Category: Product Management
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Machine Learning in Production? What This Really Means
Machine Learning in Production? What This Really Means From notebooks to real-world systems The post Machine Learning in Production? What This Really Means appeared first on Towards Data Science. Sabrine Bendimerad Go to original source
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Why SaaS Product Management Is the Best Domain for Data-Driven Professionals in 2026
Why SaaS Product Management Is the Best Domain for Data-Driven Professionals in 2026 How I use analytics, automation, and AI to build better SaaS The post Why SaaS Product Management Is the Best Domain for Data-Driven Professionals in 2026 appeared first on Towards Data Science. Yassin Zehar Go to original source
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Understanding the Generative AI User
Understanding the Generative AI User What do regular technology users think (and know) about AI? The post Understanding the Generative AI User appeared first on Towards Data Science. Stephanie Kirmer Go to original source
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How to Develop AI-Powered Solutions, Accelerated by AI
How to Develop AI-Powered Solutions, Accelerated by AI From idea to impact : using AI as your accelerating copilot The post How to Develop AI-Powered Solutions, Accelerated by AI appeared first on Towards Data Science. Anna Via Go to original source
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A Product Data Scientist’s Take on LinkedIn Games After 500 Days of Play
A Product Data Scientist’s Take on LinkedIn Games After 500 Days of Play What a simple puzzle game reveals about experimentation, product thinking, and data science The post A Product Data Scientist’s Take on LinkedIn Games After 500 Days of Play appeared first on Towards Data Science. Yu Dong Go to original source
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The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation
The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation How product, growth and engineering teams can converge on a single signal for better incident management The post The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation appeared first on…
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Expected Value Analysis in AI Product Management
Expected Value Analysis in AI Product Management An introduction to key concepts and practical applications The post Expected Value Analysis in AI Product Management appeared first on Towards Data Science. Chinmay Kakatkar Go to original source
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It Doesn’t Need to Be a Chatbot
It Doesn’t Need to Be a Chatbot A more organic, incremental approach to integrating AI into existing products The post It Doesn’t Need to Be a Chatbot appeared first on Towards Data Science. Dr. Janna Lipenkova Go to original source
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What Clients Really Ask for in AI Projects
What Clients Really Ask for in AI Projects Managing AI projects is no walk in the park, but you have the power to make it easier for everyone The post What Clients Really Ask for in AI Projects appeared first on Towards Data Science. Ivo Bernardo Go to original source
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Data Mesh Diaries: Realities from Early Adopters
Data Mesh Diaries: Realities from Early Adopters Early-adopter realities gathered from real data mesh implementations The post Data Mesh Diaries: Realities from Early Adopters appeared first on Towards Data Science. Corné POTGIETER Go to original source
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Tips for Setting Expectations in AI Projects
Tips for Setting Expectations in AI Projects If you want your AI project to succeed, mastering expectation management comes first. When working with AI projets, uncertainty isn’t just a side effect, it can make or break the entire initiative. Most people impacted by AI projects don’t fully understand how AI works, or that errors are…
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The Stanford Framework That Turns AI into Your PM Superpower
The Stanford Framework That Turns AI into Your PM Superpower A human-centric guide to AI automation for product managers. The post The Stanford Framework That Turns AI into Your PM Superpower appeared first on Towards Data Science. Rahul Vir Go to original source
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The Mythical Pivot Point from Buy to Build for Data Platforms
The Mythical Pivot Point from Buy to Build for Data Platforms For companies with data-intensive architectures, there often comes a pivotal point where building in-house data platforms makes more sense than buying off-the-shelf solutions The post The Mythical Pivot Point from Buy to Build for Data Platforms appeared first on Towards Data Science. Ming Gao…
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Stop Chasing “Efficiency AI.” The Real Value Is in “Opportunity AI.”
Stop Chasing “Efficiency AI.” The Real Value Is in “Opportunity AI.” Companies pursuing incremental productivity gains risk being displaced by AI-native competitors building entirely new business models The post Stop Chasing “Efficiency AI.” The Real Value Is in “Opportunity AI.” appeared first on Towards Data Science. Shreshth Sharma Go to original source
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Why AI Projects Fail
Why AI Projects Fail No one agrees on the exact number, but estimates say anywhere from 50% to 80% of AI projects end in failure. The post Why AI Projects Fail appeared first on Towards Data Science. Ivo Bernardo Go to original source
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Gaining Strategic Clarity in AI
Gaining Strategic Clarity in AI Introducing the AI strategy playbook The post Gaining Strategic Clarity in AI appeared first on Towards Data Science. Dr. Janna Lipenkova Go to original source
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Enterprise AI: From Build-or-Buy to Partner-and-Grow
Enterprise AI: From Build-or-Buy to Partner-and-Grow Not long ago, a cooperation partner casually approached me with an AI use case at their organization. They wanted to make their onboarding process for new staff more efficient by using AI to answer the repetitive questions of newcomers. I suggested a practical chat approach that would integrate their…