Decoded: AI for Everyone

Joel Leslie

Where silicon meets soul, and algorithms make sense of the everyday.

This isn’t just another tech podcast. Decoded demystifies artificial intelligence with wit, warmth, and a dash of the delightfully unexpected. From invisible assistants that shape your shopping habits, to machine minds behind medicine, marketing, and music... we explore how AI is quietly reshaping our lives, one line of code at a time.

No jargon. No gatekeeping. Just real stories, smart people, and a gentle unravelling of the future we’re already living.

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21 episodes
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English

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S4 · E11
September 4 · 22 min
AI Misalignment: When Following the Rules is Not Enough!
Sometimes AI does exactly what it was asked to do, and still gets it wrong. In this episode of Decoded: AI for Everyone, we explain misalignment in plain English. Not as science fiction. Not as a robot rebellion. But as something much more ordinary: the gap between the instruction and the intent. An AI system may follow the rule, optimise the target, complete the task and produce the output, while still missing the human purpose behind it. This episode looks at real-world examples including healthcare algorithms, AI chatbots, proxy targets, optimisation, hallucinations and AI assurance. It explores why a system can appear to work, yet still create harm if it is solving the wrong problem. The key idea is a relatively easy one: "The instruction is not always the intent." Before using AI for anything that matters, ask what the task is really for. Are we trying to be faster, or safer? More persuasive, or more accurate? More concise, or more honest about uncertainty? Because when AI follows the rules too literally, human judgement matters more, not less. Resources: Decoded-Podcast.com/resources/s4e11 More AI resources: PromptEngineeringCookbook.com
S4 · E10
August 28 · 27 min
AI & Security: The Model Is the Target
AI security is no longer just about firewalls, passwords and patches. In this episode of Decoded: AI for Everyone, we explore why advanced AI systems are becoming strategic assets and why the model, the data it can see, the instructions it follows and the tools it can use all need to be protected. For frontier AI companies, the model itself may be the prize... the weights, training pipeline, safety methods and unreleased capabilities. But for most organisations, the risk is different. They may not own the model, but they may connect AI to internal documents, emails, workflows, customer records, policies, finance systems and decision processes. That is where the danger changes. The more useful an AI system becomes, the more valuable it may be to someone trying to misuse it. An attacker may not need to break every lock if they can manipulate the AI into using the access it already has. This episode looks at prompt injection, red team testing, hallucinations, silent failures, model security and why AI systems need an additional layer of assurance beyond normal software testing and cybersecurity. The useful habit is to ask three questions before connecting AI to anything important: What can it see? What can it do? What happens when it is wrong? Because the model is valuable because it can help. It is risky for the same reason. Show resources: Decoded-Podcast.com/resources/s4e10 More AI resources: PromptEngineeringCookbook.com
S4 · E9
August 22 · 18 min
AI & Learning: Getting the Answer Is Not Learning
Getting the answer is not the same thing as learning. In this episode of Decoded: AI for Everyone, we explore how AI is changing the way we learn, not just by giving answers, but by making ideas more visual, interactive and personal. The public conversation often focuses on students using AI to cheat. That matters, but it is not the whole story. AI can also turn equations into graphs, text into examples, confusion into questions and abstract concepts into something people can finally see. But there is a risk... AI can make learning feel easier without making understanding deeper. A clear summary can create false confidence. A polished answer can feel like mastery. A student, worker or leader may recognise an explanation while it is in front of them, but struggle to explain it once the answer disappears. This episode looks at the difference between answers and understanding, recognition and recall, fluency and mastery. It also explores how AI can become a better tutor when it asks questions, creates practice, diagnoses gaps and keeps the learner active. Before asking AI to explain more, ask it to quiz you first. Because the answer is not the lesson. The lesson is what remains when the answer is gone. Resources: Decoded-Podcast.com/resources/s4e9 More AI resources: PromptEngineeringCookbook.com
S4 · E8
August 14 · 18 min
The AI Scam That Knows You, intimately!
