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Finding the “Need”: Using Data to Build Products People Actually Give a Damn About

Real product managers uncover product opportunities using data and business intelligence.
Start with clarity and explore patterns using CSV files and tools like Excel or Google Sheets.
Look for non-obvious signs of need by separating mild curiosity from real pain.
Pitch hypotheses backed by data and logic, create models to evaluate needs, and prioritize based on data, user feedback, and team agreement.

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Product Management 101: #46 Landing Page Test

In the world of product management, landing page tests are crucial for validating ideas before investing time and resources into development.
Landing page tests help in de-risking decisions by providing valuable insights in the early stages of product discovery.
They are lean, cheap, and fast, making them ideal for validation and continuous discovery.
Real-world examples like Buffer, Dropbox, and Zappos demonstrate the effectiveness of landing page tests in assessing user demand and guiding product development.

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Why Every Product Leader Needs to Consider an AI Product Manager Course

An AI product manager course is essential for product leaders to understand how to build AI-driven products responsibly and collaborate effectively with data teams.
It focuses on asking the right questions, steering teams in the right direction, and making decisions in high uncertainty situations.
Ideal for current or aspiring product managers in AI-driven companies, as well as professionals transitioning from other domains into product roles.
When selecting an AI product manager course, prioritize those developed by practitioners for real-world application with case studies, industry experts, and project-based learning.

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Stop Wasting Design Time…

Psychologists call the peak-end rule, where endings have a significant impact on how people perceive products.
Users remember peak moments and endings more than individual interactions.
Examples like TurboTax, Airbnb, and Peloton show how nailing the endings can enhance user experience and memory.
Creating meaningful peak moments and endings in products is crucial for building lasting memories and user loyalty.

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5 Plant-Based Recipes That Naturally Help You Relax

Turmeric-Ginger Golden Milk is a warm drink containing turmeric, ginger, and cinnamon linked to reduced anxiety.
Avocado Spinach Smoothie is a creamy green smoothie packed with magnesium and healthy fats for a calm day start.
Lentil & Sweet Potato Stew is a comforting dish providing complex carbs and tryptophan to regulate mood and sleep.
Chickpea & Quinoa Buddha Bowl is a B-vitamins and plant protein-rich bowl supporting nervous system health.
Dark Chocolate Chia Pudding is a dessert rich in antioxidants from dark chocolate, aiding in stress reduction.
Magnesium helps calm the nervous system, antioxidants fight inflammation, and complex carbs promote stable mood.

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Unlocking AI: work at pace, not at haste

To ensure successful AI projects, it is essential to fail fast, learn, and improve with the confidence of decision-makers releasing the funds.
Understanding the business problem before jumping to solutions and aligning with the strategic context is crucial in AI initiatives.
Documenting stakeholders' needs, prioritizing use cases, and fostering buy-in are vital for adoption and collaboration in AI projects.
Assessing risk appetite for AI interactions, data quality, and ongoing support commitment are key factors in successful AI deployment.
Differentiating Proof of Value, Proof of Concept, and Minimum Viable Product, and managing expectations are crucial in AI project delivery.
Constantly reminding stakeholders of realistic timelines and capabilities and seeking a balance between quality and analysis paralysis is crucial in successful AI projects.
Working at pace while ensuring thoroughness, collaboration, and strategic alignment is foundational for unlocking the true potential of AI projects.
Commitment to these principles ensures technologically sound, strategically aligned, and user-centric AI projects that deliver significant business value.
Maintaining transparency, managing expectations, and embracing iterative approaches are key to successful AI project delivery and adaptation.
The foundation of project success and unlocking AI potential lies in thoroughness, collaboration, and strategic alignment, rather than haste.

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How Poor Documentation Nearly Cost Us Millions — and What We Did About It

A major telecom manufacturer faced potential financial losses due to poor documentation of a large network product.
Critical knowledge erosion within the several hundred-person development team led to outdated and scattered documentation.
Initially viewed as overhead, the outdated documentation posed a direct threat to the product's competitiveness.
A methodical approach to restoring knowledge allowed for confident steering of the system's evolution, reducing the risk of financial losses.

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The MCE Model — Creating Value through Minimal Resources and Feedback-Driven Iteration

Companies like Apple, Facebook, and Amazon started with minimal resources but created value by embracing the 'just try it' mindset and gathering feedback for continuous improvement.
The Experiment Framework in the MCE model leverages limited resources to accelerate innovation, enabling teams to create value even with little funding or few people.
Top management makes final decisions on proposals in the MCE model, focusing on business goals and the current situation after a detailed failure analysis.
A structured approach with clear proposal presentations prevents future stakeholder issues in the Creative Organized Technology (CreativeOrgTech) framework.
Teams evaluate feasibility and may opt for Phased Project Planning (PPP) to reach targets incrementally, developing MVPs based on lean startup principles.
The hybrid Experiment Framework combines NASA's PPP approach with lean startup techniques, allowing for hypothesis testing through MVPs for practical innovation.
The Build-Measure-Learn loop in PPP forms a self-correcting feedback cycle, aligning with the lean startup methodology for effective progress towards objectives.
In situations where MVP results are unsatisfactory, teams use feedback to pivot or improve plans before moving on to the next phase of the PPP.
Japan's space development history showcases how the Experiment Framework was utilized to achieve milestones, gradually improving rockets and achieving space program goals.
Through iterative experiments and feedback processes, Japan successfully launched artificial satellites, becoming a key player in space exploration.
The Experiment Framework's application extends beyond space development to various fields like product and process innovation, facilitating progress and value creation.

