MVP vs MLP

Why 'Lovable' Beats Just 'Viable' in an AI-Powered World

Building a startup today is like cooking for picky eaters.
Sure, you can serve something edible — but wouldn’t you rather serve something irresistible? The same distinction exists between building a Minimum Viable Product (MVP) and a Minimum Lovable Product (MLP).

And in an era where AI makes good enough easy, "viable" just doesn’t cut it anymore.
You need to be lovable. You need to spark joy.
Even in B2B SaaS. Even if your product is "serious."
Especially if your product is serious.

Let’s talk about why.

MVP vs MLP: What’s the Difference, Really?

An MVP is the absolute scrappiest version of your product that still solves the core user problem.
It’s a quick proof: Does anyone even want this?
It’s fast. It's cheap. It’s usually ugly.
It’s your basic "Hey, does this make sense?" pancake.

An MLP?
Still lean. Still sharp. But now you’re not just solving the problem — you’re solving it in a way that makes users feel something.
A little delight. A little magic. A little “wait, where has this been all my life?” feeling.

MLP is when your pancake comes with maple syrup, butter, and maybe a sprinkle of cinnamon, not because it's expensive, but because it makes people want to come back.

In other words:

• MVP asks: Does this work?

• MLP asks: Will someone miss this if it disappears tomorrow?

Quick Table: MVP vs MLP

(This is the most basic TL;DR of everything else here!)

MVP Culture Helped Us Ship Faster, But It Also Created New Blind Spots

Look- MVP thinking made sense when building things was hard.
Server space was expensive. Tools were clunky. Engineers were scarce.
You needed to ship fast, fail faster, and find any traction you could.

But that world is gone.

Today?

• You can spin up a functional backend in an afternoon.

• You can AI-generate landing pages, onboarding flows, even product tours.

• You can A/B test your way to infinity.

The cost of building has collapsed.
But weirdly, the cost of boring users has skyrocketed.

In a world where switching products is one tap away, and "AI can do this for me" is the baseline expectation, functionality alone is not enough.
You don’t win by being useful.
You win by being loved.

WTFund Roadshow Diaries: What Founders Are Getting Right (and Wrong)

Over the past few weeks, running the WTFund roadshow across cities, listening to 100+ young founders pitch their hearts out, I saw a beautiful pattern:

1. MVP quality is up — Products are better, faster, smarter, right out of the gate.

2. Problem validation is happening faster — Founders are talking to users earlier, testing assumptions better.

3. Energy is insane — Indian founders today are fearless, scrappy, and ambitious in a way that feels genuinely historic.

But...

There’s still one blind spot:
User love is an afterthought.

Here’s what’s happening:

• Founders validate that a problem exists.

• They build something that works.

• But they don’t check if it delights.
  And that gap is deadly.

Why?
Because products that solve real problems, but suck to use, end up as freemium graveyards.
You get users who’ll tolerate you when you’re free… but won't pay.
You get usage without loyalty.
You get install-and-abandon cycles.

In short: You build a bridge, but no one wants to cross it.

And in 2025, in a world drowning in apps, plugins, and AI hacks?
If you don't emotionally hook users, someone else will.

AI: The Best Friend and Worst Enemy of Mediocre MVPs

AI democratized building. That’s incredible.
But it also raised the bar permanently.

Because if a user sees your tool and thinks,
"I can build something similar in a weekend with ChatGPT and Framer,"
You've already lost.

Today’s AI-powered users expect:

• Speed (baseline)

• Personalization (preferred)

• Delight (non-negotiable)

MLP isn't optional anymore. It’s survival.

Real-World MLPs (That Used AI to Win Hearts)

Let’s look at some real startups and companies that used AI to reach MLP faster, creating tangible (even measurable) delight for their users. These examples span both consumer (B2C) apps and business (B2B SaaS) tools, proving that joy and user love can be central even for “serious” products:

• Duolingo (B2C EdTech): Duolingo started as an MVP: a simple language-learning app offering bite-sized exercises. It worked, but the reason people got hooked was the fun, gamified experience (streaks, the goofy green owl mascot, leaderboards – Duolingo basically made learning feel like a game). The team always cared about delight, and now they’re leveraging AI to amp it up. In 2023, Duolingo introduced GPT-4 powered features in a new tier called Duolingo Max. One feature, Roleplay, lets users practice conversations with an AI chatbot in scenarios like ordering coffee in Paris – essentially giving learners a playful virtual language partner. Another feature, Explain My Answer, uses AI to provide personalized feedback when you make a mistake​. These AI additions turn what could be a dry quiz app into a dynamic, interactive tutor that adapts to you. Duolingo’s ability to quickly integrate cutting-edge AI (thanks to partnering with OpenAI) meant they could deliver an MLP-level experience without waiting years to develop such sophisticated tech themselves.

• GitHub Copilot (B2B Dev Tool): On the surface, writing code is serious business, but even developers love a little delight. GitHub Copilot is an AI pair-programmer that uses OpenAI’s models to auto-suggest code as you type. Essentially, it took the MVP of “AI-assisted coding” (the underlying AI model that could complete code) and wrapped it into a product developers could easily use in their editor, making it instantly lovable by solving tedious coding tasks with uncanny ease. The impact was huge: developers started raving about how fun and efficient coding became with Copilot. Studies showed that developers using Copilot could code up to 55% faster, and more importantly, they reported feeling more productive, more fulfilled, and less frustrated while coding​. In a 2023 survey, 92% of developers said they enjoy using AI coding tools and that these tools improved their satisfaction at work​. Talking about measurable delight – Copilot helps prevent burnout (41% of devs said AI tools help prevent burnout) by taking away the boring parts of coding​.