AI-enabled scams are becoming harder to spot because they no longer have to sound fake. In this episode of Decoded: AI for Everyone, we explore how scams are becoming more personal, more believable and more emotionally targeted. A scam message may now use your role, your family context, your writing style, your supplier relationships, your recent posts or even a cloned voice to sound familiar at exactly the wrong moment. This episode looks at voice cloning, deepfake video calls, personalised phishing, supplier impersonation, fake workers, social engineering, urgency and trust. It also revisits the privacy lesson from earlier in the season: the more personal context we put online, into systems, or into AI tools, the more material others may have to imitate us. The scam that knows you does not need to be perfect. It only needs to sound familiar when you are least ready to question it. We also cover practical habits such as using trusted callback numbers, verifying through a second channel, slowing urgent requests down, and setting a private family passphrase that is long, memorable and not easily guessed. Because in the age of AI-enabled scams, the safest sentence may be: “I am going to call you back.”... Resources: Decoded-Podcast.com/resources/s4e8 More AI resources: PromptEngineeringCookbook.com
S4 · E7
August 8 · 17 min
The AI Race Trap: The Race No One Wants to Lose
Everyone says they want safe AI. No company wants to move too fast. No country wants to lose control. No researcher wants to build something they do not understand. But nobody wants to be second. In this episode of Decoded: AI for Everyone, we explore the race trap: why competitive pressure changes AI risk, and why slowing AI down is harder than it sounds. Following on from the previous episode, S4E6, on AI acceleration, this episode looks at what happens when companies, countries and other actors all know caution is sensible but still fear falling behind. We explore frontier AI competition, national rivalry, safety trade-offs, the OpenAI and Hugging Face security incident, reward hacking, Pacing the Frontier, and the harder question behind AI slowdown: who slows down, who verifies it, and what happens if someone does not? This is not an argument against pacing AI. It is an argument for taking pacing seriously. Because slowing down is not just a pause button. It is a trust problem, a verification problem, a security problem and an enforcement problem. Once the race begins, caution only works if it survives the race. Resources: Decoded-Podcast.com/resources/s4e7 More AI resources: PromptEngineeringCookbook.com
S4 · E6
July 29 · 20 min
When AI Enters the Engine Room
Most people still think AI is just a chatbox. You type a question. It gives you an answer. An email. A summary. A recipe. A report. That is the version of AI most people know. But the chatbox is only the front counter. Behind it, AI is becoming something much larger: agents that use tools, systems that coordinate other systems, and research workflows where AI helps improve the next generation of AI. In this episode of Decoded: AI for Everyone, Joel looks at the acceleration loop: what happens when AI is no longer only the product, but part of the process that builds the next product. This is not about panic. It is not about claiming AI is already fully building itself. It is about understanding why some researchers are less worried about chatbots writing emails and more concerned about AI entering the engine room of AI development. We look at multi-agent systems, the road to artificial superintelligence, AI 2027, AI 2040, and the ROME case, where an experimental AI agent reportedly found unintended paths while using tools and infrastructure. The key question is simple: When AI starts helping build better AI, can human oversight keep up? Because once AI enters the improvement loop, the issue is no longer only capability. It is speed. And speed is not the same as control. Resources for this episode: Decoded-Podcast.com/resources/s4e6 For broader AI tools, prompt guides and practical resources: PromptEngineeringCookbook.com
S4 · E5
July 23 · 21 min
The AI Invisible Workload & the Privacy Cost of Relief
AI promises to take pressure off... But at what cost? For years, companies have tried to understand what is inside your head. Search engines saw what you looked for. Social platforms saw what you clicked. Your phone saw where you went. Your calendar saw what you scheduled. But none of them could see the whole messy working file of your life. The unpaid bill. The prescription. The school note. The dentist appointment. The conversation you are avoiding. The birthday present you still have to buy. The thing someone mentioned in passing that somehow became yours to remember. Until now! In this episode of Decoded: AI for Everyone, we look at the invisible workload: the hidden work of remembering, organising, following up, checking, planning and carrying the open loops of everyday life. AI can help with that. It can organise the mess, reduce friction and make life easier to manage. But there is a trade... For AI to organise the invisible workload, it first has to see it. And the invisible workload is not just admin. It can reveal your health, money, family, work, relationships, worries and responsibilities. Sometimes, it includes other people’s private information too. This episode is not about rejecting AI. It is about using it deliberately. When you hand AI the contents of your head, what are you actually handing over? Who can see it? Where does it go? What should you leave out? And how do you get the help without giving up more than the task requires? Season 4 continues with a sharper look at Applied Intelligence: not just what AI can do, but what it costs, what it changes and how we stay in control. Resources for this episode: Decoded-Podcast.com/resources/s4e5 For broader AI tools, prompt guides and practical resources: PromptEngineeringCookbook.com
S4 · E4
July 15 · 30 min
ChatGPT And Your Personal Performance Stack!
