-world examples, not theory."The goal is to leave no ambiguity about audience, purpose, or output format.&nbsp;Prompting Is Iterative : Don’t Expect First-Time Perfection Even with good prompting, you’ll often need to revise. That’s normal.What matters is how you manage the loop:<ul><li>Run your prompt </li><li>Read the output critically </li><li>Adjust tone, detail, or structure in your next instruction </li><li>Ask for revisions in specific sections, not a total rewrite </li></ul>Good prompts evolve. Over time, you’ll learn how to guide the model like a junior team member — one who’s fast, flexible, and doesn’t complain about feedback.<h2>&nbsp; Why This Matters for Non-Technical Teams</h2>Prompt engineering isn’t about hacking AI. It’s about using it well. That’s why it belongs in marketing, ops, HR, and admin — not just IT.Getting your team confident with prompts means:Less editing after the fact Faster outputs that actually meet the brief Better adoption and fewer abandoned pilots That’s exactly what we cover in our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclass</a>: practical, role-specific training on how to work with AI, not around it.<h2>&nbsp;FAQ</h2>Q: What’s the biggest mistake in prompting? A: Being too vague. The model doesn’t know your goals unless you spell them out.Q: Do I need to follow a strict prompt format every time? A: No. Use structure when it helps. But the key is clarity, not rules.Q: How do I know which model to use? A: Use GPT-4 or Claude 3 for detailed tasks. Use Claude 2 or GPT-3.5 for quick content or admin jobs.Q: Can prompt engineering replace training? A: No. You still need to teach people how to work with AI tools — prompting is one part of that.Q: Where can I learn this properly, without hype? A: Our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclass</a> teaches real prompting techniques using the tools you already have — built for teams who want clarity, not complexity.

How to Write Prompts That Actually Get Useful AI Results

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