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The engine behind every top 1% startup is a great CRM.
One of the tools that fascinates me most is Lovable, both because of how fast their product ships (daily?) but also for how spectacular it is to enable creativity (i.e. meet my friend Arnold) and give you what genuinely feels like superpowers.
So I decided to deep dive into how this European outlier grows.
Here’s what actually worked, stage by stage:
📐 Quick note on methodology: this analysis focuses on the 80/20 mechanics that help explain Lovable’s growth (not a comprehensive profile, and not an endorsement or investment advice). Based on 40+ sources including podcasts, company blogs, investor analyses, and third-party teardowns. All revenue figures from TechCrunch or public statements. This company moves so fast that data from 3 months ago is already outdated, I used the latest confirmed source in every case. Treat all numbers as directional.
Act 1, The Spark: $0–$10M
Founder brand as a permissionless acquisition channel
Anton Osika studied engineering physics at KTH, worked at CERN, was the first engineer at Sana Labs, and co-founded Depict.ai through YC. In 2023 he built GPT Engineer as a side project, an open-source experiment to see what LLMs could do with code.
It hit 50K GitHub stars which was the fastest-growing repository on GitHub that year. GitHub’s systems temporarily shut it down thinking it was a DDoS attack 😅, because it was spawning 15,000 new repositories a day.
He tried to productize it twice.
Launch 1 (early 2024): user growth stalled almost immediately.
Launch 2 (mid-2024): retention collapsed, the AI got stuck on anything complex, and the pricing model was bleeding money on power users.
Most people read that as a no, but Anton read it as a spec.
He and co-founder Fabian Hedin migrated the entire backend from Python to Go, built new scaling laws for AI self-debugging so the model could get itself unstuck, and made the call that changed everything: stop targeting developers.
Their hypothesis was that the real opportunity was giving non-technical people the ability to build software from scratch (superpowers).
“Lovable” as a rebrand was spot on, as it told you how it should feel. Elena Verna, who joined later as Head of Growth, has a name for this: the Minimum Lovable Product, software with personality, software you trust because it feels alive.
The name has also become somewhat of a cultural enforcement mechanism inside the company, when someone says “this is not lovable” in a meeting, everyone stops what they’re doing.
Third launch was in November 2024, which became #1 on Product Hunt, #1 on Hacker News and drove $10M ARR in 2 months with 15 people.
The levers that drove it:
Founder brand as distribution: Anton had already been cultivating an audience on socials built over years of posting raw numbers, failed experiments, hiring photos, half-formed ideas a-la Pieter Levels. When hey launched people already trusted the person before they trusted the product. This deserves a deep-dive on its own, worth having a trip down memory lane on Anton’s timeline.
GPT Engineer’s 50K GitHub stars were a pre-built trust base: Thousands of developers already knew the name and the credibility likely transferred directly to the new product, again part of a long-term founder brand investment.
Short video demos as an ad: Nobody knew what vibe coding was in late 2024 but you watch 10 seconds of someone building a real app by typing a sentence and you think “I had no idea this was possible.” / what kind of sorcery is this. I think Twitter, Tiktok and YouTube drove real curiosity at scale due to the product’s inherent “magic moments”.
Co-marketing with Supabase, Replicate and Resend: gave them reach into audiences that were already product-curious and technically adjacent.
Product Hunt and Hacker News as coordinated launch amplifiers: as usual, but also with leveraged via points 1 and 2 above.
User-generated content from day one: Every post someone shared of their Lovable build was basically an organic proof point (PLG mechanics).
One mistake Anton calls out directly that caught my eye and is worth highlighting as it is a perpetual debate I had both working at Meta on product discussions but also with many of my founder friends (almost weekly):
On trying to keep the GPT Engineer open-source community alive alongside Lovable: “A bad idea to do two things that were like a bit too tangentially related.”