Most people already use ChatGPT. They use it to write emails, summarise documents, plan trips, explain ideas, compare options, study, draft posts, organise notes and make sense of everyday tasks. But for many people, ChatGPT still works like a blank chatbox. You open it, ask a question, get an answer, close it, then come back later and start all over again. In this episode of Decoded: AI for Everyone, we continue Season 4: Applied Intelligence by looking at how to turn ChatGPT into something more useful: a personal performance stack. Not a complicated system. Not a tutorial. Not AI for everything. A practical way to use ChatGPT across the parts of life and work where better planning, clearer thinking, better writing, smarter research and stronger follow-through actually matter. We walk through real use cases, including: Weekly planning Life admin Decision briefs Writing and editing Learning and study Budget and spreadsheet review Travel planning Creative thinking Personal knowledge bases Most people do not need more AI tools. They need a better way to use the one they already open. This episode introduces a simple loop: Capture. Context. Thinking. Output. Review. That is the foundation of a personal performance stack. You’ll also hear practical cautions about not turning ChatGPT into one giant dumping ground, not pasting sensitive information by habit, not confusing memory with judgement, and knowing when to start a fresh chat. Resources for this episode, including the prompts, starter templates and practical examples mentioned in the show, are available at: decoded-podcast.com/resources/s4e4 More from Decoded: decoded-podcast.com Practical AI tools, prompt guides and platform comparisons: PromptEngineeringCookbook.com Strategen AI helps organisations adopt AI safely, practically and without unnecessary cost or risk: strategen-ai.com
S4 · E3
July 8 · 42 min
Claude Cowork: When AI Starts Working in Your Files
From Chatbox to Workspace! What happens when AI stops being a chatbot and starts working inside your files? In this episode of Decoded: AI for Everyone, we continue Season 4: Applied Intelligence by looking at Claude Cowork and the bigger shift it represents. AI is moving from the chatbox into the workspace. Documents, spreadsheets, folders, reports, meeting notes, templates and outputs. The question is no longer just, “What should I ask AI?” It is, “How do I structure the task so AI can help safely and practically?” We walk through real-world examples of using AI inside work, including preparing a briefing note, working with Excel, identifying duplicated expenses, creating summary tabs and charts, using brand templates, and setting up folder structures that help AI understand what to use, what to protect, and where to put the final output. You’ll also get a practical at-home exercise using recipes and meal planning, so you can test the workflow safely without starting with client files, sensitive documents or your whole desktop. The takeaway is simple: do not just give AI a messy task and hope for the best. Give it a workspace, rules, boundaries and a review step. Resources for this episode, including the folder structures, workspace rules, prompts and practical instructions, are available at https://decoded-podcast.com/resources/s4e3 More from Decoded: https://decoded-podcast.com AI tools, platform comparisons and practical guides: https://PromptEngineeringCookbook.com Strategen AI helps organisations adopt AI safely, practically and without unnecessary cost or risk: https://www.strategen-ai.com
S4 · E2
July 2 · 17 min
AI & Search
ChatGPT is not Google. And Google is not ChatGPT. In this episode of Decoded: AI for Everyone, we continue Season 4: Applied Intelligence by looking at one of the most common mistakes people make with AI: treating a generated answer like a verified answer. Search helps you find information. AI helps you explain, summarise, compare and make sense of information. Some tools now do both, but the difference still matters. We break down how to use AI and search together without getting misled, including when AI is useful on its own, when you need to check sources, and when you should slow down before relying on the answer. You’ll also get a simple practical prompt you can use before your next important search: “I’m trying to find reliable information about [topic]. First, explain the topic in plain English. Then give me five search terms to use, the most reliable types of sources to check, the claims I should verify, and any red flags that might suggest the information is weak or outdated.” Use AI to understand. Use search to verify. Use judgement to decide. Resources Resources for this episode, including the prompt and supporting notes, are available at: https://decoded-podcast.com/resources/s4e2 More from Decoded: https://decoded-podcast.com Prompt guides and practical AI resources: https://PromptEngineeringCookbook.com Strategen AI helps organisations adopt AI safely, practically and without unnecessary cost or risk: https://www.strategen-ai.com
S4 · E1
June 25 · 38 min
Applied Intelligence: How AI Actually Works in the Real World
Welcome to Season 4 of Decoded: AI for Everyone. New season. New look. Longer episodes. And a sharper focus on helping you actually understand and use AI in the real world. In this opening episode, we go back to the foundations: how AI actually works. Not in a heavy technical way, but in plain English. We unpack tokens, prediction, context windows, pre-training and fine-tuning, using something most of us already understand: predictive text on your phone. Because once you understand that AI is often predicting, generating and shaping responses based on patterns and context, a lot starts to make more sense. Why does AI sometimes sound confident but wrong? Why does a better prompt usually get a better answer? Why do different tools give different responses? Why does context matter so much? And why is ChatGPT not simply “Google with a nicer interface”? This episode is a bigger one, so take your time with it. There is a lot to take in, but it sets the foundation for the rest of Season 4. We also share the practical prompt and frameworks mentioned in the episode, including SCAFFOLD and CRAFTED, so you can start getting clearer, more useful answers from AI. Resources: Episode resources, prompts and frameworks: Decoded-podcast.com/resources/s4e1 Decoded: AI for Everyone: Decoded-podcast.com Prompt guides and practical AI resources: PromptEngineeringCookbook.com Strategen AI, helping businesses adopt AI without adding unnecessary cost or risk: Strategen-ai.com This season is about cutting through the hype and the confusion, with a more practical understanding of how AI works in your work, your choices, your creativity and your everyday life.
