Hitting $2M ARR in two years even though he was "late to the AI
party"
Dominic Zijlstra thought he was too late to surf the AI wave, but then realized that the people he was following on X were just really early. So he built Adaptify. And exactly two years later, he's bringing in $2M ARR.
Here's Dominic on how he did it. 👇
AI FOMO
I'm Dominic. I'm Dutch, but the Netherlands always felt too small for me, so I studied engineering physics in Germany and Brazil, and later worked in London as a space engineer for Airbus and as a data analyst in a fintech startup. Around that time, I met my wife, who is Chinese.
As I'd always loved language learning, I tried to learn Mandarin but hit a roadblock until I found an obscure method using mnemonic techniques that finally worked to learn those weird characters! I turned this method into a product (Traverse), which was my first SaaS project that made enough money to quit my job during Covid.
Then, in early 2023, as I interacted more with ChatGPT, I turned from an AI skeptic into an AI enthusiast. Like many founders at that time, I caught AI FOMO — that fear of missing out on the AI revolution and the strong conviction that AI would change our ways of doing business for good.
So, together with a friend, we started exploring making AI products. After a few months, that turned into Adaptify, an AI SaaS that completely automates SEO delivery and reporting for agencies, and has grown from 0 to 2M ARR in less than two years.
Pivoting and pivoting again
We thought we were already late to the party, so we did some pretty random stuff at first. We launched a newsletter, created a prompt database, and built a chatbot for a client we found through an old email list. Weirdly enough, we actually started making money from these experiments, which gave us confidence to keep exploring.
The real breakthrough came when I decided to scratch my own itch with SEO for my other project, Traverse. That's when we pivoted to automated SEO content creation. A few months later, a friend shared an interesting PR backlink building playbook with us, and we added that feature. It ended up making our tool really unique and distinct from other AI writers in the market, as we were now a fully automated SEO delivery tool with keyword strategy, content, and backlinks.
Then we made another crucial pivot to focus specifically on agencies. This happened almost by accident — we had put up a higher price for a multi-site plan, initially, just to make our base plan seem cheaper for SME customers. But it turned out there was real demand from agencies who actually wanted to manage multiple client sites.
So we pivoted and now our strategy is laser-focused on signing agencies because we know they'll like the product and add more client sites later, growing their lifetime value significantly. In terms of features, this also meant we added reliable SEO reporting (including AI personalized emails).
Building RAG before it was cool
Building our initial product was really a journey of learning and experimentation. We had some help from Copilot and spent a lot of time copy-pasting mostly broken code from ChatGPT and trying to make it work. It was definitely more manual than the AI-assisted development we do now.
One of our early projects was building a chatbot, which actually made us really good at having AI understand a website's content. We essentially built a RAG (Retrieval-Augmented Generation) system before it was even cool or had that name. That early experience with making AI understand and work with web content became foundational to everything we built later.
The learning curve was steep for both of us. My cofounder actually learned coding from scratch to build our initial frontend! Meanwhile, I really became a Python async expert in the process, diving deep into LLM chains, vector databases, and all the fancy new AI technologies that were emerging.
What's been incredible is how falling AI costs have allowed us to make our product increasingly smart by adding more and more AI capabilities while maintaining healthy margins. We've been able to build what I'd call revolutionary UX features, like automatically changing product settings based on user feedback - things that would have been impossible or prohibitively expensive just a year or two ago.
The timing worked out perfectly. We were learning these technologies right as they were becoming more accessible and cost-effective, which let us build something truly innovative without breaking the bank.
The advantage of a standard stack
We've built on a fairly standard modern stack, but when you add AI to the mix, it becomes really interesting. And having a standard stack nowadays is actually a real advantage because AI tools are much better at understanding and working with common technologies.
Our frontend is NextJS with Tailwind CSS, running on Vercel.
For our database, we're using Firebase.
On the backend, we're running FastAPI on Google Cloud Run, with Cloud Jobs handling our long-running tasks. Our codebase really leverages async Python, which is crucial when you're orchestrating multiple AI operations simultaneously.
