Founders who sold a B2B MVP ( code / IP / design ) before having real users/customers - How did you actually do it?

Many orgs have the resources to build what you are trying to sell. How did you overcome the Build vs Buy barrier?

Would love to hear more about the below:

• What you showed in demos if the product wasn’t fully ready
• How you handled the “do you have customers yet?” question
• What made prospects trust you enough to buy/pilot
• Licensing Strategies
• Were they charged immediately or started with pilots/LOIs
• What surprisingly worked (or completely failed)

Context: Trying to understand what early enterprise selling looks like before traction exists. Thank you.

Would YC even look at a company like ours?

Genuinely asking because I’m getting mixed opinions.

We’re a bootstrapped manufacturing software company from India. Started in 2017. Profitable. Around ₹3 Cr revenue this year (~$350k), and roughly 3x growth over the last couple of years.

We build software used inside factories. Started with MES-type use cases, but over time it has expanded into production monitoring, OEE, traceability, quality workflows, maintenance workflows, machine integrations, and other plant digitization use cases.

Customers are in automotive, electronics manufacturing, and industrial sectors.

One thing I want to clarify upfront: this is not a services/staff augmentation business.

We already have a product platform running across multiple customers. Deployments are handled by our delivery team, not founders. Yes, implementations involve configuration, integrations, and some customization because factories are messy and every plant has its own realities. But that’s true for most enterprise software.

A typical customer journey for us:
started with 1 production line, then 5, then eventually 20 lines on the same platform.

Now the obvious pushback is: this space already has big players.

Tulip has raised huge funding. Then there’s Siemens, SAP, Rockwell, and many MES players in India too.

So I’m not pretending we discovered some untouched category.

Another thing we’re working on internally is using AI to reduce deployment/customization effort. One of the painful parts of industrial software is customer-specific configuration and workflow changes. We’re experimenting with AI-assisted workflow generation / configuration support / faster customization to make deployments increasingly productized.

Today our growth is mostly referrals, repeat business, and founder network.

No proper outbound sales, GTM, channel strategy, content engine, no repeatable lead generation.

If we stay bootstrapped, we’ll probably keep growing, but slowly, mostly in India.

If we raise, the goal would be building an actual growth engine and eventually expanding beyond India.

One thought I keep having:
if the exact same product with similar customer traction was selling into the US at US industrial software pricing (say closer to Tulip-type ACVs), the revenue profile would look very different.

So my actual question:

Does YC see something like this as:

• a scalable vertical SaaS business
• too implementation-heavy
• too crowded
• more of a strategic investor / PE type business
• or something potentially venture fundable with the right positioning

Would appreciate honest feedback, especially from people who’ve seen enterprise / industrial SaaS up close.

“Teachers/mentors in the startup space — how do you handle these problems?

1. What questions should you ask when running a beta test?
2. What kind of app should you build — one that solves people’s problems vs. one that goes viral?
3. How soon should you throw your MVP into the market? Is it okay if it’s not perfect?
4. When you get beta feedback and people’s vision turns out to be different from yours, should you immediately change your vision?”

I was on Product Hunt and came across a launch that is currently ranked #2. It was hunted by Garry Tan, and the product seems to be backed by a team that went through YC.

My question is: To get Garry Tan as hunter, do you need to be a YC founder/team? Or is it possible even if you are outside the YC network?

Thanks a lot !!

For reference, I applied and I got this email 30 minutes later...

<no-reply@ycombinator.com

Welcome to Startup School!

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So I am building software that helps mid market construction businesses who aren't big enough but also not very small. But having a hard time getting a pilot agreement most of them don't have email and I target US based firms especially in California and Texas so can't really do walk in or cold call.

How to reach out to them ? Good ways as non us founder

I’m building a company, but the only differentiation i have from competitors is price. Is that enough for customers?

Pitching b2b right now is an absolute nightmare if your stack is just a standard llm. corporate compliance will literally laugh you out of the room if your product can hallucinate a workflow error even 1% of the time

We are basically being forced to pivot to strict reasoning architectures. seeing theorem-proving agents like Aleph actually clear formal verification benchmarks makes it so painfully obvious where the real enterprise money is heading

building another api chat interface is just a waste of a seed round at this point tbh

I've been seeing the same posts 15 times a day about builders vibe coding a tool and realizing the difficult part is not build, but rather execution. So I wrote a post addressing it directly.

tldr: Building is the easy part. Most people think that they've been blocked by lack of technical skills and AI tools remove that block, only to realize that the actual work is not in building, but rather customer discovery and selling.