Building a trust machine without ever buying growth
A founder’s personal brand can get you to $10M (as wild as that is). But what gets you to $100M is likely, as is usually the case, a system.
And Lovable’s system has more moving parts than almost any company at this stage, and almost none of them are paid.
Before getting into the levers, the context that makes them all make sense is what I hear Elena Verna call “the product-market fit treadmill”. Which means that every 90 days, a new model drops, consumer expectations reset, and what felt like product-market fit the previous quarter feels shaky again.
Worth noting how they explicitly call out how growth work has totally flipped from 5-10% innovation, 80%+ optimization to, at Lovable = 95% innovation, 5% optimization.
Which means Lovable is rebuilding the growth engine while driving.
Growth lever 1: Hire for slope, surround yourself with people who see around corners.
This one sits at the top because it’s the precondition for everything else and the founder seems to be very direct / osbssessed about it (for good reason): the pocket moves fast, and the only durable advantage is being surrounded by exceptionally smart people who can see what’s coming before it arrives.
Lovable hires ex-founders and high-slope new grads, and Stockholm turns out to be a structural advantage here, where Lovable is quickly becoming the biggest talent magnet in the city, something that’s simply not possible in SF where OpenAI or Anthropic will outbid you on a bad Tuesday.
The cultural consequence is a growth team that builds core product (i.e. they’ve launched a Shopify integration, enabled voice mode, built agentic workflows, etc.). None of that would usually come from a growth team at a traditional company.
Growth lever 2: Turn every engineer into a marketer.
The system is called beeswarming and it’s more deliberate than it sounds. Every employee ships code to production, builds side projects on Lovable, and posts about their work on social. When a post goes up, it gets dropped in an internal channel and the whole team swarms it with comments and reposts within the first two hours.
There’s also somewhat of a structural advantage here because typicallly large companies cannot do this (requires review, approval, less incentive too etc).
“If you asked me what the organic marketing strategy was five years ago, I would have said SEO. Now it’s all about social, no matter how B2B you are.”
Influencer marketing seems to be 10x bigger for Lovable than paid social.
Growth lever 3: Freemium as a marketing budget, not a cost center.
Most companies treat freemium as a necessary evil but Lovable’s biggest cost bucket is freemium, and they track it explicitly as a marketing line item, not COGS.
The logic is that a free user who gets delighted posts on social, refers friends, and builds apps that other people see. They track this through the “Lovable Score” which measures referral propensity across the user base.
They have it as a rule that free giveaways must exceed your paid marketing spend. If you’re spending more on Google and Meta than on delighting free users, you’re subsidizing third-party platforms instead of building an earned channel you own.
The free day campaigns is another example of this tactic. They’ve run 3 as far as I can tell: a free weekend in early 2025 for acquisition when the brand was young, a summer 2025 free weekend near $100M ARR specifically for resurrecting dormant accounts, and Women’s Day 2026 with advance notice and mission alignment. The last one:
“All I see is people talking about the Lovable free day. That is something you cannot pay for. A campaign bigger than one that would cost us millions of dollars, and our users are doing all the marketing for us.”
Growth lever 4: Ship every single day.
Not bug fixes, teal product changes based on user feedback. You can see these happening in real time following Anton on Twitter, which is amazing.
Engineers ship, then post, Beeswarming kicks in. Which also means the marketing team has no involvement in daily releases (more focus), and has product engineers announce what they ship, directly, on their own channels.
On this wave, and in this market, daily or weekly shipping puts you in the habitual zone vs monthly tends to put you in the forgettable zone.
On top of the daily releases, they run tier-one launches every 1-2 months that bundle features into a story with a bigger narrative arc. The full circle is that daily retains existing users and tier-one launches acquire and resurrect dormant accounts.
And of course the “constant noise” is a deliberate retention strategy (and so is layering in each of these growth levers, across Act I and II).
“Micro-releases make the product feel alive. Users signed up for version X but keep getting version X+. It builds trust without you having to ask for it.”
