The hottest Product Management Substack posts right now

And their main takeaways
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Top Business Topics

Claire Vo: The CPO who automates herself with AI

CommandBlogue • 19 implied HN points • 19 Aug 24
🕹 Technology Product Management
  1. AI is changing how product managers work. It helps them complete tasks much faster, which could mean fewer PMs are needed in the future.
  2. The role of PMs might shift more towards being makers, meaning they will need to have skills in design and engineering to stay relevant.
  3. To break into product management, it's important to show what you can do by building something real for the companies you're interested in, rather than just sending a resume.

Why we like coffee more than Duolingo - P.1

Gentle Nudge • 99 implied HN points • 17 May 24
🕹 Technology Product Management
  1. Behavior depends on three factors: motivation, ability, and prompts.
  2. Product loops play a crucial role in user engagement and retention, involving triggers, actions, variable rewards, and investments.
  3. Consider additional variables like schedule, existing routines, sequences, and organic frequency when designing product loops for sustainable user engagement.

Briefing: Instagram nudges, Stripe retries, Chrome AI

Department of Product • 275 implied HN points • 25 Jan 24
🕹 Technology Product Management
  1. Instagram is implementing a new safety feature to deter teens from night-time app use.
  2. Many companies struggle to train employees on GenAI tools, but new visual AI workflow tools like VectorShift aim to simplify the process for product teams.
  3. Netflix's success in ad-funded plans raises questions on whether this model will extend to other product categories like SaaS.

A Complete Product Discovery Guide

Untrapping Product Teams • 412 implied HN points • 21 Jun 23
💼 Business Product Management
  1. Product discovery is essential to uncover what creates value, while product delivery produces what creates value.
  2. Having a sustainable balance between product discovery and product delivery within one team is crucial for success.
  3. Product discovery is a journey, not a rigid plan, where you set a business outcome as your north star and make decisions along the way.
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I Was Wrong About Scrum, Again

Rethinking Software • 549 implied HN points • 30 Nov 24
🕹 Technology Product Management
  1. Sprints can feel non-stop and stressful since they don't have breaks, which can lead to burnout. It's suggested that a 'sustainable pace' would help, but taking real breaks might be a simpler solution.
  2. Daily stand-ups can make team members feel pressured to justify their work constantly. However, the intent behind them is not for status updates but to facilitate communication and support.
  3. The role of a Product Owner in Scrum can leave developers feeling sidelined. Developers may worry that their insights are overlooked, but it’s believed that good Product Owners will always prioritize the development team's needs.

Product Delivery Guide

Untrapping Product Teams • 334 implied HN points • 19 Jul 23
💼 Business Product Management
  1. Product delivery is about creating value steadily, not just following a plan.
  2. Key aspects of product delivery include organizing the product backlog, refining tasks, aligning goals, and delivering value consistently.
  3. Be mindful of common traps like treating the product backlog as a wishlist, separating discovery from delivery, and focusing only on output instead of outcomes.

Build What You Depend On

Kathy PM • 13 implied HN points • 24 Jan 26
🕹 Technology Product Management
  1. Use your own product for real, high-stakes work — not demos — so every moment of friction becomes obvious and compels fixes.
  2. Dogfood the way customers actually do, including the API and cross-team workflows, and do it continuously so slow, repetitive annoyances surface.
  3. Make sure the people who feel the pain can act on it; dogfooding only improves the product when teams have the agency to fix issues and earn real trust.

The 9 Fundamental Ingredients to Thrive with Product Management

Untrapping Product Teams • 157 implied HN points • 07 Feb 24
💼 Business Product Management
  1. Product management is like cooking: it's not just about the recipe, but also about how you do it and the ingredients you use.
  2. Recognize the fundamental ingredients for thriving in product management, such as product vision, strategy, goals, and testing assumptions.
  3. Having a strong product vision is crucial for inspiring and motivating teams to progress in the right direction.

TBM 320: From Fluffy Concepts to Concrete Outcomes & Behaviors

The Beautiful Mess • 555 implied HN points • 10 Nov 24
💼 Business Product Management
  1. It's important to translate vague concepts into specific behaviors. Instead of saying you want to be 'data-driven,' describe actual actions that show you are doing this.
  2. Discussing behaviors as a team can spark valuable conversations and help everyone understand what needs to change. It allows people to share experiences and ideas in a meaningful way.
  3. When trying to improve team actions, focus on what gets in the way—like training gaps or social pressures. Identifying these barriers helps create better strategies for change.

#91: Are you doing more or extra?

Many One Percents • 294 implied HN points • 19 Feb 23
💼 Business Product Management
  1. Focus on doing extra work that goes beyond your current tasks and requires new skills or research.
  2. Avoid getting stuck in doing more of the same work as it may not lead to significant breakthroughs.
  3. Adding value by going the extra mile, like training colleagues or improving team workflows, can have a big impact.