Founders have always loved the fantasy. Build something great, launch it, and customers will show up. Most learn the hard way that this almost never happens.

But AI coding tools have made the fantasy much easier to believe. And that’s the problem.

When building software took months, teams had natural friction. You had to choose carefully. You had to explain the idea to engineers. You had to prioritize. You had to justify why this thing deserved to exist before anyone spent six figures and a quarter of the year building it.

Now one person can open Cursor, Lovable, Replit, Bolt, v0, or Claude Code and create a polished app over a weekend.

That feels like magic.

It also makes it dangerously easy to skip the only part that ever mattered: finding a market that actually wants the thing.

“If you build it, they will come” was always wrong because customers don’t reward effort. They reward relevance.

People don’t care how long you spent building. They don’t care how elegant the architecture is. They don’t care that your app has a beautiful onboarding flow, a clean dashboard, and a clever name.

They care whether you solve a painful problem at the exact moment they feel it.

Before AI coding tools, founders still fell into the build-first trap. But they hit constraints early.

A non-technical founder had to find a technical cofounder or hire engineers. A technical founder had to spend nights and weekends grinding through implementation. A team had to choose between features because engineering time was scarce.

Those constraints forced some thinking.

A founder would ask:

“Is this worth building?”

“Who exactly needs this?”

“Will they pay?”

“How will they hear about it?”

“What will make them switch?”

AI removed much of that friction. Now the question has quietly changed from “Should we build this?” to “Can we build this?”

And the answer is almost always yes.

That’s where people get in trouble.

Vibe coding creates the illusion of progress.

AI coding tools compress the distance between idea and output.

You describe the app. The tool creates the interface. You ask for auth. It adds auth. You ask for Stripe. It wires in payments. You ask for a dashboard. It gives you charts, filters, empty states, and a gradient that looks like every YC company from the last three years.

Within hours, you have something you can click.

That click is addicting.

A clickable product feels like progress because humans like tangible things. A Figma mockup feels more real than a positioning doc. A working app feels more real than ten customer calls. A demo feels more real than a distribution plan.

But “real” is doing too much work there.

You can have a real product and zero real demand.

You can have a login screen, billing page, onboarding checklist, and database schema before you have one sentence that makes a buyer say, “I need this now.”

AI makes it easier to build real software before you’ve found a real reason for anyone to care.

The cost of building dropped. The cost of attention did not.

AI has lowered the cost of software creation. It has not lowered the cost of distribution.

If anything, distribution has become harder.

Everyone can ship now. Everyone can generate a landing page. Everyone can create screenshots. Everyone can post “I built this in 48 hours” on X. Everyone can publish a launch video, write a Product Hunt post, and produce ten LinkedIn carousels with the same slightly breathless tone.

The bottleneck moved.

The scarce resource is no longer code. It’s attention, trust, urgency, and belief.

Customers have more tools than they can evaluate. More demos than they can watch. More AI copilots than they can remember. More “all-in-one platforms” than they can distinguish from one another.

So when a founder says, “But the product works,” the market shrugs.

Of course it works.

That’s table stakes now.

The harder question is: why should anyone rearrange their day around it?

Vibe coding rewards the wrong founder instinct

Most founders already prefer building to selling.

Building feels safe. You control it. You can improve the product, fix bugs, add features, redesign the homepage, and convince yourself you’re moving forward.

Selling exposes you.

You have to ask someone to care. You have to hear confusion in their voice. You have to watch them ignore your follow-up email. You have to accept that the idea in your head may not survive contact with the market.

AI gives builders a perfect hiding place.

Instead of doing ten painful customer conversations, you can build ten more features. Instead of narrowing your buyer, you can create a flexible product that “works for lots of use cases.” Instead of writing a sharp positioning statement, you can ask the model to generate five landing page variants.

It feels productive.

It can also become avoidance with a beautiful UI.

The founder tells himself he’s iterating. But he’s not iterating on demand. He’s iterating on the object.

There’s a difference.

The market does not buy capability. It buys a specific change

AI tools encourage founders to build capabilities.

A CRM for creators. A dashboard for agencies. An AI assistant for real estate brokers. A research tool for investors. A workflow platform for operators.

All of these can sound plausible. Most will fail.

Why?

Because customers rarely wake up wanting “a capability.” They wake up wanting a specific change in their life.

They want to stop spending Sunday night preparing a board deck.

They want to answer customer emails without hiring another support rep.

