Tech Skills in High Demand Right Now

Product Management is not about: - Asking customers about the requirements. - Writing detailed specifications. - Creating prototypes and wireframes. - Assigning tasks to developers. - Verifying and accepting the work of others. - Obsessing over velocity, deadlines, and roadmaps. - Mastering Scrum or any other framework to perfection. - Acting like the CEO of the product. Anyone can do that. It’s about: - Understanding customers' problems, needs, and desires. - Understanding the market and the business in depth. - Collaborating closely with engineers and designers. - Identifying opportunities, finding solutions, and tackling the risks together. - Marrying customer goals and business goals. - Influencing others to work toward the common goal. - Being humble (it’s okay not to be the smartest person in the room). - Experimenting to test assumptions. - Leading without authority. - Turning chaos into clarity. Start with these questions: - Why are we building this thing? - Why are we building it now? - Who are we building it for? - What is unique about our product? - How is it aligned with the company's vision? - How is it aligned with the company's strategy? - What does success look like? How can we measure it? - What are the customers' needs/jobs? - How will it affect our customers and users? - How will it create value for the business? - Can we buy it instead of building it? - How can we ensure our customers will love it? - Will our customers know how to use it? - Can our business support it (e.g., legal, finances)? - Is it feasible? Can we build it with existing technology? - How can we bring it to market? - Do we have the required channels? - Should we do it at all? Are there any ethical considerations? - What are the riskiest assumptions? How can we test them? - What does the data tell us? - How can we get maximum validating learning with minimum effort? - What else can go wrong? Be curious. Learn and experiment. Question solutions and push back on things handed down. Remember that product management is about creating a "product customers love, yet also works for our business" (Marty Cagan, Inspired), not about pleasing stakeholders. After 10 years, I’m still learning daily and don’t know everything, but I’m happy to offer my perspective on any questions you have. Drop them below. --- P.S. Enjoy this? Here you can get 600+ free PM learning resources (courses, templates, books): https://lnkd.in/evvCX2wn

Product Managers: Stop trying to prove you’re the most technical person in the room. Do this instead. Listen - you weren’t hired to write code. You were hired to lead. The fastest way to dilute your impact is by trying to match your engineers on technical depth instead of leaning into your actual superpower: clarity, strategy, and customer obsession. Here’s what actually moves the needle: 1. Know your customer inside and out. Not just their problems—but their aspirations, fears, and daily tradeoffs. 2. Craft a compelling narrative and strategy. A vision without clarity is just noise. Great PMs align people through story and focus. 3. Understand enough technical depth to earn respect, not to build the thing yourself. Your job is to ask the right questions, not answer all of them. 4. Be the decision-making engine. Create a space where smart people make smart decisions—fast. And when they are stuck, you make the decision for them. 5. Ask the “dumb” question. “Can you translate that into plain English?” is often the bravest, most powerful thing in the room. The best product managers I know don’t try to be engineers. They respect the craft—and build trust by doing what engineers need most: clearing ambiguity and setting a compelling direction. Remember: if you’re feeling the pressure to out-tech the tech team, stop. Instead, manage the product. Shape the story. Lead the room.

The role of product management, especially for AI-based products, is changing a lot. Interestingly, a significant number of products are becoming "AI-based" products. You'll often see requests for a stronger technical background alongside traditional PM skills. It's not enough to just know the market and users anymore; product managers now need to understand things like algorithms, data pipelines, and machine learning. This isn't a small change; it's a real shift in what's required. It’s not about knowledge of a toll but the technology. I'm seeing this trend firsthand. Look at product manager job descriptions, and "understanding or working knowledge of AI" is becoming standard. We're also seeing more data scientists and AI engineers moving into product management. This isn't just a career switch; it's a sign that technical knowledge is crucial for building good AI products. For people without this background, it's a big challenge, requiring a lot of learning and a willingness to try new things. Being able to explain complex technical ideas in a way that users understand is now a must-have skill. The key to AI product management is balancing big ideas with what's actually possible. Without understanding AI's strengths and limitations, product managers can easily get swayed by marketing hype or struggle to create realistic roadmaps. It's the difference between a dream and a practical vision. Equally important is building strong communication with engineering teams, not just for technical alignment but for building trust. Don't believe the idea that you don't need technical skills in PM. This trend is only going to get stronger. It's better to adapt and learn than to struggle later. #ExperienceFromTheField #WrittenByHuman