Redefining data products: calming the noise

Datent • 137 implied HN points • 06 Feb 24
🕹 Technology Product Management
  1. The term 'data product' has become so broad that it lacks credibility and value.
  2. Data professionals can learn a lot from actual product management and strategy.
  3. Creating a taxonomy based on intention and proximity to the customer can improve the understanding and management of data products.

Why engineering leadership matters more than ever | Manoj Mohan

Dev Interrupted • 23 implied HN points • 16 Dec 25
🕹 Technology Product Management
  1. As AI makes code cheaper to produce, engineering leadership matters more than ever; leaders must provide high‑level judgment, start from customer pain points instead of models, and use simple frameworks to manage risk.
  2. The AI stack is shifting from prompt tinkering to context engineering and standardization, and policy is consolidating toward national frameworks to avoid fractured rules and tooling.
  3. Raw scale is no longer the main source of value — teams should measure AI assistant impact, focus on fine‑tuning and efficiency, and use clear, semantic names and namespaces so humans and models can understand the codebase.

📝 Guest Post: How to Build the Right Team for Generative AI*

TheSequence • 994 implied HN points • 19 Jan 24
🕹 Technology Product Management
  1. You may not need ML engineers for Generative AI projects due to the availability of pre-trained models like GPT-4.
  2. Prompt engineering, the clear articulation of needs in natural language, is a crucial skill for AI application development.
  3. Product managers and domain experts play a significant role in shaping AI products through prompt engineering, reducing the need for technical experts.

TBM 227: Explicit vs. Implicit Strategy

The Beautiful Mess • 1507 implied HN points • 18 Jun 23
💼 Business Product Management
  1. A strategy should be a clear description of challenges, decisions on what to address, and specific actions to impact those challenges.
  2. Translating strategy into tangible goals and budgets is crucial for making it meaningful to people in the organization.
  3. Creating a safe space for hard discussions, dedicating time for strategy development, and focusing on deployment are essential for making a strategy effective.

TBM 278: The Power of Firsthand Experience

The Beautiful Mess • 793 implied HN points • 17 Mar 24
💼 Business Product Management
  1. Having firsthand experience is crucial in understanding product concepts, like observing failed launches or successful market fit.
  2. Seeing a team hit dead ends before succeeding can encourage more leeway for experimentation and resilience.
  3. Direct access to customers, effective team dynamics, and confronting false assumptions can greatly impact decision-making and product success.

Introduction to unFIX

Ageling on Agile • 139 implied HN points • 17 Jan 24
💼 Business Product Management
  1. Different organizational structures can create value in different ways.
  2. Stability is essential but not always guaranteed in organizations.
  3. Adapting organizational structure quickly is crucial for responding to changing circumstances.

Embarking on the Product Management Journey: Product Research and Discovery

Product Power by Samet Ozkale • 196 implied HN points • 19 Oct 23
💼 Business Product Management
  1. Product managers can find ideas through user interviews, trend analysis, personal experiences, and input from internal stakeholders.
  2. Criteria for pursuing an idea include satisfying a need, having a unique selling point, being profitable and in demand, and creating value.
  3. Utilizing the Double Diamond framework can guide product discovery and development by focusing on understanding problems before jumping into solutions.

Everything New Has Bugs

Fish Food for Thought • 23 implied HN points • 03 Dec 25
🕹 Technology Product Management
  1. When you speed up releases or adopt new systems, bugs and incidents will usually rise at first — it’s a natural tradeoff between velocity and stability.
  2. Give teams slack and real ownership so they can fix problems, learn, and improve quality instead of just reacting to fires.
  3. Invest in supporting systems and feedback loops like CI/CD, observability, error budgets, and postmortems so you can absorb turbulence and restore quality faster.

Navigating the Shift from Feature to Product Teams and Building a Product Mindset

An Innovator's Sketchbook • 98 implied HN points • 04 Feb 24
💼 Business Product Management
  1. Transitioning from feature to product teams involves empowering cross-functional teams focused on outcomes and value.
  2. The localization industry is evolving with AI, leading to job destruction but also creating new business opportunities.
  3. Feedback is important for team growth, and using the 'Situation-Behavior-Impact' framework can lead to effective and powerful feedback.

Technically Monthly (January 2026)

Technically • 12 implied HN points • 06 Jan 26
🕹 Technology Product Management
  1. Try multiple vibe-coding tools by building the same thing so you learn their quirks, limits, and pricing before committing.
  2. Monitor AI with simple evals: study failures, use straightforward assertions instead of AI-judging-AI, and follow a loop of vibe check, spreadsheet, fixes, then targeted tests to cut hallucinations.
  3. Use AI thoughtfully at work by customizing prompts and iterating on workflows; learn prompt engineering or you risk being outcompeted by careless automation.