They want to know which accounts are likely to churn before the renewal call.

They want to turn messy founder thoughts into five sharp LinkedIn posts before the baby wakes up.

That level of specificity matters.

A product built around a broad capability usually feels optional. A product built around a painful moment can feel urgent.

AI helps you build the broad capability faster. It does not automatically help you find the painful moment.

You still have to talk to people.

Annoying, I know.

The MVP is getting misunderstood

Founders used to define an MVP as the smallest thing they could build to test a market assumption.

Now many people treat an MVP as the fastest full-looking app they can generate.

That’s not the same thing.

A real MVP tests a risky assumption.

Will recruiters pay to find candidates this way?

Will accountants trust AI to draft client memos?

Will parents invite other parents into a private coordination app?

Will sales managers change pipeline review behavior if reps get automated coaching?

A vibe-coded MVP often tests something else:

Can I make the app work?

Can I make it look credible?

Can I connect the APIs?

Can I generate enough features that people understand the vision?

Those questions may matter later. They rarely matter first.

The first question is usually much more brutal:

Does anyone want this badly enough to do something inconvenient?

Pay. Switch. Migrate data. Invite a teammate. Change a workflow. Risk looking stupid. Reply to a cold email. Schedule a demo. Enter a credit card.

If they won’t do one of those things, your product may not have demand yet. It may only have applause.

AI also makes fake validation easier

Here’s the uncomfortable part: AI doesn’t just help founders build faster. It helps them manufacture the feeling of validation.

You can generate:

• A polished landing page
• A waitlist
• A launch post
• Customer personas
• Market research
• Competitor analysis
• Sales emails
• Testimonials placeholders
• Demo scripts
• Investor-style narratives

Some of that can help. But it can also create a movie set.

From the street, it looks like a company.

Walk behind the facade and there’s nothing holding it up.

The danger is not that founders use AI to support go-to-market work. They should. The danger is that AI can make weak evidence look strong.

A hundred waitlist signups from curiosity traffic is not demand.

A few “this is cool” replies are not demand.

A viral post from other builders is not demand.

A prospect who says “circle back next quarter” is not demand.

Demand looks like someone trying to pull the product out of your hands before it’s ready.

The new founder skill is not building. It’s sequencing.

AI does not make building irrelevant. It makes sequencing more important.

The best founders will not stop building. They’ll build in tighter loops around sharper market signals.

They’ll ask better questions before they open the editor:

Who feels this pain today?

What are they using now?

What happens if they do nothing?

Why have existing tools failed them?

Where do they already look for help?

What would make them switch this week?

What proof would they need before trusting us?

Then they’ll build the smallest artifact that tests the next assumption.

Sometimes that artifact is a product.

Sometimes it’s a landing page.

Sometimes it’s a concierge workflow.

Sometimes it’s a spreadsheet.

Sometimes it’s a five-line cold email.

The amateur uses AI to build the product he imagined.

The pro uses AI to test whether the market is real.

What founders should do instead

If you’re using AI coding tools, keep using them. They’re incredible.

Just don’t let speed trick you into skipping the work that speed cannot replace.

Before you build, write the sales email.

If you can’t write a clear email to a specific person with a specific pain, you probably don’t understand the market yet.

Before you add features, get someone to commit.

Not compliment. Commit.

Ask for money. Ask for a pilot. Ask for data access. Ask them to introduce you to the teammate who owns the problem. Ask them to use the ugly version this week.

Before you polish the UI, make the promise sharper.

A beautiful product with vague positioning loses to an ugly product that says exactly what the buyer already believes they need.

Before you call it an MVP, name the assumption.

If the build does not test a specific risk, you’re not learning. You’re decorating.

And before you celebrate how fast you shipped, ask the question founders hate:

Did anyone pull?

The paradox gets worse before it gets better

AI vibe coding tools will create a flood of software that looks finished but has no audience.

More apps. More dashboards. More wrappers. More “AI-powered” workflows. More weekend builds that feel like startups for about nine days.

But the same tools will also help serious founders move faster than ever.

The difference will not be who can build.

Everyone can build now.

The difference will be who can think clearly enough to build the right thing, for the right person, at the right moment, with the right path to reach them.

That’s the part AI has not automated.

Buiding shit from 4+yrs, 23, based in India. Been building since 16. Looking to join an early stage EU/US startup or MNC as a founding PM or PM.