Product tools have changed, but the core product skillsets remain the same: 1. HYPOTHESIS TESTING: Defining a clear hypothesis, designing good experiments to test it, interpreting the test results, looping learnings into product strategy... data-driven product teams were always doing this. Vibe-coding has made it possible for product teams to run more tests faster and more independently, but the science (and math) of hypothesis testing is still the same. 2. CUSTOMER DATA & RELATIONSHIPS: Product demos, sales partnerships, feedback conversations, thought partnering with customers, running deep qualitative and quantitative data analysis... never been more important. When you can make a thousand things, knowing what's the right one for your specific business and customer is the only moat that matters for product teams. 3. PRODUCT QUALITY: Testing is archaic, a realm from the era of deterministic software. Almost every tech company's software is now non-deterministic. Quality IS the product. And there is no way to quantify quality, if there ever was. It's in the hands of AI, your job is to know what quality means to your product. And then articulate it clearly. 4. WRITING AND COMMUNICATING: Knowing how to write well precedes writing good evals. Knowing how to listen well precedes good context gathering. Instead of learning how to do prompt engineering, learn how to write good evals and how to engineer good context. You don't need to learn any new tools to do this. The language is English. Write well, listen well, organise well. Context and prompt engineering will follow. 5. ANALYSIS: Core to everything. Knowing when it's a problem worth solving and how much. Knowing how to see what happened. Knowing what's the takeaway and feeding those takeaways into your next steps. Knowing how to deal with conflict. Knowing how to balance tradeoffs. The job was always analysis. More so now.

It's easy to forget fundamentals of product management while chasing AI outcomes. Experience is handling the latter, while keeping the prior intact. These fundamentals didn't come easy. We earned them through years of talking to frustrated users, shipping features that flopped, and slowly learning what actually matters. Don't throw that away just because AI is the new shiny thing. Understanding customer problems still remains the biggest skill of a product manager. Nothing beats that. And this isn't something you learn from a course. While data has always been my primary go-to, it's actually customer empathy that struck gold. That gut feeling when something's off in a user interview, knowing which complaint is the real pain point that took years to develop. And that's something I've always found AI to be lacking at. So till the day we haven't created a bot that makes people feel interested, excited or comfortable about sharing their experiences, product management as a role will hold heavyweight importance in building truly fantastic products. They're what separate us from anyone who can just write a prompt. #productmanagement #ai

AI didn’t just change how we build -  it changed what we need to build. What once required months of work and a team of engineers now takes hours and a few prompts. The cost of building has collapsed. But here’s the real question:  Does anyone actually need what you're building? As AI democratizes speed and scale, the real differentiator isn't velocity -  it's clarity. Knowing what to build, when, and why. These are the skills product managers and product leaders need to double down on: 1.  Financial & Market Fluency Understand the levers your customers care about. What are they solving for 𝘳𝘪𝘨𝘩𝘵 𝘯𝘰𝘸? How are macro shifts reshaping the problem space?     2. Discovery Mastery Dig deeper than feature requests. See the unspoken needs. Ask better questions and connect the dots others miss.     3. Hypothesis-Driven Mindset AI tools make testing faster and cheaper — use them. Explore bold bets without overcommitting. Ship learning, not just features.     4.  Strategic Prioritization Just because you 𝘤𝘢𝘯 build something doesn’t mean you should. Tie product bets to long-term outcomes. For platform PMs, that includes balancing internal vs. ecosystem value.     5. Relationship Building Talk to customers. Align with stakeholders. Influence across functions. Empathy and trust are still your sharpest tools.     6. Storytelling Your ability to shape a vision, influence decisions, and rally teams depends on how well you tell the story — especially in a world flooded with noise. In a recent mentoring session, someone asked me: “With AI evolving so fast, how do I stay relevant as a PM?” This is how. Use AI to accelerate execution -  but build your edge in the skills AI can’t replace. 👇 Which of these are you investing in this year? What else belongs on this list? #ProductLeadership #ProductStrategy #ProductManagement #AI #PlatformProducts #

"Technical" Product Manager ≠ Code Let’s get this straight: Technical doesn’t mean you write code. Every company has its own definition of what "technical" means in product management — and many get it wrong. To me, being a Technical Product Manager means this: 🧠 You understand the tech well enough to talk about scalability, performance, and cost trade-offs with engineers. 🗣️ You translate that tech language into business outcomes for stakeholders. 🔁 You become the bridge — not the bottleneck — between engineering and business. Here’s what that looks like in real life: 🎯 From Engineering → Business 👨💻 “We need to break this monolith into microservices to reduce deployment risk and improve observability.” 📈 PM says to business: “By decoupling the system, we can ship features faster with fewer outages — this supports your quarterly release targets and improves uptime during peak.” 🚚 From Business → Engineering 💼 “Our international customers are abandoning carts due to delayed shipping estimates.” 💻 PM to engineers: “Let’s prioritize integrating real-time carrier APIs or improve caching logic for geo-specific inventory visibility.” See the difference? It's not about the jargon. It's about the impact. And if you're fluent in both tech and business — you’re not just technical. You’re valuable. #TechnicalProductManager #ProductLeadership #Scalability #CrossFunctional #PMMindset #EngineeringExcellence #BusinessImpact

Want to become a Product Manager in 2026, but don’t know where to start? Most people think Product Managers write requirements or manage sprints. But the real role of a PM is much bigger. A Product Manager’s job is to find the right problems, align teams, make smart decisions, and drive measurable product impact - not just manage tasks, but own outcomes. This roadmap breaks down the complete step-by-step journey to becoming a job-ready PM, from building product thinking to mastering execution and strategy. Here’s what you’ll learn: ✅ How PMs balance Users, Business, and Technology to make clear product decisions ✅ The 6 core skill pillars every PM must master - product thinking, research, execution, communication, data, and strategy ✅ How to frame problems correctly (the skill most aspiring PMs miss) ✅ Discovery frameworks to decide what’s worth building ✅ Prioritization methods used by real product teams (RICE, MoSCoW, Kano) ✅ Writing PRDs that guide execution - not just documents ✅ Using data, analytics, and experimentation to validate decisions ✅ Stakeholder management and execution skills that keep teams aligned ✅ Building a strong PM portfolio that proves real capability The roadmap also includes a practical 4-month learning path designed to take you from fundamentals → portfolio → interview readiness. 💡 Product Management isn’t about building features. It’s about building the right product, the right way - for real impact. Save this roadmap if you’re planning to transition into Product Management or level up your product skills in 2026.

