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Dr Patrick Giwa PhD

@patrickgiwa

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People treat using AI at work like a prompting skill. That is why so many people get poor results from it. The real value comes from knowing where AI fits into your work. Especially in Product. 👇 Most Product Managers repeat the same tasks: Research. Requirements. Prioritisation. Stakeholder updates. Analysis. Decision-making. Each can become a repeatable AI workflow. Here are 6 I’d teach first: 1/ Customer Research Give AI your interviews, surveys or support tickets. Ask it to identify recurring problems, behaviours and needs. 2/ Requirements Give AI the business goal, user problem, constraints and context. Use it to draft requirements and acceptance criteria. 3/ Prioritisation Give AI your ideas, evidence, goals and constraints. Ask it to compare options against your criteria. 4/ Stakeholder Updates Give AI your notes, decisions, risks and next steps. Ask it to create the right update for each audience. 5/ Product Analysis Give AI your data, experiments or research. Ask it to identify patterns and questions worth investigating. 6/ Decision Review Give AI the decision, assumptions, evidence and risks. Ask it to challenge your thinking before you commit. Good AI use rarely starts with a clever prompt. It starts with a repeatable piece of work. Pick one task you do every week. Turn it into a workflow. Then improve it every time you use it. Liam Darmody and I are running a free 1-hour training showing you how to go from using AI as a chatbot to running a small AI team that can help with real work. Reshare to help another Product professional work smarter with AI. Follow @patrickgiwa for more. by @patrickgiwa
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a day ago
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Business Analysis is saturated. But it’s not the only way into tech. 👇 I’m in a community of over 1000 Business Analyst professionals and have mentored over 100 BAs. Here’s what I see. For some reason, everyone thinks Business Analysis is the golden ticket into IT. Yes. It was the case for a long time. But currently, it’s not. It’s just one of many entry points — and right now, it’s crowded. Here are some alternative career paths: 1. Non-Technical Career Paths • Change Manager → Guide people through change and reduce resistance • Product Manager → Lead vision, own outcomes, drive strategy (I chose this path because I love the process of building solutions for user problems.) • Delivery Manager → Like project management, but with actual impact. Keep things moving, unblock teams, ship faster. • AI Consultant → Help businesses use AI without drowning in buzzwords • Data Governance Specialist → If you love structure, standards, and making data usable and safe Technical Career Paths • Cybersecurity Analyst / Consultant → Every breach = a job opportunity. High stakes, high reward • DevOps Engineer → Automate, deploy, repeat. Great for problem-solvers • Cloud Engineer → Design, deploy, and manage infrastructure on AWS, Azure, or GCP. • AIOps Engineer → Use AI to manage IT systems. Still emerging = big potential • Solutions Architect → Design systems that scale. Think technically. Communicate clearly. • Data Analyst / Analytics Consultant → Turn raw data into smart decisions Being a Business Analyst is a skillset, not a final destination. Use it to break in. Then break out. What role are you curious about? Repost to help BAs explore what else is out there + Follow @patrickgiwa for more. by @patrickgiwa
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a day ago
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Nobody cares if you use AI or not. The market rewards results. Some people refuse to use AI because they believe it makes them dumber. Well, those who ignore AI are losing out. Here’s why 👇 1/ Speed matters in our work today → AI helps with the first draft → AI cuts time spent on admin work → AI helps you get to a useful answer faster People notice who gets good work done quickly. 2/ Good people use it to improve their thinking → Good people use AI to test ideas → Spot weak logic → Sharpen their writing → Prepare better before they act AI does not remove judgement. It makes judgement more valuable. 3/ The market rewards output → Faster turnaround → Clearer communication → More capacity → Less time lost on low-value tasks Nobody gets praised for doing everything the long way. Working without AI is like working without search, spreadsheets, or spellcheck. It is not a badge of quality. It is a slower way to do the job. The people pulling ahead are not handing over their brains. They are using AI for the parts that waste time, then using their own judgement where it counts. 🔄 Reshare to help knowledge workers use AI properly + Follow @patrickgiwa for practical AI at work ideas by @patrickgiwa
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2 days ago