Please Note: Using the power of this god-tier subreddit for something slightly unconventional today. hoping the YC internet council allows it. (Pls don't take my post down )

Experience

- Current: PM at an AI startup. Joined a month ago, the role turned out to be sales heavy with 0 product surface. Moving on.

- Prior: Frontend engineer at an enterprise AI company for \~1.5 years. Owned the agentic AI module end to end, built workflow configurators for business users, wrote an internal frontend framework that lifted team velocity.

- Before that: Consultant. Took ambiguous client requirements to delivered product. Scoping, timelines, demos, dev team management.

- Before that: Co-founded a hyperlocal commerce startup. Bootstrapped, ran for \~2 years, team of 20+ across product, eng, design, ops. Shipped two mobile apps (consumer + merchant), did 50+ customer interviews on the ground. Shut it down. Took the lessons.

First gig: dev intern out of college.

Products I have built (happy to walk through any of these on a call, keeping names off public posts)

- A restaurant review tool was live at 2 resturants with in Bangalore. Catches unhappy diners before they leave public reviews.

- A people discovery platform for my city. mutual-interest unlock model, no ads. This now has live users

- A zero-commission marketplace for real estate brokers. Dual-sided, broker tools + consumer property app.

- An automation tool for a financial services client. Cut a manual workflow from 2-3 hours to 10 seconds.

- A newsletter SaaS with AI writing, email infra, subscriber management, tiered pricing.

- An aviation community I built on Instagram at the age of 17. 0 to 12K followers organically, partnered with flight schools in India and the US.

Btw i was feeling alone in my city then i ran club nights and offline events in my city, pulled most of the crowd from Reddit. I write my own copy so distribution is part of the build for me, not a separate function.

Looking for:

- Founding PM or early PM, even at MNC works.

- Real product to own.

- Equity/ESOPS

- Decent compensation

- Async-friendly, no daily target chasing.

- Founders who want to build to sell or scale, and the - product has depth.

Open to wearing other hats too. Project mgmt, Hiring, ops, whatever the stage needs. I cannot sit idle, that is the only real requirement on my end.

DM me. Happy to share resume, portfolio, references, and walk through any of the products in detail.

The competitors app, like mine, is 100% free and has no ads/IAP:

(check play store "globo")

Somehow he managed to get to 100K downloads on android

While I am at 1k downloads:

(check play store "geochamp")

His product is worse. So it's definitely not the product that matters

We are both doing lots of reddit marketing, I checked. But he never created any viral post, and reddit marketing alone could NEVER lead to 100k downloads.

NOTE:

Even though is app is free, has no IAP & contains no ads I assume he invested a significant amount of money into running play store ads to get users?

... would be surprising to see someone invest money into running ads for an app that has no IAPs/ads (which is the case for globo & geochamp)

How much for 100.000 users would I need to invest? 10.000$ ? 50.000$?

Note:

• I am not planning on monetizing my app to grow since I do not have any money to invest into ads and I am convinced the CAC/LTV would not come out positive with my product
• I want to become sth like globo or Seterra, which are both 100% free and still grew to 100k/1 million users (Seterra due to early mover and website-ads referencing, with which I am fine)

Curious what the founder crowd here is seeing.

We've been running a few AI-native bets in parallel out of our software agency and the pattern across them is starting to feel like:

What looked good in 2024 but isn't holding up:

• "AI agent for X" pitches without a clear human-in-the-loop layer. Customers turn them on, get burned by one bad output, never come back.
• "AI-native" SaaS where the AI itself is the headline differentiator. We keep watching those bets lose to incumbents who slapped GPT into their existing surface — distribution beats novelty.
• Workshops and one-off training. People feel smarter for a week, then revert. We had to kill our own AI engineering workshop product and rebuild it as ongoing coaching for that reason.

What's working better than expected:

• Living in surfaces the user already inhabits (WhatsApp, Slack, email) instead of asking them to learn a new dashboard. Cuts the activation
• problem in half.
• Multiple cheap experiments in parallel instead of one big product bet. We just shipped a new AI ops agent for staffing agencies with three lead magnets simultaneously.
  • a WhatsApp bot for the operator who wants to feel it,
  • a 60-second side-by-side LLM-vs-agentic-workflow demo for the skeptic,
  • a 10-day course for the cautious.
    • Letting engagement signal which segment is the real wedge.
• Cooperative-style ownership. With 20+ co-owners we can run more parallel bets than a single founder could. This way the failure of any one bet doesn't sink the team but we're still around zero with AI-native offerings.