For the AI infrastructure, we use Pinecone as our vector database to handle all the semantic search and content matching. We've built our LLM chains with Langchain, and Langsmith has been crucial to inspect actual runs and identify patterns, super helpful for improving our AI performance and debugging issues before they become problems.
And we use AI tools like Cursor and Claude Code for development; they understand this stack intimately, which accelerates our development speed significantly.
3-tier paid ads
Our growth story is really about finding what works and doubling down hard. We've been doing paid ads from the very start because they give us a really quick way to evaluate if an idea is viable — you need to make your money back and the market tells you immediately if you're onto something.
A lot of our growth comes from Meta Ads, and we really don't do anything complicated. We stay away from "Advantage Plus" and some of the hype. Instead, we use a simple three-step funnel: top of funnel, middle of funnel, and bottom of funnel.
Top of funnel targets people who've never heard of us and may not even be solution-aware, so we focus on pain points they're experiencing. Middle of funnel targets people who are solution-aware, so we can showcase why we're the best solution compared to alternatives. Bottom of funnel targets people who've seen our ad and been to our website but haven't converted yet — we try to push them over the edge with free trial offers, testimonials, social proof, and urgency.
The timeline has been pretty incredible. Once we settled on the automated SEO idea in June 2023, we grew to over $200k ARR in just 6 months. We hit $1M ARR at around 15 months, and now exactly 2 years in, we're over $2M ARR with plenty of room to scale our ads even further.
Using the "Value Ladder"
We use what my marketing cofounder calls a "Value Ladder" approach, and this has been absolutely crucial to our explosive growth. We found this unique market opportunity that no other tool was addressing properly, and we solved it. But we realized we were leaving our main driver on the table.
So now we have an entry-level tool called "Pitch Mode" that solves a really big problem for our target audience, and it's inexpensive — we turned it into our lowest tier — making it much easier for us to drive conversions. We know that a certain percentage of Pitch Mode users will upgrade to our core product over time. And once they sign up for the core product, they just keep adding more sites as they gain confidence that our product delivers on its promise — it really does automate SEO delivery and reporting, massively freeing up their time to sign more clients and grow their own businesses.
This value ladder approach has led to some explosive growth over the past six months. The beauty is in the customer lifecycle: we start agencies on a cheap plan because we know they'll love the product. As their confidence grows, they add more client sites, which dramatically increases their lifetime value.
Automate everything
Customer feedback has been absolutely crucial, but more importantly, we've learned which customers to listen to and which feedback to ignore. This skill has been invaluable in maintaining product focus while still being responsive to user needs.
Our comprehensive AI-first approach has given us a massive competitive advantage. We use AI to automate internal processes in development, sales and customer support, and we've even built out our own AI lead scoring and customer health system that could almost be a tool on its own.
Our ability to quickly implement simple changes that lower churn has been game-changing. When customers give us feedback about friction points, we can often ship a fix within days or weeks, not months. This responsiveness has helped us maintain incredibly low churn rates.
The AI FOMO that initially felt like a disadvantage actually became our biggest asset. When we thought we were late to the party, it pushed us to move faster and be more decisive with our pivots.
Three pieces of advice
Validate with paid ads
The biggest piece of advice I'd give is this: If you don't want to fool yourself, use paid ads to validate your idea.
It's so easy to get caught up in vanity metrics or convince yourself that people really want what you're building based on friendly feedback. But paid ads don't lie — they force real people to make real decisions with real money.
The beautiful thing is that a decent ad can be quickly created with AI now, so there's really no excuse not to test your ideas this way. If you can get anywhere close to breaking even on your ad spend, that's a very strong signal you're onto something.
You aren't late to the party
And here's something that took me a while to learn: Whenever you think you're late to a trend or opportunity, you're still very early — probably very, very early. The Twitter bubble represents maybe the leading 1% in technology adoption. Everyone else is still catching up. AI is the biggest new technology since the birth of the internet, and we're barely scratching the surface of what's possible.
Team up
Finally, if you want to go far, go together. Having a cofounder or even just other indie hackers you can bounce ideas off is invaluable. You can help each other see blind spots that you'd never catch on your own. Some of our best pivots and decisions came from conversations where someone pointed out something we were completely missing.
