The hottest Product Management Substack posts right now

And their main takeaways
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Top Business Topics

3 Actionable Tactics To Create A Good Data Strategy

Three Data Point Thursday • 39 implied HN points • 01 Feb 24
💼 Business Data Strategy Product Management
  1. Netflix transformed into a data company by focusing on leverage and transitions in their value chain.
  2. To create a good data strategy, consider mapping out your value chain, playing Perfect World scenarios, and performing pipeline analysis.
  3. Use data and algorithms to increase the bottleneck in your value pipelines for impactful data strategies.

15 Product Management templates to boost your productivity

Untrapping Product Teams • 393 implied HN points • 29 Mar 23
💼 Business Product Management Templates Strategy Discovery Delivery
  1. Product management is complex, and there isn't a one-size-fits-all solution for everyone.
  2. Utilizing various templates and methods can help create value and accelerate growth in product management.
  3. Premium materials and resources are available to help product leaders and managers understand key principles for success.
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Week 82 - E10 - Future Trends: Gen AI and the Next Generation of Products

The Product Channel By Sid Saladi • 13 implied HN points • 10 Mar 24
🕹 Technology AI Product Management Generative AI Autonomous Agents
  1. Cognitive generative AI combines generative models with cognitive computing capabilities, revolutionizing industries like healthcare and creative design.
  2. Generative AI is poised to transform immersive experiences like VR and AR by generating realistic 3D environments in real-time.
  3. Autonomous generative AI agents can make decisions independently, adapting to dynamic environments and revolutionizing industries like customer service and supply chain management.

Why product analytics is completely different than BI

timo's substack • 294 implied HN points • 28 Feb 23
🕹 Technology Data Analytics Product Management Business Intelligence Data Collection Data Modeling
  1. Marketing analytics, BI, and product analytics have different requirements for source data and data handling.
  2. Product analytics involves more exploration and pattern-finding compared to marketing analytics and BI.
  3. Adopting product analytics requires a different approach, mindset, and tool compared to traditional analytics setups.

Get Your Positioning Right

Build To Scale • 138 implied HN points • 31 Aug 23
💼 Business Startups Product Management Marketing Differentiation
  1. Positioning your product correctly is crucial from the start, you can't retroactively adjust it like changing a boat into a car.
  2. Identify your target market, the problem your product solves, and what makes you better than competitors.
  3. Use a simple positioning template to describe your product's key attributes clearly and guide your marketing efforts.

Week 78 - E6 - 🏰 Building a Moat for Your AI Startup 🏰

The Product Channel By Sid Saladi • 20 implied HN points • 11 Feb 24
🕹 Technology AI Startups Product Management Data science Innovation AI Generative AI Product Management Data Training AI Startups
  1. Building a competitive moat in AI involves strategic navigation of the generative AI value chain to create unique advantages.
  2. For AI startups, it's crucial to focus on acquiring proprietary data, integrating AI into comprehensive workflows, and specializing models through incremental training techniques.
  3. Companies like Anthropic, Landing AI, and Stability AI showcase effective moat-building strategies in AI by emphasizing ethical development, democratizing technology, and niche specialization.

How to optimize your free trial

Kyle Poyar’s Growth Unhinged • 236 implied HN points • 10 May 23
💼 Business Marketing User Experience Product Management Conversion Onboarding
  1. Collaborate with experts to conduct a thorough audit of your product-led growth strategy.
  2. Implement best practices at each stage of the free trial experience such as creating a compelling sign-up page and a goal-oriented onboarding checklist.
  3. Utilize personalized templates, value-add empty states, and contextual guidance to enhance user experience and increase conversion rates.

Premortem Of My Career Direction: Lessons From Poker And ‘Thinking In Bets’

Harmony • 19 implied HN points • 07 Feb 24
💼 Business Consulting Coaching Product Management Writing Job search
  1. Premortem involves imagining project failure and analyzing potential reasons for it.
  2. Analyzing career directions like consulting, coaching, and product management can help in setting robust goals.
  3. Considering possible reasons for failure in different workstreams can aid in planning and making improvements.

Week 75 - E3 - 🛠️ Prompt Engineering Basics and 50+ Free 🎁 Product Management Prompts 🚀

The Product Channel By Sid Saladi • 23 implied HN points • 21 Jan 24
🕹 Technology AI Product Management Prompt engineering Generative AI
  1. Prompt engineering is crafting effective natural language prompts to get desired outputs from AI.
  2. Prompt engineering is crucial for product managers to unlock AI potential in workflows and decision-making.
  3. Well-structured prompts include clear instructions, context, format, and tone, enhancing coherency and relevance.