What we're still trying to figure out:

• Whether "AI-native" companies actually have durable moats or whether everyone re-converges to the same product surface in 18 months.
• Whether you can monetize agents that primarily save time rather than directly create revenue. Most of our agents fall in the first bucket and pricing it is harder than we thought.

Asking the sub:

• If you're running an AI-native agency: which of the above bets are matching your data, and which are wrong?
• What's the unsexy thing that ended up mattering more than the AI itself?
• Anyone solved the "agent matters more in hour 3 than hour 0" demo problem?

I know it says June 5 but has anyone heard back from yc at all?

Recently applied to YC Co-Founder Matching after finishing a startup chapter and exploring new opportunities around AI/Web3/internet products.

Still waiting for approval, but curious about other people’s experiences with the platform.

Did anyone here actually find a serious long-term co-founder through YC Matching or similar communities?

Most alternatives I tried so far seem full of inactive profile and spam.

Would genuinely appreciate any advice or lessons learned before diving deeper into it (already checked their guide).

I am curious to hear if any introverted founder managed to make it in the tech industry? did you eventually grow and learn how to pitch/sell? how is it currently going for you? did you eventually get a co-founder?

I recently quit my full-time job as a VC to go all in on my recruiting startup. I built a recruiting agency in 2021 that scaled to $200k/yr, solely using cold email. However, times have changed. I'm building another recruiting firm, focused solely on AI engineers. I've sent thousands of cold emails this year and haven't managed to close a single new client from it. We've built custom technical vetting and other stuff that I believe makes us better than any competitors. I try to get that across in our cold emails, but my guess is that the people I'm targeting are so flooded with similar emails that it gets lost in the noise.

The clients I have today have been the result of massive luck. A VP at Google filled out the form on my landing page. He said he found us through AI search. I'm trying to replicate that, but so far I've had no luck with it. Then, I'm working with some startups, where I met the founders in-person at events in SF.

Now that I'm full-time, I want to really focus the majority of my time on business development. However, I'm not sure where to focus my energy. Nothing I've tried has worked, and everything that has worked has been luck-based. I really want to find a solution to this, as my tendency is to dive into product/code and neglect active sales. I know that's a road that leads to nowhere though.

If anyone has any ideas, I'd really appreciate it.

after reading about YC’s spring and summer 26’ request for AI-native agencies & service companies

I decided I’ll shift our current startup from being AI GTM Engineer SaaS (it’s an AI agent for GTM) to an AI-native GTM team/agency that uses this agent itself to sell the outcome to a very narrow ICP in B2B tech

But then

I realised that me, my co founder and the rest of the 4 engineers don’t actually have deep experience in GTM, sure, they’re all superb SWE’s and my co founder is an AI/ML engineer who built many agents but

How will we perfect such an agent that should serve these companies without actually one of us having deep domain expertise

So I thought, since we wanna go down this route of AI-native service companies because the potential is immense

Why don’t we act as an engineering team for existing successful GTM agencies and help turn *those* AI-native instead with the AI-agent we were initially building while we manage it, expand it into deeper workflows, maintain it, etc on a retainer basis

We’d be “AI-nativizers” for them instead, I mean the whole point of having or turning a service company into being AI native is to increase margins to near software like (70-90%) and make it easier to scale without adding headcount or losing on profit

I hope this doesn’t just sound good in my head but, we initially started as a software company many months ago then pivoted to SaaS then now repositioning to this

“Helping existing GTM agencies increase margins by 15-20% and scaling without adding headcount or losing on profit using our vertical AI agents that we imbed into every workflow to turn them AI-native”

Think of it like we’re selling the managed service tier of a SaaS but for existing GTM agencies

Would love your insights on this, founders!

We’re a small team of 4 building a B2B SaaS product.

Right now, one developer is focused on ML/data work. My dev partner (my brother btw) is asking me what he should work on next, and honestly, I don’t have a clear answer.

That feels weird, because usually “not enough dev capacity” is the problem. But we’ve reached a stage where the bigger question is not execution, it’s product direction.

We have users & design partners, we have signals, we have feedback, but we’re still figuring out what the product should become:

• Is this a feed users check daily?
• Is it a workflow?
• Is it a notification layer?
• What actually makes users come back?
• What is the core recurring value?

So now I’m stuck in this awkward moment where giving my dev partner random tasks feels wrong, but not giving him anything also feels like wasted momentum.

Curious how other founders handled this stage. What would you focus on when direction is not clear?

Would love practical advice from people who have been through this.

Where do we find sent request in YC startup school?