Don't be afraid to start "late," don't be afraid to test with real money, and don't try to do it completely alone. The opportunities are bigger than ever right now.
What's next?
We're growing so quickly right now with such a small team that there's just enormous untapped potential. We've maybe captured 1-2% of our addressable market pretty quickly, and we'd like to own a much bigger piece of that. Our goal is to be the definitive solution for agencies that want to automate SEO.
But there's a bigger picture here too. AI is fundamentally changing how we think about business and work. What's left for humans when AI can automate so much? I believe it's wisdom work — the strategic thinking, the big ideas, the human insight that guides these AI systems.
My personal goal is to remove myself from day-to-day operations so I can focus on strategy and those big ideas. Becoming a father has reinforced this — I want to be present for my family while building something that can scale beyond what any individual could achieve.
We're at this incredible inflection point where if we add just a little bit of gas to the fire, the growth potential is massive. The market is there, the product-market fit is proven, and we have plenty of room to scale our advertising and expand our reach.
Follow along
Definitely follow us on YouTube. We just started working on content that basically documents our journey, so there should be a lot there for other founders to learn from. But we're just getting started with this content strategy!
I'll be honest - we've been operating in stealth mode earlier since the Twitter communities I was active in before weren't really our target community. I was actually hesitant to do this interview initially. But now we realize there's so much that other founders can learn from our journey, especially around AI-first product development, rapid pivoting, and bootstrapped growth. We want to give back and share more of what we've learned.
The indie hacker community has always been about sharing knowledge and helping each other succeed, so we're excited to be more open about our journey and hopefully help other founders who are navigating similar challenges with AI, product-market fit, and scaling.
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Really inspiring story, Dominic — loved how you validated your idea with paid ads early on instead of guessing.
I also advise my early SaaS agency clients to run ads to validate their ideas. Additionally, it helps to use tools like Mixpanel (Google Analytics) and Hotjar (Microsoft Clarity) to see what this paid traffic does on your website and how it moves through the funnel steps.
Curious:
How much spending did you take before you felt confident that a new idea had real traction?
What exact paid media platform did you use for the validation?
What key metrics did you keep an eye on?
appreciate the paid ads however if bootstrapping/very tight on cash initially, any other recommendations?? thanks!
Hey there! In this case, I’d dedicate all my time to building partnerships—affiliates, referrals, influencers, and the like.
Awesome suggestions!
Yes I can second partnerships if you have tight initial cash, this ended up being the primary channel for my previous SaaS, Traverse
Yep we used Hotjar a lot as well early on. I think we spend around $1k to get our first customer on a $499/month plan, so we kept doubling down and seeing similar (and later increasingly better) numbers. The main thing we looked at is payback period, which is 2 months in the above case. We exclusively used Meta ads for validation
That was a great result, Dominic! Since you only needed to retain that customer for two months to break even, your LTV/CAC ratio was clearly in a good place. No wonder your company grew to this level. I’ve also noticed Meta ads tend to be more cost-effective than Google Ads.
Very often, people validate theirs idea to late...
Although he joined the AI wave later than others, he hit $2M in two years by solving real problems, delivering value rapidly, and remaining consistent.
I had a similar experience last year. I built a content tool using GPT, Google Sheets, and Firebase. I thought it was too simple. Then I saw others using the same setup to build real products. What made the difference wasn’t the tools. It was focus and knowing who the product is for. When Dominic shifted to agencies, that part really hit me. I was trying to build for everyone. Now I see why that never worked.
Absolutely wild how much of this resonated... I just had to say how refreshing and real your entire story is. From space engineering to data analysis, then teaching yourself async Python and building a successful AI SaaS... it’s deeply inspiring. So many people talk about chasing product-market fit like it’s some elusive target, but you built your way into it, and that’s honestly one of the coolest parts of your journey.
Loved your thoughts on value ladders, paid ads as a lie detector, and especially that bit about “wisdom work.” That’s where it’s all heading. Tech will handle the mechanics, but it’s the humans who still shape the meaning and strategy behind it.