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Most careers don’t move in straight lines. But on LinkedIn, it feels like everyone else has it figured out. 👇 Not true! What you don’t see are the quiet detours: • Starting at 30 • Learning Claude • Making a mistake • Restarting after a layoff • Learning tech skills at 45 • Finding confidence slowly • Learning about AI in your thirties • Trying a role that doesn’t fit • Starting again in a new country • Switching paths to learn Claude AI skills • Growing into the job you once felt unqualified for We hide these parts. We tidy up our timelines. We pretend every step was planned. But the truth is simple. Your twists are the reason you grow. Each restart sharpens you. Each setback teaches you what matters. Each pivot expands the path you can walk next. The people moving fastest today aren’t following perfect plans. They’re adapting. They’re stacking skills. They’re turning strange turns into real leverage. Your messy career isn’t holding you back. It’s shaping you. The career detour you thought was a setback might be the exact thing preparing you for what’s next. Own the journey. Follow @patrickgiwa for more by @patrickgiwa
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2 days ago
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I spent 2 years learning AI the hard way. Most of it, I did in the wrong order. I’ve now changed my ways. Here’s the path I’d hand my past self. Ten steps, no shortcuts skipped 👇 1. Pick one tool and go deep. Ignore the rest for a month. At this point, the models are pretty much the same with marginal differences. It’s now like an Apple vs Android debate. The people who try everything learn nothing. 2. Stop collecting just prompts. Learn to give context. Most bad output is a context problem. You can’t go wrong with giving more context. 3. Show it one strong example. Skip the long description. It copies patterns better than it follows instructions. 4. Rebuild one weekly task with AI, end to end. Not ten tasks. One. All the way through. 5. Learn to edit what it gives you. AI writes the draft. Taste is the skill that’s left. 6. Learn to spot AI-slop in your own work. If you can’t catch it, it will out you. 7. Use a fast model to explore, your best one to finish. One model for everything is a beginner move. Some models are great for writing while some are better at building. 8. Build one small agent for work you repeat often. That is where the hours come back. 9. Keep your judgment sharper than your tools. Tools change monthly. Good judgment is your USP. 10. Teach it to someone else. You don’t really know it until you can. At work, your family, your community. Share what you learn. That’s the whole path. Most people are stuck on step 1, hopping tools, wondering why nothing is clicking. Comment PATH and I’ll send you the version with the resources for each step. * Repost to help someone learn AI in the right order + Follow @patrickgiwa for AI-native work insights by @patrickgiwa
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3 days ago
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AI is changing how small businesses run—not someday, but now. Winners who act early will gain clear advantage today!! 👇 I’ve spent years in technology helping teams turn complex problems into digital solutions and systems. I’ve never seen tech shift this fast. Most small businesses still think AI means using ChatGPT to write a few emails. That is only a tiny part of the picture now. AI is starting to change how customers find you, how staff work, how leads are handled, how admin gets done, and how decisions are made. The way your business runs has already started to shift. Most businesses just have not caught up yet. In the next wave of AI adoption, the winners will not be the companies with the biggest budgets. They will be the ones that take early, practical steps. The ones that ask better questions. Where are we losing time? Where are customers waiting too long? Where are staff repeating the same work every week? Where are decisions being made with poor information? AI adoption does not start with buying another tool. It starts with understanding where AI can remove friction without creating risk. For most SMBs, that means looking at five areas. 1. Admin work that slows the team down 2. Customer questions that repeat every day 3. Sales follow-up that gets missed 4. Reporting that takes too long 5. Staff using AI without clear guardrails You do not need to rebuild your whole business. You do need to start mapping where AI can help. Safely. Practically. With a clear link to time, cost, service, or revenue. Because your competitors are not waiting for AI to become perfect. They are learning now, too. They are building confidence now, too. They are finding small wins now, too. And those small wins will become a serious advantage. As a small business, you do not need more AI hype. You need a clear path to adoption. Follow @patrickgiwa for more! by @patrickgiwa
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3 days ago
