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Product Management for AI

O'Reilly on Data

A couple of years ago, Pete Skomoroch, Roger Magoulas, and I talked about the problems of being a product manager for an AI product. These articles show you how to minimize your risk at every stage of the project, from initial planning through to post-deployment monitoring and testing. Product Management for AI.

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DataOps: Managing the Process and Technology

David Menninger's Analyst Perspectives

The result was battle-tested integrations that could withstand the test of time. Organizations needed to make sure those processes were completed successfully—and reliably—so they had the data necessary to make informed business decisions.

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Beyond “Prompt and Pray”

O'Reilly on Data

Instead of having LLMs make runtime decisions about business logic, use them to help create robust, reusable workflows that can be tested, versioned, and maintained like traditional software. By predefined, tested workflows, we mean creating workflows during the design phase, using AI to assist with ideas and patterns.

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Practical Skills for The AI Product Manager

O'Reilly on Data

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.

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When Life Gives You Lemons Make PM Lemonade: Surviving Product Management During Crisis

Speaker: Vivek Bedi, Keynote Speaker, Author & Entrepreneur

In fact, the entire way product managers work has completely changed. The work/life balance of PMs is being tested; managing a product team and various roadmaps virtually adds to the list of current challenges. Meanwhile many professionals are exploring if pivoting into product management is a career path for them.

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AI Product Management After Deployment

O'Reilly on Data

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed. Debugging AI Products.

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Data Observability and Data Quality Testing Certification Series

DataKitchen

Data Observability and Data Quality Testing Certification Series We are excited to invite you to a free four-part webinar series that will elevate your understanding and skills in Data Observation and Data Quality Testing. Reserve Your Spot! Don’t miss this opportunity to transform your data practices.

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Revolutionize QA: GAPs AI-Driven Accelerators for Smarter, Faster Testing

GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Ready to transform your QA practices?

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Using Continuous Customer Testing for Pandemic-Proof Product Success

Speaker: Luke Freiler, CEO and co-founder of Centercode

COVID-era product management is fraught with challenges as companies scramble to adapt their approach to make the most out of the current economic climate. How to expand product test coverage — even when budget cuts leave you short-handed. Scaling testing processes to support release schedules that are bursting at the seams.

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Why Product Managers Must Relearn Their Customers

Speaker: Janelle Estes, CIO, User Testing

The impact on businesses cannot be understated, and product managers have felt the brunt of it. How to use customer feedback to understand their needs, test hypotheses, and refine your approach through ongoing feedback. We are living in unprecedented times that have changed the way we live and work. Real-life examples of this process.

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How To Design Your Next Roadmap with Data-Driven Pit Stops Masterclass

Speaker: Sonia Singhal, Product Manager at eBay

These days, a simple A/B test can seem to incorporate the whole alphabet, and making a decision from that data isn't as easy as A, B, C either. How do we know we are testing the right thing? How can we shorten the time it takes to do the tests while gaining larger amounts of data? A Live/On-Demand Masterclass.

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Put Your Data to Work: The Complete Playbook

From search engines to navigation systems, data is used to fuel products, manage risk, inform business strategy, create competitive analysis reports, provide direct marketing services, and much more. An interactive quiz to test (and refresh) your knowledge of different data types and how they help your organization.