Thanks for sharing this in such detail.
Glad it resonated so strongly with your Sierra!
This is fire 🔥 — from language learning to AI-first SEO, that’s one hell of a pivot path.
Quick question: how did you decide which features to automate first once you started gaining traction? Was it based on user feedback, intuition, or internal bottlenecks?
Also love the value ladder idea — feels like a smart way to grow LTV without forcing upgrades too early. Respect!
Good question! It was mostly user feedback, to which we were very open since we were not initially SEO experts ourselves. For our internal tooling and dashboards, definitely internal bottlenecks is also something that helped us prioritize
That makes a lot of sense! So basically listening closely to users became your edge. Curious — was there ever a feature users kept asking for that you were hesitant to build at first?
Incredible journey, Dominic!
Love how you turned AI FOMO into focused execution and real traction. The SEO automation space is crowded, but Adaptify's positioning around agencies and your value ladder strategy really stands out. Also, can’t agree more on using paid ads as a truth serum for validation brutal but effective.
We’re also building in the AI x marketing space at GudSho and your story is a great reminder that it’s never “too late” if you’re solving the right problem with clarity and speed.
Thanks for sharing this in such depth lots to take away for any AI-first team trying to scale!
Cheers Mate!!
Hitting $2M ARR in just two years, despite being "late to the AI party," shows that timing isn't everything—execution is. With the right niche, strategic positioning, and a deep understanding of user pain points, even late entrants can scale rapidly. It’s a testament to focusing on value, not hype, in the AI space.
Yep solving real business problems is key, that you're using AI to do so is secondary (but it does massively increase the space of business problems that can now be solved with software)
Great interview and very inspiring. I have a question for Dominic. For the Langchain flow, do you have a preferred LLM for each type of SEO task? Curious how you decide which model to use where.
Definitely! We use Claude for creative writing, and the OpenAI O3 thinking models for more logical tasks like turning qualitative + quantitive data into a keyword strategy. Recently also been switching over some tasks to Gemini flash and pro as they're cheaper and quality seems up to par now
Wildly impressive! Hitting $2M ARR in 2 years, especially in a crowded AI space, is no small feat.
Curious — what part of the product or messaging helped you stand out despite being late to the AI wave?
We’re building ZTH, an AI pitch deck engine for founders, and constantly wrestling with differentiation too — so would love to learn from your experience!
Messaging definitely took us quite a while to get right! I think the key insight was when we realized we're an automated SEO tool for agencies, rather than an SEO writer or even a general AI SEO tool. This also helped us become clear on our roadmap and add stuff like whitelabel reporting etc which is now one of our most-loved features
What a great journey, thanks for sharing.
It is great journey thanks for sharing
Very welcome!
Wow what a journey, It proves you are never late for anything if you build the right stuff.
This!
Definitely, and especially if you hang out with the right crowd you're never late
It’s encouraging to see that being late to AI doesn’t mean you’re locked out. What stood out for me was your section on building RAG before it even had a name. That’s a great example of solving problems first and worrying about labels later. The way you turned async Python, LangChain, and vector DBs into something practical for SEO shows that consistency and execution matter way more than timing. Makes me think being late often gives you the perspective to build something more resilient.
Super insightful breakdown — the three-layer funnel really clicked for me. I’ve been struggling to prioritize where to put my limited energy as a solo builder, and this framework gives me a clear way to think about awareness, consideration, and conversion. It’s also encouraging to see success even when “late to the AI party.” Great reminder that execution and clarity matter more than timing. Thanks for sharing this!
Very inspiring, loved the Automate everything part.
That's something I'd advise every founder to take note of!
The best part? You didn’t just ride the AI hype — you built something boring, useful, and focused. That’s what actually scales. Respect.
came late on Party doesn't matter theres still invovations that are pending
This was an inspiring read — especially the reminder that being “late” doesn't matter if you execute well and really know your audience.
I’m in the early stages with an AI tool for brand name generation, and it’s reassuring to see stories like this. There’s still so much room to innovate, even in crowded markets.
