Validating via services before building a $27k MRR product

This is the part most founders skip and it's exactly why most products fail. You spent a summer doing the work manually before automating it. That's not just validation, that's building domain expertise that directly informed what the product needed to do.

The detail about it taking 5 hours to find 100 qualified prospects is the kind of data point that makes automation decisions obvious. You knew exactly what to build because you'd done it by hand hundreds of times. Compare that to founders who jump straight to code and guess at what the workflow should look like.

Question: when you transitioned from manual to automated, how did you handle the quality gap? The hardest part of automating anything that requires "judgment and timing" is that V1 of the automation is always worse than the human version. Did you run both in parallel for a while, or did you just ship the automated version and iterate based on customer complaints?

I'm building a small AI tool called Ziraxo that converts images into 3D models.

Still improving it and would love to hear feedback from people working with 3D.

The project name is Ziraxo.

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Great article!

I'm building an AI tool that turns images into 3D models automatically.

I'd love to hear feedback from people working with 3D or game development.

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Huge respect for turning a manual, painful process into a 7-figure exit and then doing it again with a clearer system.

What stood out most to me wasn’t the LinkedIn growth engine — it was the “no code, just manual service first” phase. Spending an entire summer manually finding 100 qualified prospects at a time is real validation. Most people skip that part and jump straight into building.

I’m much earlier in my journey and building a multiplayer product right now, and this reinforces how powerful service-led validation can be before scaling with automation.

Curious — during that manual phase, what signal convinced you it was truly scalable and not just temporarily working because of effort intensity? Was it conversion rates, retention, LTV, or something else?

Appreciate you sharing the full arc here.

Lead generation is the cornerstone of any solid sales cycle. Doing it manually (phone calls, emails, text, etc.) is definitely time and money consuming and the success relies solely on the individual making the contact. Leveraging the power of AI for SaaS was clearly a game changer and will only get better! Congrats!

Love this story. Turning a manual growth process into a product is such an underrated path to SaaS success. The “service before software” approach really shows how demand should come before code. Great breakdown 👏

The manual validation phase really stood out to me. Spending an entire summer doing painful, unscalable work before writing code is something many founders skip.

Curious — during that manual phase, what was the biggest signal that convinced you people would keep paying long-term, not just try it once?

Love this. Services are the fastest way to validate demand + pricing before you burn months building. The service → product path is underrated.

Love it !
We have been customers of gojiberryAI for a while now and the tool is amazing.

This caught me: “It was painful and completely unscalable. But it proved two important things: Real demand existed and customers were genuinely happy with the results.”

I read a book a long time ago called “The Lean Startup” where they preached the test and pivot idea. In this case they saw through the results that this was validation of the idea but not the process. Thanks for posting

I'm still in the 'manual frustration' phase with my Python tool after 680h on a 94°C laptop, 5-10 users yet, just me fixing memory leaks at 3 AM

What was the one manual thing you did for customers that made them say 'I need this as a product' instead of 'nice try'?

​I think this is a smart move. In my experience, founders often get paralyzed by the ‘aesthetic’ of a brand name while completely ignoring the clinical reality of SEO or cultural friction. Solving this early saves so much technical debt later. Curious to see how you’re handling the validation metrics.

Really solid example of validating before building. The way Romàn proved demand with manual services first and only then automated it shows a smart path to real $27k MRR, and it’s a great lesson for anyone thinking about jumping straight to code.f

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Impressive journey, Romàn! It's incredible to see how you turned a successful exit into a new product that leverages the very tactics that made your previous venture successful. The transition from doing manual lead generation to automating it with Gojiberry AI is a perfect example of solving your own pain point, and the results speak for themselves.

I love how you validated the idea through manual services first before jumping into product development. It's a smart approach that minimizes risks and ensures there's real demand. The fact that you didn’t write any code for the MVP and instead focused on customer validation is a great lesson for any aspiring SaaS entrepreneur.

Your growth strategy is another gem. Leveraging multiple channels, from Reddit and LinkedIn to cold email and influencer partnerships, shows how versatile and scalable a multi-dimensional marketing approach can be. The key takeaway for me is that there’s no silver bullet, just consistent, compounded effort in the right places.