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Leader Spotlight: Deriving product strategy from customer listening, with Ezinne Udezue

Ezinne Udezue has had a successful career as a product leader, working for companies like T-Mobile, Procore Technologies, and WP Engine, and co-authoring a book on product management.
She emphasizes the importance of customer listening in shaping product and company strategy, highlighting the need to interpret natural conversations and feedback from various sources like support calls and sales conversations.
Ezinne shares insights on leveraging customer listening to refine and evolve product strategies, citing examples from her experiences at WP Engine and T-Mobile.
At WP Engine, customer feedback revealed the need for a dark mode UI for developers, showcasing the impact of early customer listening on product improvements.
She discusses how customer feedback played a significant role in T-Mobile's transformation from the fifth to the second position in the telco market through a customer-first approach.
Ezinne outlines a framework called LiSA (Listening, Synthesizing, Acting) to guide the process of integrating qualitative feedback with quantitative data to make informed product decisions.
She stresses the importance of balancing customer, problem, and business perspectives to distinguish strong signals from noise in feedback channels and advises on engaging engineering teams to showcase the impact of product changes.
Ezinne recommends tapping into underutilized sources of customer insight like Reddit and creating product councils with experts to drive valuable conversations around product development.
In conclusion, Ezinne Udezue's expertise in customer listening highlights its critical role in shaping successful product strategies, emphasizing the need for continuous feedback interpretation and alignment with business goals.

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From Generative to Agentic AI: A Product Manager’s Guide to the Next Generation of AI

From passive tools to proactive collaborators, computers have evolved into agentic AI systems that act with autonomy and intent.
Generative AI creates original content based on learned patterns, while agentic AI acts autonomously and makes decisions to achieve goals.
Generative models like GPT-4 create diverse outputs across text, images, audio, and video, offering cross-domain versatility.
Agentic AI systems operate autonomously, adjust strategies in real time, and collaborate with humans to execute complex tasks.
Deploying generative AI for creativity and agentic AI for decision-making is crucial for maximizing efficiency and outcomes.
AI frameworks like LangChain, AutoGPT, and Azure AI Studio offer infrastructure for orchestrating complex agent behaviors.
Choosing the right AI approach based on specific needs is essential, using a framework that considers reasoning, tool integration, and memory.
Shifting organizational mindset towards AI-powered collaboration is crucial for success in the new era of AI integration into workflows.
AI collaboration requires addressing product and ethical challenges, embracing a mindset of amplifying human capabilities with AI support.
Thriving in the AI-powered future involves active engagement, creativity, ethical considerations, and shaping the evolution of AI technologies.

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A DevRel’s Perspective: Navigating Product Launches, Quality, and Market Velocity in the AI Era

DevRel plays a crucial role in navigating product launches, quality, and market velocity in the AI era, emphasizing the developer-to-developer connection.
Product launches involve rigorous checks for user safety, data privacy, and more, with a need to balance model quality and launch readiness.
Market velocity requires understanding customer needs and staying ahead of competitors to maintain user trust and market share.
Quality and security should not be compromised in the rush to launch, as good-quality products that are easy to understand are well-received by users.

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The Usability Trap (or: Why That Avocado Stick Shouldn’t Exist)

Usability in product development is often focused on making things easy to use, but it's essential to also consider usefulness.
Just because something is easy to use doesn't mean it's worth using, highlighting the importance of creating products with real value.
Perceived usefulness is more important than perceived ease of use in determining the success of a product, as demonstrated by the Technology Acceptance Model (TAM).
Instead of just focusing on prototypes to test usability, considering provotypes that question the necessity and real-world value of the product can lead to more meaningful design outcomes.

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9 Likes

Medium

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Hustler’s Guide to Working Backwards: Build and Interview Like an Amazonian.

Working Backwards approach involves starting with answering key questions through four pillars: PRs, FAQs, Tenets, and Metrics.
In interviews, respond like a PR to make people care about the product and speak about FAQs to anticipate questions and align with stakeholders.
Tenets act as guardrails defining product operations and scale. Use them to justify decisions and show credibility.
Define success metrics upfront to measure product success effectively. When discussing success measures, focus on numbers with reflection for a compelling response.

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The Toolbox, the Square Peg, and the Next Chapter: A Product Leader’s Reflection at 47

The author reflects on their product leadership journey at the age of 47 and discusses the importance of having a diverse skill set and problem-solving abilities.
They emphasize the significance of being a builder and problem solver who thrives in ambiguity, collaborates with teams, and translates ideas into tangible products.
The author highlights their experience in full-stack development, automation, and people skills, underscoring the value of empathy, direct communication, and alignment within teams.
Ultimately, the author shares their eagerness to join a team that values outcome-driven builders and emphasizes the importance of continuous learning and adapting to keep their skills sharp and toolbox up-to-date.

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Medium

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Google NotebookLM vs. Obsidian: Strategic Tools for Maximizing Knowledge Work Efficiency

This article compares Google NotebookLM and Obsidian as tools for maximizing knowledge work efficiency
Google NotebookLM is an AI-powered smart notebook that excels in providing fast access to insights from various documents like Google Docs and PDFs.
Obsidian is a markdown-based note-taking app focused on connecting information through backlinks and graph views, suitable for writers, researchers, and product strategists.
The article suggests a workflow layering approach using both NotebookLM and Obsidian to cater to quick insights and long-term strategy needs in professional environments.

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