Minimum Viable Product is a development approach grounded in lean startup principles. Introduced by Eric Ries, it emphasizes learning through direct interaction with real users instead of relying on assumptions or internal opinions.

Lean Startup Foundation

At its core, MVP follows the Build → Measure → Learn feedback loop. This cycle represents a fundamental shift from traditional product development, moving from an Idea → MVP → Data → Idea process that prioritizes learning over building.

An MVP is not about cutting corners or building less. It is a focused version of a product that helps a team learn what works by testing with actual users. The goal is to validate key assumptions early, using the simplest version possible to gather meaningful insights.

Key Elements

• Product Discovery: Understanding customer problems and needs before building solutions.

• Hypothesis Formation: Creating testable assumptions about your value proposition, customers, channels, and relationships.

• Backlog Management: Prioritizing features based on learning objectives rather than feature completeness.

Minimum Viable Product follows iterative and incremental development. Instead of aiming for a perfect product from day one, teams build in small steps, learning and improving as they go. This approach reduces risk and increases the speed of validated insights.

• No Big Bang Delivery: Avoid building in isolation and launching everything at once. Large releases often rely on assumptions and leave little room for adjustment.

• No Unfinished Products: Each release should be complete and functional. Even early versions must deliver a real, usable experience for the customer.

• No Minimum Releasable Crap (MRC): An MVP is not an excuse to ship poor quality. Early users should experience value, not broken features or placeholders.

• Start Small: Begin with the smallest possible solution that delivers value. Focus on solving a real problem in the simplest way.

• Delivering Less: Instead of more features, focus on the core need. The goal is to find the cheapest and fastest way to solve the customer’s problem.

The aim is not just to release quickly. It is to build the Earliest Testable, Usable, and Lovable Product. A version that is complete enough to use, clear enough to test, and valuable enough to matter. This is the fastest path to learning what works.

What is True MVP?

A true MVP balances minimal effort with real value. It is not just a stripped-down version of the product, but a version that delivers enough for users to experience the core value and for teams to learn what matters.

A good MVP has four essential traits:

1. Functional: The core functionality works as expected. It solves a clear problem and delivers on its main promise.

2. Reliable: It performs consistently. Users should not face major issues, crashes, or failures that break trust.

3. Usable: The experience should be simple and intuitive. Users must be able to complete the main task without friction.

4. Empathic Design: Even early versions should show an understanding of the user’s needs, context, and environment. Design choices should reflect real usage patterns.

Teams can simulate the underlying technology behind the scenes. What matters is the experience from the user’s point of view. Focus on the outcome, not the polish.

A true MVP is a learning tool. Build just enough to test key assumptions. Use every iteration to gather feedback, improve direction, and move closer to product-market fit.

• Focusing on “Minimum” Over “Viable”: Stripping too much and forgetting the product still needs to deliver real value.

• Feature Creep (Kitchen Sink Syndrome): Adding extras that dilute the core purpose and slow down learning.

• Sacrificing Security and Privacy: Skipping essential protections to save time puts users and the product at risk.

• Moving Too Slowly: Waiting for perfect delays feedback and learning. Shipping early matters.

• Building for Everyone: Trying to please all users usually means solving nothing well.

• Ignoring User Feedback: Collecting feedback is not enough. Learning comes from acting on it.

Not all MVPs involve writing code. The best type depends on what you need to learn, how much risk you’re managing, and what resources you have. The goal is always the same: learn fast with the least effort.

Manual and Simulation-Based MVPs

• Piecemeal MVP: Built using existing tools and solutions instead of developing custom technology. Combines off-the-shelf tools to deliver value without building custom tech.

• Wizard of Oz MVP: Users interact with what looks like a finished product, but tasks are done manually behind the scenes.

• Concierge MVP: A fully manual service for a small group. Lets you observe real user behavior and refine your solution.

• Email MVP: Delivers the product value manually using emails. Great for services or subscription ideas.

Validation-Focused MVPs

• Landing Page MVP: Simple page that explains your product and measures interest through signups or clicks.

• Fake Door MVP: A page or feature that invites users to try something that doesn’t exist yet. Used to test demand.

• Pre-order MVP: Tests market demand by accepting orders before the product exists, validating willingness to pay and providing funds for development.

• Explanatory Video MVP: Demonstrates how the product works using a short video. Useful for complex or technical ideas.

• Audience Building MVP: Focus on building a community around the problem space before launching the product, creating a ready customer base.

• Marketing Campaign MVP: Run ads to test messaging, positioning, and demand before launch.

Product-Focused MVPs

• Single-Feature MVP: Focuses on one feature that delivers core value. Keeps the build small and learning clear.

• No-Code MVP: Use no-code tools to build and launch a working version without writing code.

• Content MVP: Use tools, guides, or educational content to solve user problems and test engagement.

• Crowdfunding MVP: Using platforms like Kickstarter or Indiegogo to validate demand and secure funding simultaneously.

The best MVP is the one that helps you test your riskiest assumption, in the shortest time, with the least effort. Start small. Focus on learning. Let data shape the next step.