Also, focusing on a narrow ICP and use case is super valuable advice. It’s easy to get distracted by the idea of serving everyone, but honing in on the right audience makes all the difference. I’m excited to see what’s next for Gojiberry AI as you expand and refine the platform!

Do you have any advices for who are trying similar approaches but failing. For example I am trying the same approach for Reddit for whenasked[dot]com platform. But couldn't find anyone to use it for feedback.

Turning the exact growth loop that led to a 7-figure exit with CocoAI into a focused product like Gojiberry AI feels like the ultimate “don’t reinvent, refine” move. Also love the reminder that intent beats volume every time, and that narrowing the ICP makes everything easier (product, messaging, sanity).

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This is a great breakdown. Curious — what was the biggest thing that actually moved usage early on?

The "services first, product second" approach really resonates. I had a similar experience building PromptGenerators — I kept manually crafting AI prompts for image and video creation before realizing the process itself could be automated. That painful repetition is what pushed me to build a tool that extracts reusable prompts from images and videos.

One question: when you transitioned from manual services to the actual product, how did you handle the quality gap? Automating "human judgment" (like identifying real buying signals) seems like the hardest part to get right without losing what made the manual version work.

services-first is underrated. you learn pricing + onboarding + real objections fast, and you end up building the exact tool you wish you had while delivering the service.

one tip: keep a running doc of repeatable steps + prompts, then turn that into product features one by one.

this is amazing

Love this approach. Doing the work manually before building the SaaS is probably the best validation you can get. If someone is already willing to pay for a messy or manual solution, you know the problem is real; you’re not guessing anymore. Most failed SaaS products I’ve seen weren’t bad products; they just solved a problem people didn’t urgently need solved.

Love this approach. Starting as a service seems like the fastest way to find real demand + messaging that converts.
Curious: what was the first “repeatable” package you sold (scope + price), and what signal told you it was time to productize?

Smart approach.
Starting with services reduces risk and forces you to understand real customer problems before building the product.
Did you keep offering services after the SaaS started growing?

We found something similar while adding AI. The problem wasn’t intelligence; it was clarity. Until users understood why the product existed, smarter behavior didn’t help.

Did you ever consider adding AI earlier and decide against it? What stopped you?

Love how pricing signals shaped what you built, not just whether to build it. Thats a massive advantage of services-first validation that more builders should try.

The "validation through manual services" approach really resonates with me right now.

I'm currently at a similar crossroads with Xora Analytics — have 4 beta users who love the product (AI-powered insights from user behavior patterns), but struggling with the free → paid conversion.

What stands out from your story:

1. You proved willingness to pay BEFORE writing code — that's the validation most founders skip. I built first, now validating pricing/positioning after the fact.

2. Manual work revealed what to automate — spending a summer doing 5-hour manual searches sounds brutal, but it told you exactly which parts customers valued most.

3. Narrow ICP unlocked everything — "trying to serve everyone slows everything down" hits hard. I'm probably still too broad.

Quick question: During that manual summer with VAs, what was the specific moment where you thought "okay, THIS is ready to be a product"?

Was it when clients started asking for faster turnaround? Or when you saw a repeatable pattern you could systematize?

Also curious — you mentioned B2B influencers on LinkedIn were particularly effective. How did you identify which influencers actually had your ICP as their audience vs just large followings?

For context, we're at:

- 4 beta users sending ~4k events/week

- Users love the AI recommendations ("move this feature here, add CTA on day 2")

- $0 MRR — figuring out what makes them pay vs stay free

Your "manual validation → product" path is making me think I should've done services first. Might still not be too late to offer some "done-for-you analytics consulting" to validate pricing 🤔

Congrats on the $27k MRR — really inspiring to see the path from painful manual work to scalable product.

The "validate by doing it manually first" approach is underrated. Spending a whole summer manually finding leads before writing any code takes real discipline — most people skip straight to building. I'm in finance/audit and just started shipping small tools for pain points I've lived through professionally. Curious about your Reddit strategy early on — when you say you "shared real data and transparent results," were you posting in specific subreddits or mostly commenting? Trying to figure out the right balance between sharing value and not getting flagged as self-promotion.

