The Digital Dominance Podcast

Anoop Suresh

The Digital Dominance Podcast is your go-to show for mastering digital marketing and product marketing. Hosted by industry veterans, we dive deep into the latest strategies, trends, and tools that drive growth, brand awareness, and customer engagement. Whether you’re a marketer, entrepreneur, or product leader, each episode brings actionable insights on SEO, paid media, content marketing, growth hacking, and go-to-market strategies. Tune in to stay ahead of the curve and dominate the digital landscape!

  1. AI for Product Managers: Foundations You Must Understand (No Coding Required)

    JAN 6

    AI for Product Managers: Foundations You Must Understand (No Coding Required)

    AI is no longer a future bet. It’s already shaping search, recommendations, support, pricing, and content across products we use every day. The mistake many PMs make is thinking they need to become data scientists. They don’t. What they do need is a clear mental model of how AI creates value and where it can fail. Here’s the foundation every product manager should have 👇 1. AI vs Machine Learning Artificial Intelligence is the broader goal: systems that simulate human intelligence. Machine Learning is one of the main ways we get there by training models on data instead of hard-coding rules. Think: AI is the destination. ML is the engine. 2. The core AI workflow Every AI product follows the same loop: Data → Model → Prediction → User Impact If you can’t clearly explain how your data turns into user value, your AI feature is still a demo. 3. Training vs inference Training is where models learn from historical data. It’s slow, expensive, and mostly invisible. Inference is where models make predictions on new inputs. That’s what users experience. PMs need to care about both, even if users only see one. 4. NLP and Computer Vision NLP enables products to understand and generate language: summarization, chat, ticket routing, sentiment. Computer Vision allows systems to interpret images and video: OCR, object detection, photo enhancement. These capabilities are now table stakes in many products. 5. Generative AI changes product design Generative models don’t return a single “right” answer. They produce probabilistic outputs. This means UX, trust, evaluation, and guardrails matter more than ever. Designing for uncertainty is now a core PM skill. 6. Data matters more than models Most AI effort goes into data collection, labeling, cleaning, and maintenance. Strong data beats sophisticated models every time. 7. Why AI initiatives fail Not because the model is bad. But due to fragmented data, unrealistic expectations, missing talent, and poor product framing. The PM’s real role in AI Define the right problem. Understand data constraints. Translate model outputs into user value. Set realistic expectations. Build trust into the experience. You don’t need to code to lead AI products well. You need strong foundations and clear thinking. #ArtificialIntelligence #MachineLearning #ProductManagement #AIProductManagement #GenerativeAI #TechLeadership #ProductStrategy #DataDriven #PMInsights

    11 min
  2. Feature-by-Release Roadmaps Done Right

    12/10/2025

    Feature-by-Release Roadmaps Done Right

    Most roadmaps drown teams in dates, assumptions, and wishful thinking. A Feature-by-Release roadmap takes a different route. It gives structure, predictability, and a realistic view of what’s coming without pretending every detail is locked in stone. In B2B environments, where customers depend on timelines to plan their own workflows, this format works especially well. It tells stakeholders what to expect, why it matters, and how releases connect to business goals. The heart of a Feature-by-Release roadmap is simple. Each release groups a set of meaningful customer outcomes. No clutter. No noise. Just a clear picture of progress. It also forces alignment. When engineering, marketing, design, sales, and support see the upcoming releases mapped in this way, they understand what’s coming and prepare accordingly. Marketing can shape messaging, sales can position upcoming value, customer teams can forecast questions, and engineering can sequence work with fewer surprises. This format keeps priorities honest. When you plan by release instead of endless backlogs, tough decisions surface early. You can’t hide low-impact features. You can’t push everything as “high priority.” The roadmap becomes a truth-telling tool instead of a political battlefield. Another advantage: it’s easier for customers and executives to absorb. Releases are familiar. They reflect how users experience the product. They also let you frame progress as a series of value drops instead of one giant undefined future. Just remember, even this structure needs flexibility. Market shifts, customer feedback, and experiments may reshape releases. That’s fine. A Feature-by-Release roadmap guides you without freezing your strategy. When you build it well, you get faster alignment, clearer communication, a calmer engineering team, stronger stakeholder trust, and a product narrative that makes sense to both internal teams and external buyers. A roadmap isn’t a contract. It’s a communication tool. Feature-by-Release is the format that keeps teams moving together.

    14 min

About

The Digital Dominance Podcast is your go-to show for mastering digital marketing and product marketing. Hosted by industry veterans, we dive deep into the latest strategies, trends, and tools that drive growth, brand awareness, and customer engagement. Whether you’re a marketer, entrepreneur, or product leader, each episode brings actionable insights on SEO, paid media, content marketing, growth hacking, and go-to-market strategies. Tune in to stay ahead of the curve and dominate the digital landscape!