danai's space

This is an article I've been dragging around for far too long, but I finally decided it was time to finish it. When I first started drafting it, I wasn't as experienced as I am today. I was trying to figure out the "perfect recipe" for product discovery and, like most things in product management, I eventually realized there isn't one. Instead, there are principles, techniques, and questions that can help us navigate the uncertainty and increase our chances of building something that actually creates value. This article is primarily for people who are new to product management or are taking their first steps into product discovery. Think of it as a starter package: a practical, high-level framework for moving from a customer problem to an MVP. Teresa Torres , in her book Continuous Discovery Habits: Discover Products that Create Customer Value and Business Value , takes a deep dive into t...

When My AI Products Weren't Taken Seriously  The Lesson That Changed How I Communicate Value 💡 This is a personal story about a time when I felt my products weren't being taken seriously — and what it taught me about product management. For quite some time, I worked as a Product Manager at a technology company, one of the fastest-growing companies in Greece, with global presense. My role was to bring AI products to life for a specific department within the company — products that could improve the customer experience, and ultimately create measurable value for the business . Introducing AI wasn't simply about building and releasing a product. 🚀 There was a lot of education around what AI could do, what the benefits were, how it could support people's work, and, of course, the inevitable conversations around how AI would change the way we work and whether we should be worried about being replaced by it. There was quite a heavy onboarding process in the beginning, and t...

ProductCon London 2026 really nailed it. One of the best conferences I’ve attended — even virtually. I genuinely felt energized and inspired by the talks. Still digesting everything. Here’s what really stayed with me: The importance of human-in-the-loop in AI systems to build trust. Ashley Nutter framed this in a practical way—clarifying when humans step in, what their role is, and what happens after they intervene. How PMs can inspire truly autonomous teams even without formal authority . Nilan Peiris was a strong reminder that real impact comes from influence, clarity, and trust — not title. The idea that ChatGPT is the product manager your customers are already talking to — the “shadow PM” who understands their pain points. Pavel Fabrikantov’s point about AI discoverability really made me rethink a few things. The shift of product managers toward becoming builders, and the need for real frameworks to drive AI-native transformation . Great perspective from Carlos...

Story time! The other day I was chatting with some friends. Most of them graduated from Computer Science. Somewhere in the discussion, a misunderstanding came up around what a product manager / product owner does compared to a project manager . That opened a can of questions. Who is more important? Why don’t we see many product roles advertised in Greek companies? And honestly—yes, product jobs are not exactly flooding LinkedIn. 💣Cue a déjà vu moment . It felt exactly like explaining my job to my mum. But it also triggered a realization: the Greek ecosystem is still not very familiar with the product role. Project management is the more traditional one. It’s been around for a long time, and for good reasons. Fair enough—let’s take it step by step. I’ve been lucky enough to work in environments that clearly differentiate the two roles, so I’ll share how I personally see it. Let’s cut to the chase, keeping things a bit abstract. For me—trying not to be biased as a product pe...

Feeling stuck? Not sure what you should work on next? Is it time to build your product roadmap, but you only have a few eggs in one basket? Ok, I got you. We are product people, and our job is simple (but not easy): solve customer problems . The real question is—how do you reliably identify those problems? There’s one place you should always start. Customer Support.🙌 They know your customers better than anyone else. They talk to them every single day. They hear the frustrations, the confusion, the anger, and the unmet expectations. Go sit with them. Talk to them. And most importantly, get access to their support tickets or complaints database. That’s the Holy Grail .💥 There’s nothing more valuable than a well-maintained complaints database. From Manual Pain to AI Superpower Back in the day—before large language models were widely available—you had to manually go through this data. Teams relied on N...

On Friday 19/12/2025, I was invited to a university workshop at the Computer Science Department of the Aristotle University of Thessaloniki to talk about what a Product Manager / Product Owner does and to share the key aspects of product management. The goal was simple: to inspire students by introducing them to career paths they might pursue in the future. I truly love workshops. I love the energy, the passion, and the interaction with people. I also deeply enjoy creating presentation decks (confession time: it’s my guilty pleasure 😄). 😮 Key realization: These students were in their third year of studies , yet they were not really familiar with how an AI model is built. Given that, we decided to start from scratch. I mainly focused on real-world examples of AI-powered products that were already familiar to them, using those as an entry point to discuss product thinking, user needs, and business impact. 👉 What do you think? Should students...

This is a more personal article, aiming to share my journey toward becoming a product professional. I hope you find it inspiring. Let’s start!😉 From my early days at university, I was good at organizing initiatives and managing projects. Whenever I was assigned to something, I truly owned it. I felt a strong sense of responsibility and took care of it until I saw it take off. Still, I wasn’t sure I had found my true calling. I thought project management might be a good fit, but I first wanted to experience working on projects and large initiatives before jumping into organizing them. I started my career while still pursuing my Bachelor’s degree in Computer Science. Early on, I was mainly involved in web development and system administration, a period that lasted around two to three years. During that time, I worked mostly in very small companies, trying to figure out who I was profe...

One of the toughest moments is when you have to kill your product 💀—when you see that your product is failing.  In this article, I am sharing my piece of advice about reading early on the signs, potential challenges that I have encountered in the AI product development, and last but not least, mitigation strategies! 🔎 Reading the signs A few signs that indicate your product should be removed from the market: Low performance in primary KPIs:  Measuring performance from day one is crucial, especially if your product is costly. When ROI is significantly low and your initial impact estimates are far off—for example, when technical costs are much higher than the value the product brings back to the company—it’s a strong indicator that the product isn’t viable. Post release analysis is absolutely necessary to indentify potential improvements before deciding to retire the product. The company is changing direction: Strategic decisions beyond your control can influence the sur...

AI products require deep analysis at many stages — from opportunity assessment to post-rollout meta-analysis. In this article, I’ll share my personal experience on navigating the analytical complexity of product development and collaborating effectively with data teams. 💣 Here Comes the Challenge What happens when the data science team supporting you needs to answer open-ended questions and extract insights without clear guidance? What happens when you have to go through a dozen reports to get the full picture? What is the role of the Product person there? What happens when the team keeps analyzing and analyzing without ever reaching a conclusion? How do we balance the need for rigor with the need for decisions and action? And what if the analysis yields inconclusive results? 👩 From Data Science to Product Throughout my career, I’ve received analyses from many different perspectives — and earlier, I used to prepare and deliver them myself. I’ve worked with aca...

What I enjoy most about the role of a Product Owner is product discovery. Many of these sessions have ended in failure 😓—but looking back, I now see those failures as invaluable. Connecting the dots helped me realize that each misstep carried a lesson. Out of these experiences, I’d like to share the most common mistakes I made (and I believe many newbies do too). Leading by example in reverse !  💀 Using discovery sessions for validation: Let me explain by using a story.  When I go to yoga, my lovely instructor always says "Use your mind like a beginner. Approach each position as if you’re experiencing it for the first time." . In Greek it's called the αρχάριος νους. Αccording to  Shunryu Suzuki: In the beginner's mind there are many possibilities, but in the expert's mind there are few. I try to bring this principle into discovery sessions today—but it wasn’t always the case. In my early days, I’d tal...