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Product Strategy as a System

Roman Pichler

Listen to the audio version of this article: [link] A Product Strategy System The product strategy system in Figure 1 consists of four main parts: people, processes, principles, and tools. Like any system, it is a collection of interconnecting parts that function as a whole. If so, what are they?

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522: Stop the stupid using proactive problem solving – with Doug Hall

Product Innovation Educators

hours daily fixing problems, with 75% of issues stemming from broken systems rather than employee mistakes. Even more concerning, products typically lose 50% of their innovative value during development as unique ideas get compromised to fit existing systems. Doug shared that the average manager wastes 3.5

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518: The non-obvious way to gain organization support for your ideas – with Doug Hall

Product Innovation Educators

Ranch and Dexter Bourbon Distillery, Hall discovered that successful innovation requires a bottom-up transformation focusing first on empowering frontline employees to fix inefficiencies (“stop the stupid”), then enabling middle managers to improve systems, and finally allowing leadership to pursue bigger strategic innovations.

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Building a resilient system: Our journey to observability at Intercom

Intercom, Inc.

That requires a strong culture of observability across our teams and systems. We operate a socio-technical system, and its ability to recover when faced with adversity is called resilience. We operate a socio-technical system, and its ability to recover when faced with adversity is called resilience.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

The number of use cases/corner cases that the system is expected to handle essentially explodes. When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases.

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Comparing a Systems Product Manager to a Feature Product Manager

Mind the Product

Vignesh Balagopalakrishnan, Group Product Manager at Yelp, looks at the key differences and similarities between a Systems Product Manager and Feature Product Manager. Read more » The post Comparing a Systems Product Manager to a Feature Product Manager appeared first on Mind the Product.

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Systems, not mandates: how to build better product teams

Mind the Product

In this guest post, regular Mind the Product contributor and Product Leader, Alex Hughes, delves into the conversation of building better product teams, and why focusing on the system matters the most. Read more » The post Systems, not mandates: how to build better product teams appeared first on Mind the Product.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.

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Innovation Systems: Advancing Practices to Create New Value

As technology transforms the global business landscape, companies need to examine and update their internal processes for innovation to keep pace. Ultimately, organizations will have to improve the velocity of innovation by creating repeatable processes that support ideation, exploration, and incubation, essential to capturing an idea’s full value.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data.

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Resilient Machine Learning with MLOps

But we can take the right actions to prevent failure and ensure that AI systems perform to predictably high standards, meet business needs, unlock additional resources for financial sustainability, and reflect the real patterns observed in the outside world.

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10 Rules for Managing Apache Kafka

Learn ten rules that will help you perfect your Kafka system to get ahead. Kafka is a powerful piece of software that can solve a lot of problems. Like most libraries and frameworks, you get out of it what you put into it.

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10 Rules to More Streamlined Data Modeling

Learn 10 rules that will help you perfect your Kafka system to get ahead. Apache Kafka is a powerful piece of software that can solve a lot of problems. Like most libraries and frameworks, you get out of it what you put into it.

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Monitoring AWS Container Environments at Scale

Key metrics to monitor when leveraging two container orchestration systems. Download this eBook to learn about: The changing state of containers in the cloud and explore why orchestration technologies have become an essential part of today’s container ecosystem.