Doing it manually all summer before writing code is such an underrated move. Painful, but that’s real validation.

The "services first, product later" approach is something I wish I'd learned earlier. I'm building a video downloader and spent months on features before really understanding which pain points users would actually pay to solve.

What really stood out: productizing the exact tactic that drove your previous 7-figure exit. That's not just founder-market fit — that's founder-distribution fit. You already knew the playbook worked because you lived it.

The ICP advice hits hard too. The temptation to "serve everyone" feels safer but just dilutes everything — messaging, features, support. Narrowing down feels risky until you realize it's actually what makes growth possible.

Curious: when you transitioned from manual to automated, what percentage of the "human judgment" in lead qualification did you manage to preserve in the product? That seems like the hardest part to get right.

Really cool product

Really impressive journey, Romàn! I’m very interested in Gojiberry AI and would love to explore your current development and see how we might collaborate. The intent-based outreach approach and consistent growth strategy are fascinating — I’d be excited to connect and learn more.

"To build the MVP, we did not write a single line of product code. Instead, we first focused on getting customers."

This is the move more founders should make but don't. The services-first validation is painful (you lived it with those 5-hour manual searches) but it proves demand in a way that surveys and landing page signups never can.

Two things stood out:

1. You used your own growth tactic to sell your previous company, then productized that exact tactic. That's the cleanest founder-market fit I've seen.

2. The multi-channel approach with consistency > any silver bullet. "Showing up everywhere, every single day" compounds in ways that single-channel focus doesn't.

Question: when you were doing manual validation with VAs, how did you handle quality control? Was there a feedback loop to catch when they were finding low-quality leads?

I like the idea "Find something that actually works, then automate it".

This is brilliant, Román! The manual validation approach before building the product really resonates. e-commerce founders actively engaging on LinkedIn converted significantly better - that's such a specific insight that probably only came from actually doing the outreach manually first. I'm curious about your workflow transition. When you were doing this manually, how did you handle the context switching between LinkedIn research, prospect qualification, CRM updates, and actual outreach?

I ask because I'm working on a similar workflow problem - but focused on the design-to-code handoff where context gets lost between tools. The manual validation approach you used is exactly what I'm considering.

Did you find specific moments where the manual process broke down that became your feature priorities? Would love to hear more about that transition from "painful but valuable" manual work to automated product.

This was really helpful, appreciate it.

I keep noticing that most platforms optimize for visibility,

not for quality of answers.

When you need a very specific, non-generic insight,

where do you actually go?

This is a great reminder that real validation comes from getting paid, not from surveys. Doing things manually first forces you to understand the customer’s real workflow before automating anything. Solid approach

This was a really interesting read. I liked how you showed the full journey, not just the success part, but also the manual work and experimentation that came before the product existed.

What stood out to me most was how you validated the idea by doing everything by hand first. Spending hours finding leads manually sounds exhausting, but it clearly gave you a deep understanding of what customers actually needed. It’s a great reminder that you don’t always need to build software right away to test if something works.

I also appreciated your focus on narrowing down your audience. The lesson about trying to serve too many people at once and then getting better results after focusing on one clear group feels very real and relatable for anyone building a product.

Overall, this was a very honest and practical story about turning a working process into a business. Thanks for sharing both the wins and the hard parts—it’s inspiring and useful at the same time.

This is a great reminder that validating demand through services first can save time and risk. Turning real user problems into a product for $27K MRR is inspiring and practical.

Hi Roman Czerny,

I saw you’re building a digital skill platform for learners and teachers.

I already have a ready-to-launch learning/career-focused website framework that can save months of development time.

Would you like to see a quick demo?

Doing the manual version first makes so much sense. If the product solves a real pain, proving demand upfront avoids a ton of wasted dev time.

this reinforces the idea that distribution execution often matter ore than the initial idea itself

Strong example of doing things in the right order: manual → validation → automation. Turning the exact growth lever behind a 7-figure exit into a product is a huge edge. Also love the emphasis on narrowing ICP early that clarity compounds fast.