Week 78 - E7 - 🚀🤖✨Transform Your Business with Next-Gen RAG Digital Assistants

The Product Channel By Sid Saladi • 13 implied HN points • 18 Feb 24
🕹 Technology AI Machine Learning Product Management Chatbots
  1. Large Language Models (LLMs) trained on Private Data are becoming popular for creating AI assistants that can engage customers, answer questions, assist employees, and automate tasks.
  2. The Retrieval-Augmented Generation (RAG) framework enhances the capabilities of LLMs by incorporating external, real-time information into AI responses, revolutionizing the accuracy and relevance of generated content.
  3. Implementing RAG in enterprises through steps like choosing a foundational LLM, preparing a knowledge base, encoding text into embeddings, implementing semantic search, composing final prompts, and generating responses can transform business operations by empowering employees, enhancing customer engagement, streamlining decision-making, driving innovation, and optimizing content strategy.

LangChain: PM's Guide for Building Smarter Products

Product Mindset's Newsletter • 9 implied HN points • 03 Mar 24
🕹 Technology Product Management Language Models Integration
  1. LangChain is a framework for developing applications powered by language models that are context-aware and can reason.
  2. LangChain's architecture is based on components and chains, with components representing specific tasks and chains as sequences of components to achieve broader goals.
  3. LangChain integrates with Large Language Models (LLMs) for prompt management, dynamic LLM selection, memory integration, and agent-based management to optimize building language-based applications.

Maximizing Product Management Efficiency with ChatGPT and Generative AI

An Innovator's Sketchbook • 19 implied HN points • 28 Jan 24
🕹 Technology AI Product Management Generative AI Automation Data Analysis
  1. Leverage AI to boost personal productivity in product management through planning, execution, and user feedback analysis.
  2. Use large language models (LLMs) in product strategy for idea generation, evaluation, and decision-making.
  3. Optimize day-to-day efficiency by using AI to break down goals into manageable tasks and plan daily schedules.

Week 77 - E5 - Roles and Responsibilities of an AI Product Manager

The Product Channel By Sid Saladi • 16 implied HN points • 04 Feb 24
🕹 Technology AI Product Management Skills Education Development
  1. AI product managers bridge business and technology in the development of AI-powered products
  2. Key responsibilities of AI product managers include research, strategy, development, execution, product launch, and growth
  3. Necessary skills for AI product managers include AI and data literacy, technical acumen, business savviness, strategic thinking, stakeholder alignment, and user empathy

Week 80 - E8 - 🤖 AI Integration for Faster, Better Product Development

The Product Channel By Sid Saladi • 10 implied HN points • 25 Feb 24
🕹 Technology Artificial Intelligence Product Management Market Analysis Decision-making Software Development
  1. Artificial Intelligence (AI) is a pivotal force in reshaping industries, offering product managers opportunities to enhance their development lifecycle.
  2. Integrating AI into product development leads to reduced time-to-market, increased efficiency, and better resonance with users.
  3. AI helps in enhancing ideation by analyzing customer feedback, conducting market research, and generating innovative concepts to uncover promising opportunities.

Leverage Points for solving complex problems

Turnaround • 277 implied HN points • 01 Aug 22
💼 Business Management Systems Thinking Problem Solving Product Management
  1. Complex problems require moving away from linear thinking and embracing complexity thinking that involves understanding interconnections and dependencies.
  2. Leverage points in a system are areas where small changes can cause significant overall impact. These include adjusting parameters, dealing with stock buffers, considering system structures, managing feedback loops, controlling information flows, setting incentives and rules, enabling self-organization, and aligning with system goals and paradigms.
  3. Differentiating between complicated and complex systems is crucial in problem-solving. In complex interconnected systems, problem statements often fall into categories such as coupled, causal, or standalone.

TWH#50: Simple Explanations For Complex Phenomena

The Hagakure • 119 implied HN points • 16 Mar 23
💼 Business Product Management Software Engineering Agile Methodology Organizational Behavior
  1. Our brains seek simple explanations for complex phenomena due to our evolutionary history.
  2. Predictability and control in knowledge work are often illusory, leading to eroded trust and inefficiencies.
  3. Embracing uncertainty and complexity in work requires shifting mindset towards experimentation and adaptation.

Week 74 - E2- Basics of Large Language Models for Product Managers 🤖

The Product Channel By Sid Saladi • 13 implied HN points • 14 Jan 24
🕹 Technology AI Product Management Natural Language Processing Innovation User Experience
  1. Large language models (LLMs) are transforming industries with diverse applications like automated article generation, conversational product recommendations, intelligent chatbots, and code generation.
  2. LLMs play a crucial role in product innovation by assisting in rapid ideation, prototyping, concept validation, and continuous enhancement of offerings.
  3. Understanding the costs and data requirements to develop LLMs is essential, as it involves significant investment in computational resources, data training, and cloud infrastructure.

New Generation Product Leader Model

Product Power by Samet Ozkale • 98 implied HN points • 16 Feb 23
💼 Business Product Management Data-driven Agile Collaboration
  1. Product leaders should focus on data-driven and customer-centric approach in product development.
  2. Understanding the user through research and user feedback is crucial for making informed decisions and solving real problems.
  3. Cross-functional collaboration and transparent accountability are essential for fostering innovation and delivering results in product management.