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Your business does not run on strategy alone. It runs on work (and people) most never stop to notice. 👇 Maybe I notice that more because I’m an immigrant. You get used to seeing what holds things together behind the scenes. The effort that gets missed. The systems people rely on but rarely value properly. The contribution that matters long before it gets recognised. Businesses work the same way. Leaders talk about growth. Teams live inside workflows. And the quality of those workflows shapes performance every day. Think about a normal week: 📥 That shared inbox? A workflow decides whether work moves or waits. 📄 That client onboarding process? A workflow decides whether the experience feels smooth or messy. 📊 That reporting pack? A workflow decides whether people get clarity or spend hours chasing updates. 🧾 That approval chain? A workflow decides whether decisions happen or stall. 🗂 That project handoff? A workflow decides whether the next person can act or starts from confusion. Most of the drag in a business lives here: ↳ repeated admin ↳ unclear ownership ↳ too many handoffs ↳ trapped knowledge ↳ manual checks ↳ workarounds people have normalised This is why so many teams struggle with AI. They jump to the tool before understanding the workflow. But AI becomes valuable when it improves how work actually moves. That means: ↳ identifying the friction ↳ choosing the right use case ↳ fixing a real bottleneck ↳ automating something meaningful ↳ helping the team work better, not just faster A lot of the value in a business sits in places people overlook. I think that is one reason this work matters to me. I know what it means to build, contribute, adapt, and improve things without always being the part people notice first. That is also how real operational improvement works. Quietly at first. Then obviously. Then everyone wonders how they ever worked without it. ♻ Reshare to help more leaders spot hidden workflows ➕ Follow @patrickgiwa for more by @patrickgiwa
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4 days ago
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Most businesses use AI backwards. Start here instead. 👇 I’ve spoken to over 100 business owners and the common mistake I see is simple: They start with the tool instead of the task. There are 10 practical AI use cases at work, and each exists for a specific reason. 1/ Customer service support Use AI to answer common questions, route urgent issues, and help staff reply faster. 2/ Customer follow-up Use AI to draft replies, chase enquiries, and keep people warm when your team is busy. 3/ Meeting support Use AI to prepare agendas, capture actions, and make sure meetings do not vanish into thin air. A national pastime, sadly, and one of my favourite AI use cases. 4/ Writing support Use AI for first drafts of emails, posts, reports, proposals, and customer messages. 5/ Research support Use AI to compare options, find patterns, and turn long documents into useful points. 6/ Sales support Use AI to qualify leads, prepare call notes, and suggest the next best message. 7/ Admin support Use AI to summarise notes, clean up messy information, and turn rough thoughts into clear next steps. 8/ Reporting support Use AI to explain numbers, spot trends, and turn updates into plain English. 9/ Process support Use AI to map repeat tasks, find bottlenecks, and suggest simpler ways to work. 10/ Front desk support Use AI to handle missed calls, reply quickly, book appointments, and pass serious enquiries to a human. If you do not know the job before you use AI, do not be surprised when it feels useless. Use AI for admin, meetings, writing, and research to save time. Use AI for follow-up, sales, and front desk to protect revenue. Use AI for reporting to run the business with more control. Practical AI starts with one question: What work is slow, repeated, or costing money? Start there. ♻ Reshare to help more people use AI properly ➕ Follow @patrickgiwa for more by @patrickgiwa
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4 days ago
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The people who will win with AI won’t be the ones who know the most today. They’ll be the ones who keep learning. 👇 AI changes too quickly to ever reach a point where you can say, “I’ve learnt it all.” Tools are constantly changing. New models are launching every day. New capabilities are being unlocked, changing how we work. In the AI world, something you learned three months ago can become useless today. So I’ve stopped trying to “keep up” with everything. I focus on one simple habit: Learn one useful thing AI can do. Try it on my real work. Keep what works. Repeat. You don’t need to become an AI expert. You need to become someone who never stops learning. The biggest advantage with AI isn’t knowing every tool, model, or feature. It’s building the habit of learning, experimenting, and adapting. Because the people who stay curious will keep finding new ways to use AI. And the people who keep experimenting will keep discovering what actually works for them. You don’t need to master everything. You just need to learn something useful today, apply it to your real work, and keep going. That’s how you build an AI advantage over time. What have you recently learned in AI? Tell me in the comments. Follow @patrickgiwa for more. by @patrickgiwa
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6 days ago