Is firebase better to use than supabse?

I'm curious to learn more about what are the channels of acquisition you built for this? Especially when the product in its early stage and the viable channels are foudner-led sales.

Incredible journey, Román! Congrats on the $35k month 🚀 What's one underrated tactic from your growth stack you'd double down on next?

Very cool well done

This really resonates.

We actually validated part of our idea the same way — by offering a “service-like” version first and observing real behavior instead of assumptions.

In our case (working on a smart health device), seeing how people reacted to data feedback was way more valuable than feature surveys. It completely changed what we ended up building.

Stories like this are a great reminder that real validation often happens before the product looks “finished.”
For context, this is what we’re building now: brusho

This hits close to home. I’m in the middle of launching my first beta, and the “do it manually first” part really resonates. The stuff that feels slow and unscalable early on is usually the clearest signal that you’re actually solving something real.

The focus on intent over volume also matches what I’m seeing. It’s easy to ship features or metrics, but what actually matters is whether it leads to real conversations and outcomes.

The ICP point is another one I’m learning the hard way — narrowing feels risky, but things only started to click once I stopped trying to make it work for everyone.

Appreciate how grounded this is. It’s reassuring to see progress come from execution and focus, not hacks or shortcuts.

This happened to me backwards. Ran a Webflow studio for 6 years, lost €50K to clients who didn't pay, studio almost collapsed. Only then did I build the contract tool I needed.

You're right about being deep in the problem. I didn't choose it... it chose me when the business imploded.

The agency-first path is underrated. You're not guessing what people need.

Nice one buddy. What about expansion?

Narrowing the ICP and focusing on intent-based outreach feels like the real unlock here. I like how the growth wasn’t about one magic channel, but about showing up consistently where the audience already lives. The LinkedIn influencer angle makes a lot of sense given the product.

Nice

Appreciate your execution and mindset. How are you planning to expand it

Such an amazing read James

I built this SaaS using only my phone and AI.

No laptop. No team. No excuses.

I’m selling it to afford proper learning and become a real developer.

This project is proof I don’t quit.

Working MVP. Full source code.

No domain.

Price: $5,000.

If you believe effort deserves a chance — DM me.

Román sold his first SaaS for seven figures, then built Gojiberry AI by automating a proven LinkedIn outreach method. After manual validation, it grew to $27k MRR by focusing on a clear ICP and consistent marketing.

This really resonates.

The “manual first, product later” pattern shows up again and again in the SaaS stories that actually work. What stood out to me is how much time was spent doing the painful, unscalable version just to truly understand where automation helps — and where it hurts trust.

It’s a good reminder that validating workflow pain is often more important than validating features. Appreciate the transparency in how long and uncomfortable that phase actually was.

Wow, exactly what I need for outreach for my dual-agent prompt engineering learning platform. I was using Instantly another but it is so expensive. I pulled leads from Evaboot but that was also expensive so I started reaching out directly one by one with little response. So detecting real buying signals is key for me. Would love to connect! Paulina

Hey, we are building an AI-based hiring platform. Please let us know if we can help you with anything!

This is such a good reminder that “validation” isn’t surveys, it’s getting paid in the scrappiest form possible. Selling the service first forces you to learn the real pain points, the real objections, and what outcomes people actually value — before you lock yourself into code. Also love how it de-risks product decisions: you’re basically letting clients fund your discovery phase. Curious: what was the hardest part to standardize when you transitioned from service delivery to a repeatable product?

I agree with you. Many founders believe strong topline revenue growth is the primary lever for a Series A fundraise. While traction is crucial, sophisticated investors dig deeper.
Their core question isn't just if you can grow, but how efficiently you can scale. They are evaluating your unit economics: the cost to acquire a customer (CAC) relative to their lifetime value (LTV). If your blended CAC is rising as you scale, it signals a potentially unsustainable model, regardless of impressive top-line figures.
A compelling Series A model must therefore move beyond simple revenue extrapolation. It should segment and de-average this data to demonstrate improving efficiency, proving that your growth builds a fundamentally sound business, not just a larger top line.