• Grammarly (B2C/B2B Writing Assistant): Grammarly used natural language processing to create a writing assistant that started as a basic grammar checker MVP and evolved into a must-have, lovable product for millions. It doesn’t just catch typos; it gives gentle suggestions to improve clarity and tone, almost like a friendly editor looking over your shoulder. By continuously improving its AI and UX, Grammarly made the experience of editing feel supportive rather than critical. The numbers tell the story: Grammarly now has over 30 million daily active users and 50,000+ teams using it in workplaces​. They even added fun weekly writing stats for users and upbeat encouragement in the app – little delightful touches on top of the heavy AI lifting under the hood. By using AI to constantly adapt suggestions to each person’s writing style, Grammarly delivers a personalized, almost human-like guidance that makes the user feel taken care of.

These examples show that whether it’s consumer apps or B2B software, adding a dash of AI-driven smarts and a heaping spoonful of user-centric design can fast-track your product to lovable status. The common thread is delight. Each product didn’t stop at solving a problem; it found a way to make the solution enjoyable, often with help from AI to scale that experience. And when users genuinely love your product, they stick around and tell their friends. (Free marketing, yay!)

Measuring Love (Because Time-on-App Isn’t Enough)

One of the biggest mistakes I see young founders make:
Thinking "time spent in app" equals love.

It doesn’t.

Someone could be stuck, frustrated, hate-using your product for 30 minutes.

Better metrics to track love:

• NPS: Would they recommend you, unprompted?

• PMF Surveys: How disappointed would they be if you disappeared tomorrow?

• Organic Advocacy: Are users tweeting, posting, or bragging about you without you asking?

• Community Behavior: Are users creating memes, jokes, fan content? (Hint: If you’re getting roasted lovingly, you’ve made it.)

Community: Your Secret Weapon for MLP

One massive insight from watching great early-stage companies:
Lovable products aren’t built alone.

They’re built:

• With beta testers.

• With loud, opinionated early adopters.

• With a tiny cult that feels like insiders, not customers.

How to build with community:

• Let users vote on features.

• Share early designs openly.

• Celebrate user wins loudly.

• Turn feedback loops into collaborative loops.

At WTFund, we’re seeing it again and again:
Founders who treat users like co-creators, not consumers, build stickier, stronger brands — even before they raise serious money.

How You Can Build Your MLP (Starting Today)

1. Choose your emotional trigger early.
Not just what you're building — but how you want users to feel.
Joy? Relief? Belonging? Power?
Lock it in.

2. Ruthlessly prioritize magic moments.
Your V1 needs one thing users screenshot, tweet, or text their friends about.

3. Use AI for polish, not just speed.
Don’t just AI your way to a working backend.
AI your way to a magical frontend.

• Smarter onboarding flows.

• Personalized nudges.

• Delightful chat support.

4. Set up love metrics, not just traffic metrics.
Launch with a lightweight NPS survey from Day 1.
If no one's recommending you without being paid to, you haven’t hit MLP yet.

5. Involve your users early and often.
Let them feel ownership.
People don’t just stay where they're helped.
They stay where they're heard.

6. Build slower if you have to, but build stickier.
Rushing to MVP is easy.
Crafting an MLP takes slightly more time, but buys you years of loyalty.

Closing Thoughts (For and From My WTFund Founders)

As a young founder hustling in 2025, you’re likely moving a mile a minute to get your product out. It’s tempting to just crank out an MVP, throw it at users, and see what breaks. And sure, speed is crucial, but remember: an MVP that only checks the functionality box might get lost in the crowd. Today’s users expect more. The great news is that with AI and modern tools at your disposal, you can aim higher from the start. You can build a product that’s viable and lovable without a 500-person team or a decade of work.

Think of AI as your co-founder that insists on better UX- from auto-personalizing content to crunching user feedback faster, it helps you polish the experience in ways that used to require lots of time and people. In an era where “products must feel good to use” to stand out, there’s no reason to settle for a lackluster app hoping users will stick around until you make it better “someday.” Delight isn’t a luxury; it’s becoming a baseline.

So, whether you’re building the next big consumer app or a hardcore enterprise SaaS, keep your eyes on the prize: user love. Obsess over your users- understand their needs and also what makes them smile. Use MVP tactics to get feedback early, but infuse MLP thinking to deliver joy and value hand-in-hand.

In the end, viable products may get users in the door, but lovable products get them to move in and invite their friends. So go on, be bold: build that Minimum Lovable Product and give your users a reason to fall in love at first login. Remember that the things that win are the ones that make people feel alive.

MVPs are survival.
MLPs are the future.
You’re not racing to ship the first version anymore.
You’re racing to create the first thing someone loves enough to tell the world about.

Build that.
We’re rooting for you!

P.S.: Applications to C1/25 of WTFund are NOW LIVE. Apply here.