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Most business owners don’t want to master AI. They want to fix missed calls. 👇 The AI industry keeps pushing mastery. Learn prompting. Master the tools. Become an AI expert. But business owners already have a full-time job: Running their business. They don’t want another thing to master. They want solutions that work. Look at every other business tool: ↳ You don’t master accounting software. You want accurate books. ↳ You don’t master your phone system. You want calls answered. ↳ You don’t master your CRM. You want organised customer data. Same with AI. Business owners want: ↳ Missed calls recovered automatically ↳ Follow-ups that happen on time ↳ Admin work that gets done ↳ Customer queries answered properly Not complex prompting workflows. The disconnect is obvious. AI companies sell tool expertise. Businesses buy problem solutions. That’s the shift business owners need to make. Stop trying to become an AI expert. Start looking for AI that just works. The tool should solve your problems. Without becoming one itself. ♻ Reshare to help business owners focus on outcomes ➕ Follow @patrickgiwa for practical AI (no hype) by @patrickgiwa
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7 days ago
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Your team is not confused about AI because they are behind. They are confused because someone is using ChatGPT for everything. 👇 One tool for research, writing, building, planning, and analysis. That is like using a hammer for carpentry, plumbing, and electrical work. It might work. But it will feel messy. AI starts making sense when you stop asking one tool to do everything. Here is the simple version I would give any small business: 🔹 CHATGPT Your daily work assistant Best for → Planning → First drafts → Summarising notes → Thinking through tasks → Connecting ideas Use it when you need everyday work done faster. 🔹 CLAUDE Your builder Best for → Building tools → Creating simple apps → Designing workflows → Agentic processes → Turning ideas into systems Use it when you want to build something practical. 🔹 PERPLEXITY Your research helper Best for → Market research → Competitor checks → Finding sources → Checking facts → Tracking change Use it when you need evidence, not guesses. 🔹 GAMMA Your slide deck helper Best for → Draft decks → Workshop slides → Training material → Internal updates → Visual storytelling Use it when you need a deck quickly. 🔹 GRANOLA Your quiet meeting notes helper Best for → Meeting notes → Action points → Follow ups → Client conversations → Sales calls Personally, I do not like bots joining calls. Every meeting I do has AI taking notes, but I prefer it to be discreet. Participants are always informed. Honourable mentions: 🔸 GEMINI Useful for reading and summarising YouTube videos. 🔸 MICROSOFT COPILOT Worth exploring if your business runs on Outlook, Teams, Word, Excel, and PowerPoint. The mistake is trying to find the “best AI tool”. That is the wrong starting point. The better question is: What job does the business need AI to do? * Admin * Sales * Customer service * Reporting * Meetings * Marketing * Operations * Training Start there. Then pick the tool. One tool will not save your business. But the right tool in the right place can save hours every week. ♻ Reshare to help someone stop wasting time on hype AI tools ➕ Follow @patrickgiwa for more by @patrickgiwa
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8 days ago
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Every resume will list AI fluency as a must-have. These free AI courses (with certificates!) from Google, Microsoft, IBM, Amazon, Anthropic & top universities will get you there 👇 Complete them at your own pace and add the certificates to your LinkedIn profile & CV. These aren’t random YouTube tutorials. They’re from trusted institutions and businesses building the AI. Here’s the full list 👇 1️⃣ IBM — AI for Everyone ↳ Learn AI basics, ethics & Gen AI tools. 2️⃣ University of Helsinki — Elements of AI ↳ Learn what AI is, what it can (and can’t) do, and how to build with it. 3️⃣ University of Maryland — AI & Career Empowerment ↳ Learn how AI is reshaping industries and creating new career paths. 4️⃣ HP — AI for Business Professionals ↳ Explore marketing, operations & prompt engineering use cases. 5️⃣ Google — AI Essentials ↳ Learn to use AI tools to work faster, think smarter & create better. 6️⃣ Amazon — Foundations of Prompt Engineering ↳ Learn to design effective & safe prompts using different techniques. 7️⃣ Anthropic — AI Fluency: Framework & Foundations ↳ Learn how to work responsibly & creatively with AI. 8️⃣ Microsoft — Introduction to Generative AI ↳ Learn Gen AI basics, how it works & how to create content. 9️⃣ LinkedIn Learning — Everyday AI Concepts ↳ Understand key AI concepts and how they apply to everyday work. AI fluency won’t be optional. It will be the new MS Word. Start now, for free. Which one will you start with? ♻️ Repost to help others upskill without going broke. ➕ Follow @patrickgiwa for more by @patrickgiwa
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9 days ago
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