Hey, honestly cool adventure. I see every day his posts on reddit about goji his last project. The videos he makes are so cool.

This really hits home. Validating by doing the work manually before building is painful, but it removes so much guesswork. Automating something only works when you’ve lived the problem first. Great story and solid lesson for founders.

Loved this story! Validating with manual services first before building the product is such a powerful approach; it forces real customer insight and reduces risk. Curious what was the biggest signalwas that told you to finally build the automated version?

super cool

We’re building an AI product and running into similar issues with API costs and model lock-in.
Curious how others here are approaching this.

Service-first validation is underrated. It forces you to face messy real-world workflows early — the exact place where most SaaS ideas either earn trust or collapse.

This is brilliant strategy. Validating via services before building the product is exactly right.

I'm doing something similar but in reverse—built 3 products first, now validating with early users. Key difference: Roman validated via manual services ($27k MRR), THEN automated.

I took the compressed path:

- Identified 3 pain points (traders analyzing charts, agencies qualifying leads, e-commerce copywriting)

- Built the AI products immediately using Coze (no-code)

- Now validating with early users instead of doing manual service first

Pros: 48-hour go-live, instant scalability

Cons: Less market validation upfront, requires product-market confidence

Roman's approach is probably safer (prove demand manually first), but I'm curious—

For people building SaaS: Do you validate demand BEFORE building (like Roman), or ship fast and iterate (like I'm doing)?

What's your timeline looking like for going from manual → automated?

Great insight about the $27k exit being proof of concept for productization. That's the golden zone.

How interesing, thanks for sharing your story.

Growth isn’t one tactic—it’s consistency across many.
Show up where your users already are, add real value daily, and let trust compound over time. 🌿

A powerful reminder that validation begins with the problem, not the product. Too many founders build first without confirming real pain. The focus on conversations and demand-first thinking is spot on.

This is inspiring.
The part that really stood out to me was validating through manual work before writing any product code. That’s something I’ve learned the hard way on a side project of mine, I doubled down on building too early instead of proving demand through real, uncomfortable manual effort.
Turning a painful, unscalable process into signal-backed validation is underrated, but this story is a great reminder that it works. Congrats on the $27k MRR, and thanks for breaking down the journey so transparently.

Inspiring story. Although we all know that this is the way to go, I think we all still dream of launching a site and customer flocking to us automatically :)

Thank you for sharing.

The tool that powered your 7-figure exit is brilliant founder logic. The manual validation summer sounds painful but clearly worth it—$27k MRR speaks for itself.

This is such a strong reminder that validation starts with the problem, not the product. Too many founders jump straight into building before confirming real pain. The emphasis on conversations and demand-first thinking really hits home. Great share.

This has some really sound advise, especially for first time or aspiring founders. Validation is not about UX, features, appeal etc, all of this assumes that a potential user already has a need. Validation should be more about the clarity on the need or the problem itself. Wish i'd read this sooner!

Love this approach. Validating through services before building is such an underrated move. It forces real conversations, real pain, and real willingness to pay. The $27k MRR outcome is proof that doing things that don’t scale early actually scales later.

Super inspiring breakdown. Thanks for sharing this!

Journey with Gojiberry AI highlights the power of validating ideas through real demand before building a product.

Focus on narrowing down the Ideal Customer Profile (ICP), using multiple marketing channels, and delivering fast, measurable results drove consistent growth.

By automating intent-based outreach, Gojiberry AI addresses a real pain point for B2B companies. Approach of focusing on customer value, rather than trying to serve everyone, shows the importance of targeted growth strategies and staying outcome-driven.

Interesting. Funnily enough I'm UI/UX designer based in India. I work full-time in B2B SaaS. I design web apps and websites. Could I use this tool to reach out to B2B SaaS founders and offer my design services?

This is a masterclass in what I call the 'Manual Purgatory' in my book, Startup Inferno.

Most founders fail because they skip the 'painful and unscalable' phase you described. They fall in love with the tech stack before they prove the demand. Your approach of using VAs and manual searches for 5 hours is the ultimate 'Grill' for a startup idea.

