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Showing posts from September, 2025

AI as Product Manager's Copilot - Workshop Slides

 AI-enabled tools have proven effective in some areas, but when it comes to the actual Product Management work product,  where creativity and authenticity matter , using AI becomes more challenging. To explore this further, I ran an experiment to answer a simple question: Can I delegate (automate) at least 30% of my PM work to AI? I documented the outcomes in a blog pos t and later shared them in a workshop with fellow PMs. The slides below are exported directly from the Miro board I used for that session.  👉 Read the full blog post here: How I Tried Delegating My Product Work to AI Link to Download 

Product Helmsmanship (P1): Balancing Strategy, Execution, and the Storms in Between

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Product Management often feels like steering a ship through unpredictable seas. Over my career, I’ve learned when to grip the wheel and dive into execution, when to step back and chart the strategic course, when to find that sweet spot in between, and when to simply hand the helm to the crew and trust them to steer. I call this balance Product Helmsmanship . The Origin Story When I first stepped into tech, I started from the lower decks. I began in execution, first as a developer writing code since I was 12, then as a Business Analyst turning requirements into documents and diagrams right after university, and later as a Project Manager focused on delivery. The transition into Product Management felt natural , but in the early years my role often felt like translation, helping business leaders and technical teams understand one another, sometimes mapping business requirements to technical jargon and vice versa. Over time, I realised Product Management is less about translating and ...

[Unpolished] When your perfect user stories are not so much perfect after all

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I spent hours and hours a few weeks back crafting a perfect playbook for user story creation, then got my AI co-pilot to create perfect user stories. They were INVEST, criticised by an Agile Coach role, and written with so much detail that there was no ambiguity in them. Crystal clear. I was so proud of them. It turns out, they were not perfect after all. In our retro yesterday, we discussed them. They had extra details, and the team needed to spend more time reading them. Having requirements (functional, non-functional, assumptions, and design) broken down into different sections also made it hard for QA to create and link test cases. The team wanted something simple. Simple is what they get. At the end of the day, the format of a user story does not matter. It is the outcome that matters. I spent a few hours and simplified some of the user stories. Next step: I will simplify the playbook for the AI copilot to create simpler and imperfect user stories from now on. [Unpolished] po...

We Are Only Human After All

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Earlier this month, I spent a few days creating a workshop on AI as Copilot for Product Managers. The feedback was positive, so I invested another couple of days turning the content into a comprehensive blog post. I was pleased with the result and genuinely believed it could be useful for others new to this space. I finished writing around 2:00 AM on Saturday and decided to schedule it for auto-publishing on LinkedIn on Monday, 8 September. Then Father’s Day happened. As a proud dad, I shared a casual photo of my gifts on Instagram along with a dad joke about ROI (Return on Investment). When my daughter asked what ROI meant, I realised my professional humour might not land everywhere, so I quickly adapted the post for LinkedIn in just five minutes, just for fun. On Monday morning, after a sleepless night with a sick child, I completely forgot about the scheduled post. As a result, the two posts went live only a day apart. The outcome? The LinkedIn version of the Father’s Day post not...

The PM’s Copilot: Reclaiming Time with AI

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Like many PMs, I didn’t really trust AI for serious product work. I mostly used it for general purposes: polishing emails and notes, drafting messages and creating images from time to time. I used AI in a project only as a second opinion and to validate my discovery work, but that was it. For more on that check my earlier  blog post . While AI felt adequate for technical tasks or copywriting, it didn’t feel reliable for the messy, ambiguous world of product management where curiosity, judgement, and breaking patterns matter most. Then everything shifted. Here is my experience report.