June 15 · 8 min
AI & Memory, Attention, Intuition, and the Habits of Thinking
Season 3 Rerun AI is making everyday thinking easier. It can draft the email, summarise the report, suggest the idea, organise the information and help us get started faster. That can be incredibly useful. But it also raises a more personal question: "When AI starts carrying more of the mental load, what happens to the habits of thinking we used to practise ourselves?" This episode revisits the idea of cognitive offloading: the way humans use tools to reduce mental effort. We have always done this. The printing press changed memory. Calculators changed arithmetic. Search engines changed how we find information. AI is different because it does not just help us store or calculate. It helps us think. In this episode: Why cognitive offloading is not automatically a bad thing How AI changes memory, attention, intuition and judgement Why the first stage of thinking still matters What writers, designers, strategists and professionals risk losing if they stop practising the early steps How to use AI without weakening your own cognitive fitness As Decoded: AI for Everyone moves toward Season 4 and Applied Intelligence, this episode is worth revisiting because the question is no longer whether we should use AI. The better question is: Which parts of thinking do we still want to keep sharp? Resources and tools: Show resource: Decoded-podcast.com Practical AI prompting techniques and guides: PromptEngineeringCookbook.com Strategic research and insights on AI and digital transformation: Strategen-ai.com Learn more about the podcast and Joel Leslie: https://joelleslie.com.au Executive podcast: DecisionLayer-Podcast.com
S3 · E14
June 10 · 14 min
When AI Enters the Workplace Before the Strategy Does
A special episode from Decoded: The Decision Layer Today, we’re doing something a little different. This episode features a short extract from Decoded: The Decision Layer, the sister show to Decoded: AI for Everyone. Where Decoded: AI for Everyone is designed for curious listeners, professionals and everyday users trying to understand AI clearly, The Decision Layer is built for business leaders, boards and executive teams navigating safe, secure and practical AI adoption inside the enterprise. This extract looks at one of the biggest issues now facing organisations: AI is already entering the workplace before many organisations have a clear strategy for it. It is showing up through approved tools, embedded software, informal use, documents, emails, analysis, customer interactions, workflows and decision support. That creates a simple but important question: "If AI is already acting inside the organisation, who owns the outcome?" In this special episode: Why AI adoption is no longer just a technology issue How approved, embedded and informal AI are entering workplaces Why “light-touch AI” can still create organisational risk What changes when AI moves from assisting people to acting inside workflows Why accountability matters before something goes wrong If you are interested in AI adoption in the workplace, you can find Decoded: The Decision Layer on Spotify, Apple, Amazon and iHeart, or listen direct at DecisionLayer-Podcast.com, where you’ll find supporting resources and executive briefings.