In my book, I use a Cost Optimization Strategy to show exactly this: how to replace expensive 'Future Tech' (like complex automation) with 'Essential Validation' (manual work) during the first 6 months.

You proved that:

Software is secondary: you didn't write a line of code until you had customers.

Staff should be lean: you used VAs instead of hiring a full engineering team too early.

Your advice on narrowing the ICP is exactly what I mean by avoiding the 'Lust of excess', trying to serve everyone is just a way to burn cash faster.

Question for you, Román: During that summer of manual work, what was the specific 'signal' from a customer that told you 'Okay, now it's time to build the actual product'?"

This is a great example of validating the hard way before scaling , manual services force you to understand real intent, not just assumptions. No surprise Reddit worked early on here; sharing real data in SaaS communities builds trust fast.

For products like this, Reddit can keep compounding as a channel for intent signals, feedback, and early adopters when used strategically.

If you’re open to swapping notes on using Reddit to drive more qualified users and conversations, feel free to DM me on Telegram @preshtechsolution.

I agree with you on validating with manual work before writing any code. Spending an entire summer doing the painful work is proof that real demand exists.
Awesome story and results!

I really liked the idea of narrowing down your ICP cohort to target specific users and validate your idea fast. I will make a not of it for any SASS that I am going to work upon next time.

nice

Great story! Manually grinding lead gen as a service first (with VAs over a whole summer) to prove real demand and nail the value prop before writing any code is classic "do things that don't scale" done right. $27k MRR from that foundation shows how much clearer the path becomes once you've already got paying customers loving the outcome.

Love this reminder: validate by delivering results, not just asking for opinions. Congrats to Romàn on the strong traction with Gojiberry AI! 🚀

Nice article but by the way it seem to me as though most founders underrate the power of stackexchange for validation. I noticed people ask and talk about pain points that are really genuine on those sites. Personally I haven't started coding my saas as I am still building the destribution, but I validated my idea and even the distribution method via stackexchange questions and metrics. But it sometimes feel like I am the only one validating on SE ahaa!

You mentioned scaling on reddit, I really envy people who could make reddit work for them. I highlighted in my previous comments how ban-happy their mods are but really, it's just hard to push anything to their audience who are mostly hardliners.

I am actually opensourcing my saas validation tool; Product Ideation - Aggregated Business Ideas from Real World Pain Points

Very nice

The underrated bit is ICP narrowing + consistency across channels. Most founders try to fix weak positioning with more features, but you did the opposite: narrow use-case, push distribution daily, let the product catch up.

Question: how did you decide when the manual process was “validated enough” to finally invest in building the product instead of continuing with services?

This is a great reminder that real validation often starts with unscalable work.
Doing it manually first forces you to face real demand, not vanity signals.
I like how results (booked conversations) came before dashboards or features.
Narrowing the ICP seems to be the real growth unlock here.
Curious — what was the hardest part to automate from that manual process?

This is a great reminder that validation doesn’t come from building features — it comes from solving real problems. Starting with services gives you direct exposure to customer pain, real feedback, and willingness to pay. We’re following a similar approach, and it’s helped us get much clearer on what actually needs to be automated.
Really valuable insights here.

This hits the nail right on the head. Very relatable!

I’m validating an idea around missed calls & unresponsive leads for small businesses.

Quick question for founders / service businesses here 👇
Have you ever lost leads just because follow-up didn’t happen on time (missed calls, WhatsApp replies, forms)?

If yes — what do you currently do to handle this? Manual calls? CRM? Nothing?

I’m building a small MVP and would love real feedback.

Fantastic real-world example of services first → product validation. Doing the work manually before writing a single line of code not only proves there’s demand, it forces you to understand what customers are actually willing to pay for and why. Many founders rush to build features without ever feeling the pain their tool is meant to solve — this approach flips that script.

By engaging directly with customers through manual service delivery, you get real signals (payments, retention, repeated requests) instead of “sounds good in theory” feedback. When you finally build the product, you’re not guessing — you’re automating something you’ve lived and learned.

This underscores a key SaaS lesson: validation isn’t about speed, it’s about clarity — and clarity is far easier to achieve when you’ve done the hard work before the code.