How we use Attio for a new PLG startup

nonamevc • 24 implied HN points • 18 Nov 25
💼 Business Product Management
  1. Attio is a practical CRM choice for early-stage startups that need flexibility and good user experience. It may not have all the features of bigger CRMs like HubSpot, but it's suitable for product-led growth teams.
  2. Integrating product and billing data in Attio is crucial for understanding customer behavior. Using tools like n8n can help automate data connections, making sure the team has a clear view of customer interactions.
  3. Email enrichment is important to transform unknown users into recognizable profiles. By combining personal and corporate email data, companies can better understand and engage their users.

Where Is Technical Program Management Heading in 2026?

Building Rome(s) • 15 implied HN points • 15 Dec 25
🕹 Technology Product Management
  1. AI tools will keep getting much smarter and cheaper, so TPMs should design workflows that age well and leverage compounding improvements instead of chasing a perfect tool.
  2. The novelty phase of AI is ending — leaders will demand real ROI, so TPMs must focus on measurable outcomes like predictive planning, risk simulations, and AI-assisted forecasting rather than surface-level automations.
  3. Companies need to provide access and training for specialized AI tools because lack of access will become an organizational problem, and the TPM role will shift toward a builder, cross-stack, AI-fluent generalist that increasingly overlaps with product management.

Managing for Abundance, not Scarcity

Anant’s Newsletter • 8 implied HN points • 14 Jan 26
🕹 Technology Product Management
  1. Writing code is now cheap because of AI, so the real constraints are context, taste, and decision-making — shift from protecting developer hours to enabling rapid experimentation and customer outcomes.
  2. Middle managers and leaders need to get hands-on and write code; pure people managers should no longer be acceptable, and everyone should be expected to be a builder.
  3. Restructure teams toward a 'diamond' model with more senior builders who can wield AI end-to-end, kill spec-first culture in favor of working prototypes, and measure success by iterations and customer outcomes instead of time estimates.

TBM 328: Beyond Firmographic-Based ICPs

The Beautiful Mess • 264 implied HN points • 18 Dec 24
💼 Business Product Management
  1. Traditional ways of identifying ideal customers, like just looking at company size or industry, aren't enough anymore. It's important to understand the specific needs and behaviors of different companies.
  2. When starting a new job, it's crucial to listen and learn from others instead of jumping to conclusions. Take your time to understand what actually matters for the product and the customers.
  3. Different organizations have unique ways of working, and it's vital to grasp those differences. Observing and talking to customers helps create better products that cater to their specific challenges and goals.

From Customer Success Leader to VP of Product

Suzan's Fieldnotes • 98 implied HN points • 15 Jan 24
💼 Business Product Management
  1. María de Antón transitioned from Head of Customer Success to Product Manager by following her instincts and overcoming imposter syndrome.
  2. Transitioning from customer success to product management involved a shift from talking with customers to creating joyful product experiences.
  3. As a leader considering switching functions, trust your cross-functional skills, seek necessary training, and have confidence in yourself.

When a PM takes over engineering

Leading Developers • 92 implied HN points • 01 Jul 25
🕹 Technology Product Management
  1. It's important for engineers to think like product people. They should understand the problem they are solving and not just build what’s written down.
  2. Good engineering managers help their teams understand the value behind technical projects, making clear connections to business goals. This helps everyone stay focused and aligned.
  3. After launching a product, teams should keep engaging with the data and user feedback to continually improve. This mindset helps engineers take ownership and see the bigger picture.

Get Your Positioning Right

Build To Scale • 138 implied HN points • 31 Aug 23
💼 Business Product Management
  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.

Tech Debt vs Quality

Fish Food for Thought • 14 implied HN points • 10 Dec 25
🕹 Technology Product Management
  1. Tech debt and bugs are different: bugs are immediate errors to fix, while tech debt is the future cost of taking shortcuts and can be intentional or accidental, so decide and plan when to incur it.
  2. Make debt visible and economic: track where it slows work, measure the "interest" it charges in developer time or incidents, and prioritize paying down high-interest items rather than treating all debt equally.
  3. Leadership and culture matter: embed maintenance into planning, keep slack for cleanup, use retrospectives and metrics to shorten recovery time, and design continuous improvement cycles so velocity and quality compound over time.

The AI user's guide to evals

Technically • 14 implied HN points • 11 Dec 25
🕹 Technology Product Management
  1. Evals are software tests for AI that turn fuzzy model outputs into measurable metrics so you can find and fix errors instead of guessing.
  2. Look at your data first — analyze real outputs to spot where the model fails, because you can’t measure or fix problems you don’t identify.
  3. Start with simple keyword checks and assertions before building complex “LLM-as-judge” setups, and iterate: test, fix, measure, repeat; otherwise your system just feels like a slot machine.