June 5 · 9 min
City Brains, Environmental Modelling & Ethical Governance
Season 2 Rerun What happens when AI starts helping us understand entire cities, environments and systems? This episode explores one of the most practical and far-reaching uses of AI: modelling the world around us. From traffic, housing and infrastructure to climate risk, energy, water, tourism, planning and emergency response, AI is increasingly being used to detect patterns, simulate scenarios and support better decisions at scale. But when AI starts shaping how cities and environments are planned, governed and prioritised, the question is not only what the technology can do. It is who gets to decide what good looks like. In this episode: How AI can support city planning and environmental modelling Why “city brains” are becoming part of future infrastructure How AI can help model complex systems humans struggle to see clearly The risks of bias, exclusion and over-automation in public decision-making Why ethical governance matters when AI is used to shape shared spaces As Decoded: AI for Everyone moves toward Season 4 and Applied Intelligence, this episode is worth revisiting because it shows AI moving beyond chat and into the systems that shape daily life. Roads. Water. Energy. Cities. Climate. Public services. AI is not just changing how we work. It is starting to change how we understand the world we live in. Resources and tools: Show Website: https://decoded-podcast.com/resources Prompts & Tools: PromptEngineeringCookBook.com AI Research: Strategen-AI.com More on Joel: JoelLeslie.com.au
May 24 · 8 min
AI in Workflows: How to Build Your Personal AI Stack
Season 1 Rerun AI becomes far more useful when it stops being “just a chatbot”. The real shift happens when AI becomes part of your workflow. Research. Writing. Planning. Meetings. Analysis. Decision support. Organisation. Automation. More people are building personal AI stacks that combine tools like ChatGPT, Claude, Perplexity, Copilot, Gemini, automation platforms, and AI-assisted workflows into everyday work. This episode revisits one of the strongest-performing episodes in the Decoded catalogue because the conversation around AI has changed. As we no longer ask, "Should I use AI?”, we're continually asking, “How do I actually use it properly?” So, in this episode, we revisit: What a personal AI stack actually is Why different AI tools perform differently How people are combining AI tools into workflows The risks of relying on one tool for everything Why good AI use is becoming a workplace capability As Decoded: AI for Everyone moves towards Season 4 and Applied Intelligence, this episode becomes a bridge between understanding AI and operationalising it. Because the future of AI lies in how the tools work together. Resources and tools: Show Website: Decoded-podcast.com Prompts & Tools: PromptEngineeringCookBook.com AI Research: Strategen-AI.com More on Joel: JoelLeslie.com.au
May 18 · 11 min
AI in Healthcare: The Breakthroughs Already Happening
Season 2 Rerun Some of the biggest AI breakthroughs are not happening in chatbots. They are happening in healthcare. AI is already helping researchers and clinicians: detect disease earlier analyse medical imaging faster accelerate drug discovery model human biology personalise treatment pathways uncover patterns humans would likely miss And some of what comes next sounds almost like science fiction. Regenerative medicine. AI-guided tissue engineering. Personalised therapies. The possibility of bioprinting and organ modelling moving from experimental research toward practical medicine. But this episode is not about hype. It is about understanding what AI is actually changing in healthcare right now, what is still experimental, and why this matters far beyond hospitals and laboratories. In this episode: How AI is reshaping diagnosis and treatment Why protein modelling became such a major breakthrough The role AI is playing in longevity and preventative care What “personalised medicine” may actually look like The difference between genuine breakthroughs and inflated expectations As Decoded: AI for Everyone moves toward Season 4 and Applied Intelligence, this episode revisits one of the most important real-world examples of AI already changing serious systems. Because AI is no longer just helping us search for information. It is increasingly helping us understand the human body itself. Resources and tools: decoded-podcast.com/ joelleslie.com.au PromptEngineeringCookBook.com Strategen-AI.com
May 12 · 7 min
The First Draft Problem: When AI Starts Before You Do
Season 3 Rerun Before we all had AI, the hardest part of many tasks was starting. Now the blank page is disappearing, completely... ChatGPT, Claude, Copilot and other AI tools can instantly generate: drafts plans emails strategies summaries ideas But something important changes when AI becomes the starting point instead of the assistant. This episode explores one of the biggest behavioural shifts in the AI era: what happens when the first version of the work is no longer yours. In this episode: Why AI-generated first drafts feel so powerful How AI subtly shapes direction, tone, confidence, and thinking The hidden risk of accepting the first “good enough” answer Why the first draft is becoming one of the most important decision points in modern work This was one of the strongest-performing episodes of Season 3, and for good reason. Almost everyone using AI today has experienced this shift already. Season 4 of Decoded: AI for Everyone is moving towards Applied Intelligence. Real workflows. Real tools. Real-world use. Before we build better AI habits, we need to understand what happens when AI starts before we do. Show link: https://decoded-podcast.com/
May 6 · 7 min
AI is Already the Default. Are You Choosing How You Use It?