Choosing the right UX metrics - Part 2

UX Psychology • 158 implied HN points • 03 Oct 22
🕹 Technology UX Design Metrics Product Management User Experience Data Analysis
  1. Identifying clear goals is crucial in choosing the right UX metrics, involving team and stakeholders can help define meaningful and actionable metrics.
  2. Mapping goals to signals helps track progress towards goals; gathering user feedback and reviews can be essential signals to measure UX success.
  3. Refining signals into specific metrics is the final step, where data scientists can assist in ensuring metrics are measured accurately; focus on key metrics and avoid adding unnecessary data.

Thoughts From Inside the Intensity Machine

•ꪜꫀᥴꪻꪮ᥅ꫝꫀꪖ᥅ꪻ• • 2 HN points • 24 Mar 24
🕹 Technology Innovation Tech industry AI Product Management Neuroscience
  1. The tech industry has shifted towards perpetuating its generative model over genuine innovation, leading to a mechanization of value generation.
  2. Revolutionary technological change requires higher flexibility, interdisciplinary collaboration, and reflexivity in research and product development, contrasting with the current 'move fast and break things' culture.
  3. Human agency involves deliberately changing conditions to create new problems, embracing novelty and deliberate decision-making to shape collective imaginary and make a positive impact.

How to Gain an Edge as a B2B PM

Product Managers at Work • 4 implied HN points • 28 Feb 24
💼 Business Product Management Customer Feedback Data Analysis User Insights
  1. Being a B2B Product Manager comes with unique challenges compared to B2C, like blending limited data with qualitative feedback for decision-making.
  2. It's crucial for B2B Product Managers to gather direct feedback from users through feedback portals to avoid bias and make informed decisions.
  3. Contextualizing and acting on user feedback effectively, based on target segments and feature usage data, can help prioritize product improvements for B2B success.

🤖 Week 73 - E1- Introduction to General AI for Product Managers 🤖

The Product Channel By Sid Saladi • 10 implied HN points • 07 Jan 24
🕹 Technology AI Product Management Machine Learning Generative AI Automation
  1. AI is essential for product managers to stay competitive and create innovative products.
  2. Understanding key AI concepts like machine learning and computer vision is crucial for product managers.
  3. Product managers should adopt offensive and defensive AI strategies to leverage its benefits while mitigating risks.

Feature flags are ruining your codebase

Leading Developers • 3 HN points • 05 Mar 24
🕹 Technology Software Development Testing Product Management
  1. Feature flags can make codebases more complex and harder to maintain, especially when used as an excuse to avoid making hard decisions like completely removing a feature.
  2. Having too many feature flags can lead to wasted time on dead code, increased testing burden, and making testing a substitute for fixing issues.
  3. Different types of feature flags, like release toggles, experiment toggles, and permission toggles, require specific management approaches to prevent the codebase from becoming unmanageable.

Week 81 - E9 - Google Gemini AI blunder: Ethical Considerations and Responsible AI in Product Management

The Product Channel By Sid Saladi • 3 implied HN points • 03 Mar 24
🕹 Technology AI Ethics Product Management Responsibility Innovation
  1. Responsible AI practices are crucial to avoid unintended harm and build trust – especially as AI impacts critical areas like healthcare, justice, and finance.
  2. Key ethical risks in AI include perpetuating bias, lack of transparency, privacy violations, and negative societal impacts, making vigilance essential for product managers.
  3. Responsible AI principles like fairness, transparency, inclusiveness, accountability, and governance guide product managers in championing AI innovation while upholding ethical standards.

Shreyas Doshi on Product Thinking

Practical Product Discovery • 58 implied HN points • 23 Mar 23
💼 Business Product Management Product Development User Experience Innovation
  1. Product thinking involves understanding motivations and conceiving solutions based on effects you want to create.
  2. Avoid relying solely on project thinking, which focuses on plans and resources rather than user needs and creativity.
  3. To learn product thinking, prioritize real goals over deliverables, understand user needs, generate options, simulate outcomes, and study examples in the wild.

🏆 100+ Top Product Management Resources 2023

The Product Channel By Sid Saladi • 44 implied HN points • 21 May 23
💼 Business Product Management Resources Frameworks Leadership Communication
  1. Over 100 curated product management resources are shared in the newsletter.
  2. The resources cover various topics such as product vision, roadmaps, prioritization, AI, prototyping, customer needs, frameworks, and leadership.
  3. It also includes additional categorized resources like books, articles, podcasts, and templates for product management.

A Letter to Devs: What to Expect from Product Managers

Odai’s Substack • 3 HN points • 12 Feb 24
🕹 Technology Product Management Software Development Collaboration Innovation User Feedback
  1. Product Managers need to excel in figuring out the next most valuable thing to build and bring clarity to the dev team.
  2. Product Management involves a structured 'discovery' process with stages like framing, observation, synthesis, strategy, and prototyping.
  3. Product Managers should show the value proposition of what is being built, provide clear direction during development, and measure outcomes to ensure usefulness.