This really resonates — especially the “manual before scalable” part.

We went through something similar where the real validation didn’t come from code, but from doing the painful work ourselves and realizing people genuinely cared about the outcome, not the tooling.

Curious — when you were doing the manual prospecting early on, what signals ended up mattering the most vs the ones you initially thought would matter?

The services-first approach is massively underrated. You get two things at once - validation that people will actually pay for the outcome, and deep insight into what they really need (not what they say they need).

I've noticed that most successful tools started as someone doing the job manually until the patterns became obvious. The automation almost builds itself once you've done it enough times.

Give a try to my Reddit Extension. It's a Chrome extension called Pulse of Reddit that basically acts like my own alert system for Reddit.

Anytime someone posts something with keywords I care about like 'looking for a designer' or 'best SEO tool' it pings me right away. It’s saved me so much time and helped me hop into threads while they’re still fresh.

If you’re tired of manual digging and want to catch those conversations early, I’d really recommend giving it a look.

It’s free to start and super simple to set up.

Website:

pulseofreddit.com

Im following a similar path:

I started my journey in 2025, unfortunately l've limited budget on marketing that's why gaining first 100 customers is quite struggling.

What do you recommend me to gain the firat 100 customers with limited budget?

I mention abour my products on groups across multiple social media platforms but l get banned. I share my products eith friends but and they try to support my products by using it. However, l only have a few friends to share with so it'snot enough. Which strategy should l choose ?

This really resonates with me — especially the idea of validating demand before committing to a full product.

I’m currently on a much smaller scale, but in a similar mindset.

I built a free, no-login tools site: https://geekskai.com (mostly small developer utilities) and didn’t plan to monetize early. I only enabled AdSense as an experiment, and it’s been interesting to see steady usage and some early revenue come in.

What I’m struggling with now is what the “next step” should be.

For someone starting with:

- free tools

- organic usage

- no clear SaaS yet

Would you lean more toward:

- offering services around the most-used tools?

- adding a lightweight “pro” tier (no ads / bulk usage / API)?

- or using services purely as a learning step before committing to a product?

Curious how you’d think about monetization at this stage.

Appreciate you sharing such a transparent breakdown.

I’m trying to avoid building the wrong thing too early.

Interesting approach

This really clicked for me. Validating through services feels like one of those ideas that sounds obvious in hindsight, but is easy to skip when you are excited to build.

What I like most is how it forces you to sit with the actual problem instead of guessing. You hear how people describe their pain, what they are willing to pay for, and what they do not care about at all. That is hard to get from surveys or waitlists.

I am early on with a small product myself, and this approach has been a good reminder to slow down and make sure I am solving something real before piling on features. Thanks for sharing this. It is a solid example of doing validation the right way.

This is really interesting, thanks for sharing.

When you say B2B influencers on LinkedIn were helpful, how did you actually identify and select them? Did you explore /tested influencers from other platforms like TikTok or IG?

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The manual validation approach really hits home. I'm on Day 4 of launching MeetDone - a tool that turns meeting transcripts into follow-up emails.

Before building, I lived the pain myself: spending 20-30 mins after every client call writing a professional follow-up. Now it takes 30 seconds.

Still at 0 paying customers, but the problem is real - just need to find the right people. Your point about narrowing the ICP fast is something I need to focus on. Freelancers and consultants seem like the right fit, but maybe I need to go even narrower.

Thanks for sharing the journey - encouraging to see the path from manual pain to $27k MRR.

I am working on marketing part of my SaaS, quite challenging at early stage, without huge financial input.

Finding 100 qualified prospects often took several hours, sometimes up to five. We spent an entire summer doing this manually, with the help of multiple virtual assistants based in Pakistan and India. It was painful and completely unscalable. But it proved two important things: Real demand existed and customers were genuinely happy with the results.

How did this initial idea come about? And for indie developers who want to validate their product in the early stages but struggle to find 100 potential users—do you have any advice? Thanks a lot!

This resonates. Years of freelance work showed me exactly what problems people pay to solve. The tricky part was turning that into a product instead of just more client work.

Getting paid while you figure out what to build is underrated.