AI Is Already the Default. Are You Choosing How You Use It? (Season 3 Rerun) AI hasn’t taken over in a dramatic way. It’s done something quieter. It's now the default. Search, writing, planning, recommendations, decisions. AI is now sitting inside the tools and systems we use every day. Most of the time, we don’t even notice it. This episode revisits one of the most important shifts from Season 3. Not what AI can do, but what happens when it becomes the starting point. In this episode: Where AI is already shaping your work and decisions How “default use” changes behaviour without you realising The difference between using AI and relying on it Why this matters before you go deeper into tools, workflows, and automation Season 4 is moving into Applied Intelligence. Real use cases. Real workflows. Real outcomes. Before we get there, this is the reset: AI is already part of how you work, the question is whether you’re still choosing how! Resources and tools: Decoded-podcast.com PromptEnineeringCookbook.com Strategen-AI.com JoelLeslie.com.au Noosa-Digital.com
S3 · E13
April 30 · 11 min
Next Gen AI - Bonus Episode
When AI goes further than you intended. Season 3 wrapped last episode, but there was one more idea worth sharing. Something that sits between where we’ve been… and what’s coming next. If you’ve been using AI lately, you’ve probably felt it. It doesn’t really wait anymore. It jumps in, tries to finish things, and suggests what to do next. Sometimes, before you’ve even fully asked. In this bonus episode, we explore a subtle but important shift: AI moving from something that responds… to something that acts. We use real-world examples, from writing and research through to automation. This episode focuses on what this change actually looks like in practice and how to stay in control as AI becomes more proactive. In this episode: How AI is moving from prompts to action Why tools are starting to “go further” than expected How to build a simple AI writing stack using multiple tools How to use deep research properly (not just surface-level answers) How to structure your files and workflows so AI works with you, not over you Where to let AI move fast — and where to stay involved Practical resources from this episode: We’ve included the full tools, prompts, and structures referenced in this episode here: decoded-podcast.com/resources/s3-bonus Including: A ready-to-use Deep Research prompt A simple AI writing stack (ChatGPT, Claude, Perplexity) A folder structure for working safely with AI automation Guidance on keeping control as AI starts to act This episode is also a preview of what’s coming next... Season 4, Applied Intelligence, moves beyond using AI… into working with systems that act. For more tools and practical AI guidance: https://PromptEngineeringCookbook.com https://joelrleslie.substack.com https://strategen-ai.com Decoded: AI for Everyone is a non-technical podcast exploring how artificial intelligence is reshaping work, creativity, decision-making, and trust, and how we can engage with these systems thoughtfully and intentionally.
S3 · E12
April 24 · 8 min
Living With AI
What to keep, what to question, and how to stay in control. AI hasn’t taken over. But it has quietly become part of how we think, decide, create, and work. Throughout Season 3 of Decoded: AI for Everyone, we explored how AI is shifting from something new… to something normal. Not through big, obvious changes, but through everyday habits and defaults. In this final episode, we bring it all together. Not as a recap, but as a practical guide to living with AI intentionally. What to keep, what to question, and what to do next. This episode explores: how AI is shaping behaviour, not just tools the small habits that determine whether AI supports or replaces your thinking when to use AI, and when not to how to maintain your voice, judgement, and agency what “good use” of AI actually looks like in everyday life From writing and research to automation and creativity, this episode translates the season into simple, practical ways you can use AI without losing what matters. Because AI is more than an email finisher or an image generator. It can be a powerful tool in your daily life, at work, at home, or in learning. But like any powerful technology, how you use it matters. The people who benefit most from AI won’t be the ones who use it for everything. They’ll be the ones who use it deliberately. Resources Prompt engineering guides and practical AI tools: https://PromptEngineeringCookbook.com AI platform comparisons and use-case guides: https://PromptEngineeringCookbook.com/ai-platforms-comparison Writing on AI, behaviour, and decision-making: https://joelrleslie.substack.com Strategic AI insights and advisory work: https://strategen-ai.com Learn more about Joel Leslie and the podcast: https://joelleslie.com.au AI executive business partner: Jarvin-ai.com AI learning facilitator: faculty-ai.com Revenue intelligence for golf clubs: yieldgolf.com Cooking to your needs: ⁠cooking-clips.com⁠ Decoded: AI for Everyone is a non-technical podcast exploring how artificial intelligence is reshaping work, creativity, decision-making, and trust, and how we can engage with these systems thoughtfully and intentionally.

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