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What Could Happen When AI Starts Writing Our Dating Profiles

AI is increasingly being used in dating profile design, with many Gen Z singles utilizing AI tools for profile optimization.
While dating app usage is high, there is skepticism about AI's ability to accurately predict chemistry and love.
There is a call for radical transparency in utilizing AI for dating profiles to retain the user's voice and vulnerability.
The debate on trust between human and AI continues, with a focus on blending machine efficiency with human storytelling in profile creation.

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Medium

How Important Is Design for Manufacturability in Product Development?

Designing with manufacturability in mind reduces production costs by choosing cost-effective materials, assembly methods, and fabrication processes.
Products designed for ease of manufacturing speed up time to market by moving through prototyping and production phases more quickly.
Well-designed products minimize waste, errors, and rework, leading to a more sustainable production process.
Aligning design with manufacturing capabilities improves product quality and consistency, crucial in industries like electronics, medical devices, and automotive.

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Medium

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Build it dirty, build it fast: why Web3 doesn’t need your perfect strategy

Embracing imperfection, vulnerability, and early product releases is crucial for learning and improvement.
Feedback from real users, even if harsh, is valuable for identifying gaps and refining ideas.
Moving fast, testing hypotheses, and adapting beats waiting for perfection in a fast-paced world.
Effective leadership in a Web3 world involves embracing ambiguity, leading with resilience, and acting decisively amidst chaos.

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4 Likes

Medium

248

GenAI Is Not the Strategy

Starting with technology is a failure of product thinking for those shipping products at scale.
Considering the problem first before delving into GenAI is crucial to avoid solving imaginary issues and wasting resources.
GenAI should not be the starting point, but rather a solution that naturally emerges as effective for addressing a specific problem.
The focus should be on good product practice and avoiding a trust hit from users if GenAI features do not deliver effectively.

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Medium

402

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Halfway Here — A Heartfelt Review of My H1 as a Human-Centered PM

The author reflects on their journey as a human-centered Product Manager halfway through the year.
The journey has been challenging, with expectations not being met and silence surrounding their work.
They emphasize the importance of mental wellness and staying committed to their vision, despite setbacks.
The author reinforces the value of emotional resilience and announces their commitment to continue their blog for personal growth.

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Dev

119

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How to Raise SaaS Prices Without Losing Your Users

Raising prices for a SaaS product is crucial for continued growth, especially if the product has evolved significantly.
Signs it may be time to revisit pricing include adding value through new features, better support/services, and outdated early-stage pricing.
To raise prices without losing users, consider rewarding existing customers, using data and feedback to shape new tiers, and framing the change around increased value.
Pricing is a product decision that should reflect the product's maturity and the value it offers to users.

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7 Likes

Medium

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From Vision to Backlog: Prioritizing Features That Truly Move the Needle

Prioritize features based on strategic alignment, customer impact, and business outcomes.
Define and weight value dimensions upfront to create a transparent scoring rubric.
Frameworks like RICE, ICE, WSJF, and Kano Model offer diverse prioritization approaches.
Regularly revisit and adjust prioritization based on evolving OKRs and strategic context.
Establish consistent scoring scale, apply weights, and visualize value scorecard for effective prioritization.

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3 Likes

Medium

265

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Delight, Defend, Profit: Mastering the DHM Framework for Product Strategy

DHM framework emphasizes user delight, defensibility, and profitability for strategic product decisions.
Delight pillar focuses on exceeding user expectations, while defensibility ensures unique advantages.
Margin pillar stresses sustainable revenue and resource allocation for ongoing innovation and growth.
Packaging DHM ideas into high-level hypotheses guides strategic decision-making and maximizes product impact.

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15 Likes

Medium

295

The Easiest Digital Products to Start Selling as a Beginner

Digital products are a powerful way for beginners to start selling products without the need for shipping or inventory.
The easiest digital products to launch include Notion templates, ebooks, mini-courses or tutorials, digital audio files, and business resources.
Examples of digital products to create are Notion templates for organization, short ebooks with valuable content, simple tutorials, audio files like guided meditations, and business resources.
Overall, digital products offer a beginner-friendly income stream with low costs, high profit margins, and room for improvement over time.

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17 Likes

Medium

381

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Agile Leadership Tip: “The #1 question I ask new engineering managers in week 1”

Agile leadership tip emphasizes asking new engineering managers what their team wishes they'd already understand without being told explicitly.
Effective leadership involves perceiving invisible expectations, unspoken tensions, quiet brilliance, and unvoiced fears within the team.
New managers are advised to prioritize observation and understanding over quick actions in their initial 100 days.
Encouragement is given to new managers to focus on curiosity, listening, and asking insightful questions in their first week rather than providing immediate answers.

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22 Likes

Medium

184

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AI Copilots Are Reshaping Workflows in SaaS Tools

AI copilots are reshaping workflows in SaaS tools by becoming integrated as workflow partners rather than standalone chatbots or novelty add-ons.
SaaS products have become bloated with more features and complexity, leading to the rise of AI copilots that aim to reduce friction and help users get work done more efficiently.
Examples of successful AI copilot implementations include GitHub Copilot, Notion AI, and Microsoft 365 Copilot.
The age of AI copilots is already here, reshaping the product experience to be more user-centric, guiding users through workflows with less cognitive load.

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Logrocket

244

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Leader Spotlight: Data-driven vs. human-centered decision making for product design, with Rumana Hafesjee

Rumana Hafesjee shares insights on product leadership and the evolving role of the product executive.
The article discusses the balance between data-driven decision making and human-centered thinking in product design.
Rumana highlights the importance of good data for understanding users and making quick decisions.
She also talks about the changing landscape of product management and offers advice for staying competitive.

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14 Likes

Medium

330

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The Great Git Directory Massacre (And Other Cautionary Tales)

After facing a GitHub Pages 404 error, author shares valuable debugging lessons.
Debugging missteps include unnecessary file additions and mistaken branch sync attempts.
Ultimately, the issue resolves by understanding GitHub Pages and utilizing Jekyll effectively.

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19 Likes

Medium

385

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Part 1: The New Age of Product Management: Fundamental Shifts in the AI Era

Product management in the AI era requires a shift from output to outcome focus, tying launches to clear business or user impact.
PMs need to master data and AI fluency, understanding concepts like data pipelines, sampling bias, and model performance metrics.
Designing for the model involves treating the AI system like a teammate, planning features to improve model feedback and accuracy.
Championing responsible AI involves incorporating fairness, transparency, and trust into roadmaps through audits, calibration checks, and transparent UX cues.

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22 Likes

Medium

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Shadow AI and the Debt You Can’t See: The Hidden Cost of Innovation

Businesses are experiencing an inflection point in the AI-dependent world where innovation comes with a hidden cost called Shadow AI and Technical Debt.
AI, while promising reinvention and efficiency, can also lead to unseen issues like product delivery bottlenecks, security vulnerabilities, and scalability problems.
Shadow AI, reminiscent of the early days of software development in garages, is now happening within regulated enterprises as employees create AI-enhanced workflows to enhance productivity.

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