Strong write-up. The part that resonates most is validating behavioral friction before building anything.

In my experience, the biggest trap isn’t lack of ideas, it’s confusing “sounds useful” feedback with actual workflow pain. Until someone is willing to change how they currently operate (or give you their email/money), the signal is mostly noise.

Out of curiosity — in your early validation, what was the most misleading positive feedback you received before you saw real traction?

Great breakdown. The “manual services first” part really stands out.

Curious - during the manual phase, what was the strongest signal that convinced you this was worth turning into a product? Was it retention, referrals, or clients asking to scale volume faster?

Really interesting breakdown.

In a crowded market like this, what took longer than expected to figure out —

the gap itself or the distribution strategy?

This resonates. I underestimated how painful maintaining scrapers would be long-term. In hindsight, data reliability mattered more than speed of iteration. The manual approach forced me to understand what data points were actually critical vs. nice-to-have before building infrastructure around them.

This is a great example of something people say they believe, but rarely execute: services as validation, not a fallback. ~

It’s not that you got to $27k MRR, but that you delayed product on purpose until demand was undeniable. Many founders feel the need to ship software. You Used Manual Effort To Buy Clarity.

Some worthy points to note.

Real constraints were imposed by manual work.

Enabling access to services revealed the true value of intent, timing and context, not where it was easiest to automate.

Sales dictate product decisions before any software change.

The product roadmap wasn’t theoretical as customers were already paying Every feature of friction was experienced by you.

Distribution was baked into our strategy from the beginning.

LinkedIn was not a “channel” you found out about later it was where the pain already lived.

Many people think services don’t scale so it’s wasting effort. But it’s software that is unvalidated that’s wasting effort. Services reduce feedback cycles, turning guessing into observation.

What’s interesting isn’t that you automated outreach it’s that you first proved people want these outcomes badly enough that they’ll tolerate you delivering it manually. The product lowered the cost, speeded up and made repeatable.

The right kind of boring is how real businesses usually get started.

This approach highlights something important.

Services force you to sit with real context — real conversations, real constraints.

That signal is hard to get once you jump straight into building.

Validation isn’t about speed. It’s about clarity.

The manual validation approach really stood out to me.

Starting with services and getting people to pay before building the product is such a strong signal of real demand. It’s a great reminder that effective validation doesn’t have to be complicated.

How do you go about getting customers?

This is a great example of letting customers shape the product instead of the other way around. Starting with services feels like a smart way to reduce risk, especially because you’re getting paid while learning what actually matters to users.

I also like how this approach naturally forces you to focus on outcomes rather than features. When people are willing to pay for a service, it becomes much clearer which problems are urgent and which are just nice to have. By the time you transition to a product, a lot of the hard prioritization work is already done.

It’s encouraging to see that this path can lead to real revenue without needing a massive launch or upfront build. Definitely a good reminder that momentum often comes from practical execution, not perfect ideas.

Loving the articles James! Thanks for writing! Be great to share more how we pivoted from Dolphin AI to Pretty Prompt (Grammarly for prompting) and hit 20k users in 6 months with users from LinkedIn, Upwork, Chili Piper, Wix 🙌

This resonates a lot. Doing things manually first feels inefficient, but it forces you to see what users actually value versus what just sounds good in theory. I’ve noticed the biggest signal isn’t usage, it’s when people start asking for the same thing repeatedly without being prompted.

The manual validation bit is the part most people skip because it feels like backwards progress. You're supposed to be building a tech company, not managing VAs in Pakistan for a summer.

But there's something powerful about doing the painful version first. You learn exactly which parts suck the most - and those are the features users will actually pay for. If you'd jumped straight to code, you probably would have built the wrong automation first.

The other underrated benefit: by the time you do build the product, you actually understand your customer's workflow inside out. Hard to replicate that from market research alone.

this reinforces the idea that distribution execution often matter ore than the initial idea itself

If you’re calculating college grades, the usual method is to multiply each subject grade by its credit units, then divide the total by overall units.

I had the same confusion earlier, so I wrote a simple step-by-step explanation with a practical example. Sharing it here in case it helps someone: