The Next Release

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...

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.