Curious — how much of your early traction came from organic vs partnerships or paid?
So SEO is still alive in this AI age?
He achieved $2M ARR in two years by identifying niche AI needs, focusing on execution, customer value, and consistent marketing—proving success isn’t about being first, but being effective.
He achieved $2M ARR in two years by identifying niche AI needs, focusing on execution, customer value, and consistent marketing—proving success isn’t about being first, but being effective.
Even though he entered the AI space later than his competitors, James Fleischmann reached $2M ARR in just two years by identifying niche opportunities, executing quickly, and delivering real value to customers.
What an incredible story! Proves that solving a real problem with great execution beats being first to market every time. Inspiring stuff, Dominic!
What a journey — love how Dominic turned “being late” into a massive advantage. So many gems here: validate with paid ads, pivot fast, and automate everything. Proof that execution > timing in the AI game. Inspiring stuff
Love the hustle, Dominic – $2M ARR in two years proves smart pivots and real validation (paid ads FTW!) are game‑changers. 🚀
Watching products like Chatbase, SiteGPT, I was also thinking I am late to the party, but now I am feeling it's not late and I just need to solve a real world problem. Thank you for sharing the post btw :)
Impressive how Adaptify scaled to $2M ARR by automating SEO delivery and reporting, especially by focusing on agencies.
What I’m noticing, though, is a shift in how people search — it’s not just Google anymore. More decision-makers ask ChatGPT, Gemini, or Perplexity directly for recommendations. For agencies, that could mean a huge visibility gap if they’re not appearing in AI-driven responses.
Dominic, curious — have you seen AI assistants becoming a source of traffic or leads yet? Do you think agencies will soon need to optimize not just for Google but for AI visibility as well?
Incredible journey, Dominic. Love how you leaned into paid ads for fast validation and pivoted based on real traction, not theory. The async + RAG build story is awesome. It shows what focused learning under pressure can do. Big respect for scaling to $2M ARR bootstrapped.
Super insightful journey, Dominic.
Curious for other builders here:
Have you tested your niche with paid ads before building like Dominic did?
Are you using AI to automate your internal ops or just your product?
When did you know it was time to niche down hard vs. explore broadly?
How are you balancing speed of iteration with maintaining product quality?
What’s your biggest constraint forcing focus right now, and how are you using it as an advantage?
Your story is a reminder that AI + focus + fast pivots = unfair edge if you stay consistent. Thanks for sharing the behind-the-scenes!
This post is nothing short of inspirational! Thank you for sharing, and congratulations!
Absolutely loved the meta-layer of your journey — using paid ads not just for traction but as a truth serum for product validation is such a powerful lens.
Also impressed by how you kept things lean and focused in a space as noisy as AI. Would love to hear more on how you filtered feedback — how did you know which user requests were worth building into the core, and which ones to let go?
$2M ARR in two years is wild, especially considering how crowded the AI space is. Would love to know what made your product stand out from the noise — timing, distribution, or something else?
Super impressive! Just goes to show that being “late” doesn’t mean you’ve missed the opportunity — execution and focus still matter more than timing. Loved the part about carving out a niche even in a crowded space. Really inspiring for anyone feeling behind in fast-moving industries like AI. Thanks for sharing the journey!
That's truly an inspiring story. I'm also currently building an AI bot using a local language model (though it's still smaller), and this article really motivated me to explore the AI world further.
Nicee idea
Love the practical tips for idea validation with paid ads and how you narrowed your ideal customer profile to agencies!
Incredible journey! Proof that you don't have to be first; just focus, be consistent, and be customer-oriented. Hitting $2M ARR in two years, especially in a competitive AI space, is no small feat. Thanks for sharing the information. It's inspiring!
thanks for you sharing!
Really resonated with your take on 'wisdom work' - stepping out of ops to focus on the main strategy. As you aim to remove yourself from the day-to-day, what were the first responsibilities you delegated? And how did you prioritize that transition without growth slowing down?
wow thats great
The success of James Fleischmann in AI has been attributed to his execution, niche targeting, and delivering real value - proving that it is never too late to succeed.
Such an inspiring journey...