Product Management Skills Are Perishable. Treat Them That Way. Product management is a craft. And like any craft, the skills are perishable. Sometimes they go stale because of company culture. You stop talking to customers. Roadmaps become executive opinions. Delivery replaces discovery. You still have the title, but the muscle atrophies. Sometimes they go stale as you climb the ladder. You spend more time in decks, forecasts, and escalations. You approve work instead of shaping it. You are further from the craft, and over time, it shows. None of this makes you a bad product leader. It makes you human. The risk is pretending it is not happening. If you want to keep your product skills sharp, regardless of level, a few practices matter. • Stay close to real customers. Not through summaries or secondhand notes. Sit in on interviews. Listen to calls. Read raw feedback. • Periodically go hands-on. Write a problem statement. Pressure test a hypothesis. Review discovery artifacts. You do not need to own it, but you do need to feel it. • Surround yourself with strong product thinkers. If you are the most product-savvy person in the room, that is a warning sign. • Teach the craft. Mentoring forces clarity. If you cannot explain good product thinking simply, your own understanding may be fading. • Be honest about your environment. Some cultures reward delivery theater over product judgment. Staying too long will cost you skills you worked hard to build. Product management rewards curiosity, tension, and constant learning. When those disappear, skills decay quietly. Treat your product skills like a living asset. Invest in them deliberately, especially as your title grows.

𝗜𝗳 𝗜 𝘄𝗲𝗿𝗲 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗺𝘆 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗰𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟲, 𝗜'𝗱 𝗶𝗴𝗻𝗼𝗿𝗲 𝗺𝗼𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗔𝗜 𝗵𝘆𝗽𝗲. I wouldn't chase every new model, framework, or viral tool. 𝗜'𝗱 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝘁𝗵𝗿𝗲𝗲 𝘀𝗸𝗶𝗹𝗹𝘀 𝘁𝗵𝗮𝘁 𝘄𝗶𝗹𝗹 𝘀𝘁𝗶𝗹𝗹 𝗺𝗮𝘁𝘁𝗲𝗿 𝘆𝗲𝗮𝗿𝘀 𝗳𝗿𝗼𝗺 𝗻𝗼𝘄. 𝟭. 𝗣𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 + 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗗𝗲𝘀𝗶𝗴𝗻 Prompting isn't about finding the perfect prompt. It's about designing workflows. * Break vague problems into structured tasks. * Define clear context, constraints, and success criteria. * Chain AI into repeatable workflows: 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 → 𝗦𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗲 → 𝗗𝗿𝗮𝗳𝘁 → 𝗖𝗿𝗶𝘁𝗶𝗾𝘂𝗲 → 𝗥𝗲𝗳𝗶𝗻𝗲. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲: Less time creating documents. More time making product decisions. 𝟮. 𝗗𝗮𝘁𝗮 & 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝗟𝗶𝘁𝗲𝗿𝗮𝗰𝘆 You don't need to become an ML engineer. But you do need to know whether your AI feature is actually creating value. 𝗟𝗲𝗮𝗿𝗻 𝘁𝗼: * Understand datasets and ground truth. * Interpret metrics like precision, recall, MAE, and latency. * Design practical evaluations using golden datasets, A/B tests, and before-vs-after comparisons. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲: You ship with evidence—not assumptions—and build trust with your stakeholders. 𝟯. 𝗗𝗲𝗲𝗽 𝗗𝗼𝗺𝗮𝗶𝗻 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 AI is a multiplier. Your domain knowledge determines what it multiplies. Go deep in one problem space. Learn the workflows, KPIs, edge cases, and failure modes that matter. Speak your customers' language better than anyone else. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲: Better product decisions. Better prioritization. Better long-term career opportunities. 𝗜𝗳 𝗜 𝗵𝗮𝗱 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝟲–𝟭𝟮 𝗺𝗼𝗻𝘁𝗵𝘀 𝘁𝗼 𝗽𝗿𝗲𝗽𝗮𝗿𝗲 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁... 𝗜'𝗱 𝗶𝗻𝘃𝗲𝘀𝘁 𝗶𝗻 𝘁𝗵𝗲𝘀𝗲 𝘁𝗵𝗿𝗲𝗲 𝘀𝗸𝗶𝗹𝗹𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮𝗻𝘆𝘁𝗵𝗶𝗻𝗴 𝗲𝗹𝘀𝗲. Everything else changes. These compound.