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Medium

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Pre-Sell Before You Build: Collect $1,000 in Commitments Without Writing Code

Pre-selling is crucial to validate market demand and secure early revenue for your startup without writing any code.
Creating a one-page document outlining your value proposition is essential before pre-selling your SaaS idea.
Engaging in discovery calls with potential customers helps validate the problem, gauge interest, and potentially secure pre-orders.
Framing the pre-sale as an exclusive opportunity and using direct language can help secure early commitments.
Utilizing the concierge MVP method involves manually delivering your service to gather valuable feedback before investing in full product development.
Successful examples of pre-selling strategies include segmenting audiences, offering discounts, and conducting personalized discovery calls.
Addressing common concerns like delivery confidence, benefits of paying early, and refund policies can help convince customers to commit.
Pre-selling is a powerful approach to gather early validation, funding, and customer feedback for your startup.
Initiating pre-sales can lead to building products that align closely with customer needs and preferences.
The article emphasizes the importance of pre-selling as a strategy to secure initial commitments and build products that customers truly want.

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Medium

229

Keep the Main Thing the Main Thing

Many Product Managers (PMs) focus more on talking about popular frameworks and products rather than building their own.
Craft and depth take a backseat to appearing smart and chasing buzzwords, often for self-promotion on platforms like LinkedIn.
This trend was observed post-Covid when hiring in PM roles surged, leading to a proliferation of noise in the industry.
In the world of AI, the noise around buzzwords and packaging stories has only amplified.
The author emphasizes the importance of depth and craft over mere noise, particularly for those starting their PM journey.
The best PMs the author learned from were not loud but deeply focused on their work.
The author suggests that sharing should stem from reflection rather than seeking attention.
Listening to customers, stakeholders, and metrics is crucial as they reflect the real value of your product and skills.
The author hopes this message encourages individuals to prioritize meaningful work over superficial noise.

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Medium

221

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Building a “house” in less than 24 hours

The frustration experienced by a person with anxiety and ADHD in dealing with AI systems was highlighted.
Challenges arose when the AI refused to implement features correctly or misunderstood core requirements, causing mental health distress.
The person humorously compared the AI's behavior to a computer system with an attitude problem, akin to a real developer.
Moments of extreme frustration led the individual to contemplate drastic actions like throwing their keyboard out of the window.
The person expressed their exasperation at the AI not understanding clear signals of broken code, resorting to humorous threats.
The tasks involved in interacting with the AI focused on providing a clear list of initial tasks or actions between input and output.
Value-driven prioritization was emphasized as crucial for the AI, categorizing features as 'Need to Have,' 'Want to Have,' or 'Nice to Have.'
By outlining the value of each feature, the individual aimed to create a product backlog to help the AI prioritize its efforts effectively.
This approach aimed to lead to more coherent and functional outputs from the AI, resembling the 'eat an elephant one byte at a time' concept applied to AI prompts.
A reminder was given to save and back up work regularly to avoid losing progress.

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Medium

203

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Finding Users Next Door-AI Adoption among Graduate Students

The study explores AI adoption among graduate students in higher education, challenging assumptions and revealing patterns.
AI tools have democratized access to advanced capabilities, regardless of traditional markers like work experience.
Students exhibit multi-platform usage, with a focus on platform agnosticism to match tool capabilities with task requirements.
Popular sub-use cases for AI among students include general applications, career development, and academic integration.
AI preparedness is driven by breadth over depth, emphasizing the use of multiple LLM platforms across different contexts.
A tiered learning spectrum is observed, suggesting the need for customized educational tracks based on preparedness levels.
Workplace discussions on AI significantly impact students' preparedness levels, indicating the importance of real-world application contexts.
Suggestions include fostering discussion culture, democratizing access to AI tools, and collaborating with AI centers for community development.
LLM product teams are advised to design for multi-platform reality, offer context-specific paths, and cater to a diverse user base.
Adopting AI together and evolving institutionally to guide the transformation thoughtfully are highlighted as crucial for academic success.
The article is eligible for web story generation as it covers a relevant and insightful study on AI adoption among graduate students with practical implications for higher education and product development.

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Medium

194

The Harsh Truth About Side Hustles Nobody Talks About

Side hustles can be unpredictable, with fluctuating success and challenges.
Days of no sales, messages, or responses can be discouraging.
Buyers may not always be serious or responsive, adding to frustration.
Lessons learned include the need for perseverance, continuous improvement, and consistency.
Side hustles require dedication and should be treated seriously like a full-time job.
Advice is given to continue pushing forward and not be disheartened by setbacks.
The article encourages resilience and ongoing effort in pursuing side hustles.
The author invites readers to follow for more content on hustle, motivation, and growth.
Overall, the message emphasizes the challenges and rewards of side hustles.
The article touches on the need for persistence and self-belief in the face of difficulties.

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Medium

119

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Data-Savvy Product Manager: Day 2 and Beyond

Day 2 is crucial for establishing consistent practices in data analysis to gain a competitive edge.
Standardized data collection processes ensure data accuracy and build trust among stakeholders.
Engage stakeholders by understanding their interests, communicating insights proactively, and visualizing data effectively.
Negotiation skills backed by data are essential for managing stakeholders and addressing their needs effectively.
Continuous optimization is key, requiring ongoing monitoring, adaptation of metrics, and fostering a culture of experimentation.
A successful data-driven PM balances quantitative and qualitative data to understand patterns and human stories behind them.

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Medium

335

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Product Discovery: The Art of Grounding Your Product Team in Customer Voice

The article delves into the approaches of Opportunity Discovery, Solution Discovery, and Planning in product strategy.
Opportunity Discovery confirms the existence of a valuable problem before proceeding further, focusing on customer needs and market size.
Solution Discovery defines how to solve the validated problem in a way that aligns with customer needs and business goals.
The Go / No-Go decision checkpoint ensures informed choices based on evidence before moving to planning.
Planning phase aligns the team on what needs to be built and ensures readiness for implementation.
A clear product strategy is highlighted as essential to keep teams focused on delivering real value for customers.
Discovery processes are emphasized as crucial in avoiding waste and disappointment in product development.
The importance of product strategy in guiding discovery work and aligning efforts to a shared vision is stressed.
AI tools like Dovetail and Microsoft Copilot are mentioned for enhancing discovery processes and capturing insights efficiently.
Engaging in thorough discovery, focusing on qualitative insights, and leveraging AI tools are advocated for effective product strategy.

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Medium

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The balance between solid business strategy and customer-oriented product development

Building a truly great product involves two essential requirements working in harmony: Market Strategy and Direction and Product Excellence and Customer Focus.
Market Strategy involves identifying target markets, lucrative opportunities, and understanding the competitive landscape through research and insights.
Product Excellence focuses on execution, user experience, and deep customer understanding to solve their pain points.
Having only one pillar locked down can lead to failures, like targeting the wrong market with a brilliant product or having a mediocre product in a promising market.
Balancing solid business strategy and customer-oriented product development is crucial for success.
The author previously undervalued the product side but realized the importance of prioritizing customer feedback and retention for a product's success.
By aligning a strong market opportunity with a customer-centric approach, the author believes in achieving the goal of building a GOAT product and finding success.
The foundation is set, and now it's time to execute.

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4 Likes

Medium

Image Credit: Medium

AI Product Management 101 — Section 2: Planning & Requirements

The Minimum Viable AI (MVA) is emphasized as a way to prove the concept with minimal model power.
Creation of a one-page Data Spec, choosing a sourcing tactic, and scoring readiness are key steps in the process.
Weighted points from readiness scores will determine if the project is 'good to go' or requires changes.
A single fail is a setback, while two fails indicate the need for a pivot.
A lean squad is recommended for a six-month Minimum Viable Product (MVP) with a budget overview and macro timeline.
Starter documents mentioned include a Data-Processing Agreement, model card template, risk log, and rollback Standard Operating Procedure (SOP).
Plans to transform the data spec into a demo within 48 hours using off-the-shelf models and fail-fast checklists are highlighted.
Contact information for further engagement is provided at the end of the article.

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Scrum-Master-Toolbox

159

Agile in Construction: Why Construction Teams Need Product Owner Thinking with Luca Cotta Ramusino

Luca Cotta Ramusino discusses the importance of applying the Product Owner role in construction and thinking like a customer to define value.
A great Product Owner in construction acts as a customer value detective, focusing on tasks that bring value to the customer and transforming project planning.
Conversely, a bad Product Owner in construction allows waste to persist, fails to engage customers effectively, and completes tasks without delivering real value.
The Last Planner Method is referenced in the discussion.
The podcast 'Scrum Master Toolbox' highlights the importance of coaching in the fintech industry for success.
An engaging story titled 'Shift: From Product to People' is recommended on Amazon by the podcast.
Luca Cotta Ramusino is a Lean advocate in the construction sector, guiding teams through agile transformations, and exploring lean and agile methods' potential.

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9 Likes

Medium

238

Image Credit: Medium

A Call to Product Leaders: If You Don’t Fund Discovery, You’re Not Funding Product Thinking

Product leaders are reminded that without funding discovery, they are not truly supporting product thinking.
Teams making decisions without learning in sprints rely on assumptions, not insights.
Many product professionals are overwhelmed with delivery tasks and lack time for understanding if their decisions address the right problems.
Discovery, the process of learning before building, is essential for reducing risk and aligning on goals.
Lack of discovery indicates a lack of team empowerment and highlights a leadership and system issue.
Product leaders are advised to start small with discovery efforts to enhance decision quality and clarify outcomes.
Product discovery is crucial even for projects, migrations, and platform initiatives, not just design-driven apps.
Teams should make space for exploring alternatives, interacting with users, and de-risking ideas to build products effectively.
Incorporating learning goals alongside delivery KPIs is key to emphasizing the importance of discovery.
Allocate time for assumption mapping, user interactions, and exploration as part of every iteration, not just as an add-on.
Encourage narrative discussions on discovery in various leadership forums and empower teams to prioritize tasks based on value and outcomes.
Utilizing AI tools can aid in accelerating analysis but should not replace direct interactions with stakeholders for meaningful insights.