The MVP is not the only way to approach early product development. Over time, new frameworks have emerged to address the limitations of MVP thinking, especially in areas like emotional engagement, business value, and market readiness.

Here are the most relevant concepts product managers should know:

Simple, Lovable and Complete (SLC)

The SLC approach argues that MVPs often set the bar too low. Instead of delivering something that just barely works, SLC encourages teams to ship a small product that feels complete, delightful, and well thought out.

• Simple: solves one clear problem

• Lovable: feels good to use

• Complete: no broken parts

Use SLC when you want to test a narrow idea with high polish, especially in markets where expectations are high and first impressions matter.

Minimum Awesome Product (MAP)

MAP expands on MVP by adding a layer of delight. It’s not enough for a product to be viable, it has to spark excitement. MAP encourages teams to create products that feel refined and useful, even if limited in scope.

• Clear focus and good design

• Memorable details

• Strong early engagement

Use MAP when your users expect great UX out of the gate or when your product depends on strong emotional engagement to succeed.

Minimum Marketable Product (MMP)

The MMP goes a step beyond learning. It’s a product that is ready to be sold. The goal is not just to validate assumptions, but to create a product that can generate real revenue, even if it’s still early-stage.

• Strong value proposition

• Polished user experience

• Enough to launch publicly

Use MMP when you need to ship something to paying customers or you’re preparing for a full-scale go-to-market launch.

Minimum Lovable Product (MLP)

The MLP focuses on emotional connection. It builds on the MVP by asking not just “is it viable?” but “will users love it?” The goal is to deliver a version of your product that creates a spark. Enough joy, excitement, or satisfaction that users talk about it.

• Focuses on joy and satisfaction

• Builds early loyalty

• Encourages sharing and feedback

Use MLP when you want early users to become advocates, or when emotional engagement is key to product success.

MVE focuses on the full experience surrounding your product. It includes the product itself, along with branding, marketing, sales, onboarding, and support. The goal is to create a smooth, trustworthy experience from the first touchpoint.

• Covers product, support, and communication

• Builds brand trust and emotional connection

• Improves retention through a complete experience

• Fits into user habits and tech ecosystems

Use MVE when you want to stand out through experience, not just functionality, especially in competitive or saturated markets.

MBI is a strategic approach often used in enterprise and scaled agile environments. It represents the smallest chunk of business value that can be delivered to a specific segment and quickly provide ROI.

• Connects to business goals

• Drives measurable results

• Fits into scaled delivery plans

Use MBI when you’re working in a larger organization with formalized delivery pipelines and need to tie output directly to business impact.

Minimum Marketable Feature (MMF)

An MMF is the smallest deliverable unit of value that can be released on its own and still provide benefit to the user. Instead of building an entire MVP or product, teams ship a single feature that stands on its own.

• Fast to build and release

• Focused on one outcome

• Reduces time to feedback

Use MMF when you want to validate one specific capability or value proposition without the weight of a full product build.

Popularized by Intercom, the cupcake metaphor teaches teams to avoid shipping “ingredients” like icing or flour. Instead, build a full mini-version of the product. A cupcake instead of a future wedding cake.

• Feels whole and usable

• Solves one real problem

• Good for learning and delivery

Use the cupcake model when you want to create something end-to-end that users can enjoy and that gives you complete learning across UX, delivery, and messaging.

MVP development is fundamentally about systematic experimentation, not traditional product building. The process emphasizes learning through trial and error, using the smallest possible experiments to test the riskiest assumptions with real customers.

8-Step Development Guide

1. Formulate the problem and determine your value proposition: Clearly articulate the customer problem you're solving and how your solution provides unique value.

2. Define the audience and highlight its core: Identify your primary target segment and understand their specific characteristics and needs.

3. Analyze your competitors: Study existing solutions to understand market gaps and differentiation opportunities.

4. Define a user journey map: Map out how customers will discover, try, and use your product to achieve their goals.

5. Make a list of functions, graded by priority: Use frameworks like MoSCoW (Must/Should/Could/Won't) to prioritize features by importance.

6. Determine the scope of the MVP: Apply the Pareto 80/20 principle—MVP equals Essential plus Simple. Focus on the 20% of features that deliver 80% of the value.

7. Assemble a team and develop an MVP version: Build your lean, cross-functional team and create the minimum viable solution.

8. Run Alpha and Beta tests, gather feedback and analyze data: Test with internal users first (Alpha), then with external customers (Beta), systematically collecting and analyzing feedback.

Trial and Error Loop

• Identify your riskiest assumption: What could make your product fail? Focus on assumptions about customer needs, solution viability, or business model sustainability.

• Find the smallest possible experiment: Design the cheapest, fastest way to test your assumption. This might be a survey, prototype, or simple landing page.

• Use results to course correct: Based on what you learn, either pivot your approach or double down on what's working. Never ignore the data.

Effective MVP development requires disciplined backlog management. Prioritize features based on learning value, not just user requests. Each feature should either validate a critical assumption or provide essential functionality for the core user journey.

Remember: MVP development is an iterative process of hypothesis formation, experimentation, and learning. Success comes from building the right thing, not building everything right the first time.