Lot of wisdom here -- thanks for sharing the details!
¡Qué recorrido tan interesante, Dominic!
Pasar de la ingeniería aeroespacial al SaaS educativo y luego al SEO con IA… impresionante. Me identifiqué mucho con lo que contaste sobre el “AI FOMO” en 2023. Yo también pasé de la curiosidad a una especie de obsesión sana por cómo la IA puede resolver problemas reales.
Estoy construyendo un pequeño proyecto llamado MyBrainyBot, enfocado en ayudar a estudiantes a aprender más rápido con IA. Leer sobre casos como el tuyo y cómo han escalado en tan poco tiempo realmente motiva.
¡Felicidades por el crecimiento de Adaptify! Muy inspirador ver ese 0 → 2M ARR en menos de dos años.
Super inspiring! Just shows you don’t have to be first to win — execution and focus matter way more than timing.
This was a fascinating and inspiring read—your journey through experimentation, automation, and niche discovery truly resonates. It’s impressive how AI-driven solutions are transforming entire workflows for agencies. A similar transformation is happening in the public sector too. For instance, in Ghana—GoGPayslip—has revolutionized how government employees access their payslips and manage salary records. Like your SEO automation, GoGPayslip simplifies processes, reduces friction, and empowers users with timely, accessible data. It's exciting to see how automation is reshaping both the private and public sectors around the world.
Super inspiring, especially the reminder that you don’t need to be first, you just need to be loud, consistent, and valuable. The AI wave isn’t over; it’s just maturing into niches.
I’m currently building an AI-powered satirical character (Angry John, imagine a foul-mouthed drill sergeant with PTSD answering dumb internet questions 😅). It's early, but watching founders scale past $1M ARR by leaning into voice + character + niche gives me real hope.
Question: What channel gave you the biggest unexpected growth spike early on? Organic, community, cold outreach?
It was paid ads from the start, and there wasn't really any spike but more gradual consistent growth (of course not without a setback now and then)
Hello! When talking about paid ads, did you have the application/platform built beforehand, or how exactly did you 'validate' the users? Did you have a dummy page for them to register early access to the platform that you have started building after?
What I am trying to ask is: what exactly did you market during the validation phase, how/what did you showcase to future potential clients?
I would be really, really grateful if you could detail a bit the validation stage beside the fact that you have used paid ads by Meta - I am more curious in how you have used them.
Wow, hitting $2M ARR in just two years and joining the AI game late is seriously impressive! Shows that timing isn’t everything—execution and persistence really make the difference. Would love to learn more about how you accelerated growth so fast!
Really great and inspiring story. Particularly impressed with the hustle and grind approach. Thanks for sharing.
Turning FOMO into form: $2M ARR shows execution > envy.
Awesome to see how you embraced being late to the party”—your pivot from AI FOMO into a focused, agency‑centric SEO stack reallystood out. Turning ads into real validation (and doubling down fast) is a leson I’m bookmarking. And your point on teamwork (“go far, go together”) feels especially true these days. Really inspiring journey—cheers to the $2M ARR milestone! Goals as a startup founder myself
Proof that execution > timing. Being “late” doesn’t matter if you build real value, find a niche, and stay consistent. Super inspiring for anyone feeling behind.
Awesome! The SEO market is huge, so sky's the limit.
Really inspiring story
Super inspiring! I’m currently building a lightweight insight dashboard for indie makers myself — it’s awesome to see others succeeding in this space.
Curious: did you focus more on SEO or communities early on for traction?
Neither, really just paid ads and we've kept doing that ever since. In many ways we haven't invested as much in our own SEO as we could given our expertise, but that's just because the business value hasn't been there until now
Appreciate the honesty — that makes sense.
I’m building something similar but trying a different path: instead of dashboards, it’s just one insight per day, sent by email.
Curious how you think about the tradeoff between showing everything vs surfacing only what matters?
Such an insightful journey, the point of choosing the feedback from the right customer, is something that made me think more when developing a product.
Kudos to you @Dominic.
I want to connect and explore potential ways we can collaborate.
Sent you a connection request on LinkedIn!!