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14 Likes

Medium

Image Credit: Medium

Designing Games with Figma

Alexia, a game designer, uses Figma for designing games and has worked on various projects including Grift: Scam Tycoon.
She authored a book on video game design, 'Video Game Design For Dummies', and released an interactive puzzle book called 'Where are the grackles?'.
Figma is preferred by many game companies for its speed, collaboration, and visualization capabilities.
In the development of Grift, Figma was used extensively for creating UI mockups, character pieces, charts, layouts, and overall system mapping.
Style guides were crucial in maintaining consistency, and Figma was used to establish visual rules, color palettes, iconography, and UI elements for the game.
The avatar builder feature in Grift was designed using Figma, allowing for easy testing of different combinations and seamless collaboration with artists.
Quick diagrams in Figma helped the team align on game systems before implementation, and core screens were mocked up to define interaction states and game flow.
Playtesting was emphasized, with Figma even used to create clickable hotspots for early user feedback on game flow before Unity builds.
Game development focuses on feelings and engagement, requiring extensive playtesting, tweaking, and ensuring the overall experience is enjoyable.
Alexia's journey into game design started with game jams, emphasizing the importance of fast-paced, creative projects for skill development and portfolio building.

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Logrocket

203

Image Credit: Logrocket

Leader Spotlight: Balancing trust and speed in digital banking, with Jyoti Menon

Jyoti Menon is experienced in product management, strategy, and development in financial services, currently VP at Bread Financial.
She emphasizes the importance of trust and modern product elements like speed and user experience.
The shift in competition now includes digital solution providers due to changing consumer expectations.
Adapting to customer expectations for instant gratification is crucial for digital product development.
Maintaining trust through value propositions and security measures is essential in differentiation.
Balancing strategic vision with market agility is key, highlighting the uniqueness of businesses and customers.
Legacy mindsets and regulatory barriers can hinder the implementation of faster digital experiences in banking.
The importance of iterative development and customer-centric approach to enhance overall banking experiences.
Balancing speed, user trust, and seamless processes in product design requires strategic use of data and personalized insights.
Communication, frequency, and channel choice are crucial for successful personalization in digital banking.

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Medium

Image Credit: Medium

Using AI in Product Discovery — How to Learn, Validate and Prioritise Faster

User feedback overload is a common challenge for product managers.
Modern product managers are turning to AI to speed up feedback analysis and prioritize tasks.
AI tools are being used by companies like Airbnb to categorize feedback automatically.
AI is not limited to product management; it is also utilized in education, restaurants, and content creation.
AI can differentiate between positive and negative feedback and provide insights on the reasons behind them.
AI helps predict user reactions and preferences based on existing data, similar to how Netflix chooses thumbnails.
AI can simulate virtual users for testing purposes, eliminating the need for traditional focus groups.
AI aids in prioritization by recommending features based on user engagement data, as seen with Spotify.
AI reveals patterns and correlations in user behavior that humans might overlook, guiding product roadmap decisions.
Various AI tools are available for feedback analysis, predicting user behavior, and prioritizing product features.
The collaboration between humans and AI is crucial for efficient product discovery and decision-making.

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Medium

345

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Navigating the Startup Journey: How to Achieve Product-Market Success

David Hirschfeld, CEO of Tekyz, shares insights on common pitfalls B2B software startups face and strategies for achieving product-led growth, emphasizing early product-market fit validation and pre-launch sales.
Hirschfeld highlights the importance of falling in love with the problem, not the solution, and warns against freemium models for startups, advocating for charging for core value from the start.
His 'Launch First' methodology prioritizes a narrow early adopter niche, high-fidelity prototypes, and pre-launch sales to validate product-market fit through revenue generation.
He distinguishes between product solution fit and product-market fit, emphasizing sales validation for the latter.
Tekyz offers comprehensive development services, focusing on problem-solving and understanding customer pain points through a data-driven approach.
Hirschfeld advises founders to understand early adopters, focus on problem statements, leverage pre-launch sales, and prioritize product solution fit for successful product launches.
The discussion provides valuable insights for B2B startups and emphasizes the importance of problem-centric development, strategic go-to-market approaches, and early validation.
David Hirschfeld shares practical advice for achieving product-led growth and can be contacted at [email protected] or on LinkedIn for further insights.
Tekyz plans to launch two AI applications: one for automating the Launch 1st Methodology Niche Analysis and Estimiz, an AI-based project estimation tool.
Outside work, Hirschfeld enjoys golfing and woodworking, showcasing a well-rounded persona beyond his professional endeavors.
For more information about Tekyz's AI services and David Hirschfeld, visit tekyz.com or connect with him on LinkedIn.

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