Product Vision & Planning

Backlog Management

Backlog

Prioritization

Rank Key Features By Key Metrics

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The most successful companies today started with remarkably simple MVPs that focused on core value rather than comprehensive features. These examples demonstrate that MVP success comes from solving real problems elegantly, not from building everything at once.

Technology Giants

• Spotify (2006): Started with the ability to find and play just a few hard-coded songs. The focus was on proving the streaming concept and user experience, not building a massive music catalog.

• Facebook (2004): Began as a social network exclusively for Harvard students. This constraint helped validate the core social networking concept before expanding to other universities and eventually the world.

• Twitter (2006): Launched as an SMS service for a closed community, testing whether people wanted to share short updates with friends. The 140-character limit came from SMS constraints, not design choice.

• Amazon (1990s): Started as an online bookstore with AI-powered recommendations that were initially just hardcoded product suggestions. This proved online retail viability before expanding to other categories.

Creative Validation Approaches

• Dropbox: Drew Houston created a simple video demonstrating the file-sync concept. People signed up for the actual product based on this video alone, proving demand before building the complex infrastructure.

• Zappos: Started by photographing shoes from local stores and posting them online. When orders came in, they'd buy the shoes retail and ship them, testing e-commerce demand without inventory investment.

• Airbnb: The founders tested the concept by renting out rooms in their own apartment, manually managing the entire experience to understand what hosts and guests really needed.

Focused Execution

• Minecraft: Markus Persson created an ugly, blocky 3D landscape in just 6 days of coding. The simplicity became a feature, and the game's creativity-focused core drove massive adoption.

• Virgin Air: Richard Branson started with just a single route, but made that experience complete and excellent. Small scale, but fully functional and customer-focused.

• Slack: Began as an internal team messaging tool for the company's own workers. They refined it based on their daily use before releasing it as a product.

• Supreme (1994): Launched with streetwear style, astronomical prices, limited runs with small inventory, and strategic collaborations. This scarcity model became their entire brand strategy.

These success stories share common themes: they started small, focused on core value, validated with real customers, and iterated based on feedback. Most importantly, they solved genuine problems rather than building features for their own sake.

AI tools now make it possible to go from an idea to a functional MVP in hours. Product managers can describe features in plain language and receive interactive outputs without needing to write code or manage full development setups.

Lovable is one of the most efficient tools for quick, high-quality prototypes. It works well with natural language, requires no setup, and produces reliable results. Suitable for both early-stage ideation and more advanced use cases.

• Fast, accurate results with clear UI

• Free plan is sufficient for most needs

• Integrates with Supabase and Figma

• Chat mode allows for discussion without changing the prototype

• Agent Mode shows potential but adds little benefit in simple cases

Best for building solid early prototypes quickly and without friction.

Bolt.new offers a clean interface and delivers strong results similar to Lovable. It supports quick project duplication and offers useful integrations. Ideal for PMs who need to create variations of a prototype or work across flows.

• Easy to use with no setup

• Integrates with Supabase, Stripe, and Figma

• Allows fast cloning of prototypes

• Output is stable and well-formatted

Performs on par with Lovable, with added convenience for reusing and managing multiple versions.

V0.app focuses on speed and simplicity, making it a good fit for lean MVPs. It delivers consistent results for straightforward front-end structures. Best used for clean, minimal prototypes without much customization.

• Works quickly with minimal errors

• Good Supabase support

• Clean UI but limited flexibility

• Fewer collaboration or workflow features

Delivers fast prototypes with minimal effort, slightly less flexible than Lovable or Bolt.

Replit is a technical tool with broad capabilities but is not ideal for quick MVPs without code experience. It often prompts backend setup even for simple tasks. Best for engineers who want AI-assisted scaffolding, not no-code output.

• Requires technical setup even for UI tasks

• Prompt flow is complex

• Free version is limited

• Wide range of integrations available

More suited for developers; not practical for fast MVP prototyping without support.

Vibe coding is a hands-on approach that uses AI coding agents like Cursor, Claude Code, or ChatGPT to generate front-end prototypes from natural language prompts. Instead of relying on ready-made builders, you describe the flow or upload a PRD, and the AI creates HTML, CSS, and JS that run locally.

This approach gives more control, especially when working with internal design systems or specific UI needs.

Cursor and Claude are strong options for working directly with your own components. ChatGPT is useful for lighter builds and quick HTML-based flows. Tools like Figma Make help bridge design and development, especially when handoff to designers is part of the workflow.

These tools require a bit more effort but offer flexibility and better alignment with how your actual product works.

Strategic Impact

Software Engineering

Artificial Intelligence

Prompt Engineering

Use Prompting to Automate Processes

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For those without technical backgrounds:

• Start with tools like Lovable or Bolt that offer fast, reliable results

• Avoid platforms requiring backend setup unless developer assistance is available

• Use minimal visual styling to signal that it’s a prototype

• Focus on testing flows, structure, and usability rather than visual perfection

These tools are most valuable when validating UX ideas, reviewing layout concepts, or preparing quick demos. They are not replacements for production-ready builds but serve as an efficient way to explore and communicate product direction.