Yuto Takashi

Posted on Jan 7

Open-Sourcing Your Business Logic: Risk or Opportunity? Lovable's Case

#discuss #opensource #startup

TL;DR

I started using Lovable (formerly GPT Engineer) and got curious about why they rebranded. What I found was way more interesting: they open-sourced their core tech, got 52K GitHub stars, and used that to build a successful commercial product. This post breaks down how and why.

Why You Should Care

Conventional wisdom says: don't open-source your business logic. You'll lose competitive advantage, get copied, and struggle to monetize.

But what if that's wrong?

Lovable's story challenges this assumption. They open-sourced everything, gained massive community trust, and built a thriving business on top of it.

If you're building anything, this case study matters.

My Lovable Experience

I recently started using Lovable. First prompt in, and boom—a surprisingly well-designed mock appeared. Then I kept iterating with abstract instructions like "make it more professional," and it just... got it.

I was hooked.

While using it, I learned it used to be called "GPT Engineer." Why the rebrand? That question sent me down a rabbit hole that led to this post.

The Journey: GPT Engineer → Lovable

Here's the timeline:

2023: Anton Osika releases "gpt-engineer" as an open-source CLI tool on GitHub
Late 2023: Launches commercial web version "GPT Engineer App"
January 2025: Rebrands to "Lovable"

The rebrand wasn't just cosmetic. It signaled a shift from "developer tool" to "platform for everyone to build software."

But the interesting part isn't the rebrand. It's why he started with open source in the first place.

Why Open Source?

Anton Osika had three reasons for going open source first:

1. To Prove It Works

His team didn't believe AI would change anything in the near future. So he needed to prove them wrong.

He spent a weekend (maybe two weeks) building the first version and open-sourced it. Why open source? Because anyone could verify it worked. No closed demos, no smoke and mirrors.

It was the most convincing form of proof.

2. To Iterate With the Community

gpt-engineer was designed to be "easy to experiment with"—you could add reasoning steps, modify the process, and tinker with it.

By open-sourcing it, he got feedback from developers worldwide. That feedback directly improved the product.

Result? 52,000+ GitHub stars and one of the fastest-growing repos on GitHub.

3. To Build Community First

Open-sourcing the CLI tool created a passionate early user base before the commercial launch.

When the commercial version dropped:

Top of Product Hunt and Hacker News
Hundreds of paying users overnight
75+ five-star reviews

The open-source version basically became free marketing that built trust and credibility.

The Smart Part: How They Split It

Here's what's clever: they didn't close the open-source version when they launched the commercial one.

Both still exist. Here's how they differentiate:

Open Source (gpt-engineer)

CLI tool
For developers and tinkerers
Maximum flexibility
Experimental use cases

Commercial (Lovable)

Web platform
For everyone (including non-technical users)
Polished UX
Production-ready with support

The strategy: Open-source the core tech, monetize the UX and operational support.

Turns out, you can give away your "business logic" and still have plenty to monetize.

The Results Speak

Let's look at what open-sourcing achieved:

Community Side:

52K+ GitHub stars
Active contributors
Tons of forks and customizations
Natural word-of-mouth growth

Business Side:

Zero traditional marketing spend
High-quality user acquisition
Built-in trust and credibility
Smooth transition to paid product

The "risk" of open-sourcing turned into the biggest growth lever.

The Philosophy Behind It

What made this possible wasn't just strategy. It was Anton Osika's philosophy.

Effective Altruism

Anton is an Effective Altruist. He wants to maximize impact on the world. For him, Lovable isn't just a business—it's a way to unlock human potential by democratizing software creation.

When you're optimizing for impact rather than just profit, open-sourcing makes more sense.

From CERN to Startups

Anton used to be a physicist at CERN. He observed something there: incredibly smart people working on highly inelastic problems.

Inelastic = more input doesn't proportionally increase output.

He realized the private sector had more "elasticity"—the same effort could create much bigger outcomes. So he left academia and started building.

First Principles Thinking

Coming from physics, Anton thinks from first principles. That means questioning assumptions like "you must protect your business logic."

Instead, he asked: "What actually creates value for users?"

Answer: Great UX, reliability, and support. Not secret algorithms.

What We Can Learn

Here's what Lovable's case teaches us:

1. Open Source Can Be Your Marketing

Instead of spending on ads, they spent on building in public. The community did the marketing for them.

2. Community Is an Asset

52K stars aren't just a vanity metric. They're:

Engaged early users
Feedback providers
Word-of-mouth amplifiers

3. Differentiation ≠ Secrecy

You don't need to hide your tech to differentiate. Lovable proved you can:

Open-source core tech
Differentiate on UX and operations
Build a sustainable business

4. Philosophy Enables Risk-Taking

Anton's Effective Altruism mindset made open-sourcing possible. His mission was bigger than protecting IP.

Without that philosophical foundation, taking that risk would've been much harder.

The Real Question

Here's what I keep thinking about: Is business logic really the defensible moat we think it is?

Lovable suggests: maybe not.

Maybe the real moat is:

Community trust
User experience
Operational excellence
Support and reliability

And maybe open-sourcing your tech is the fastest way to build that trust.

Knowing vs. Doing

I knew open-source strategies could work. I've seen successful examples.

But knowing something works and actually doing it are completely different things.

The fear of being copied, the anxiety about losing competitive advantage, the pressure to monetize immediately—all of that makes open-sourcing scary.

What Anton Osika showed is that overcoming that fear isn't just about courage. It's about having a clear philosophical foundation that makes the decision obvious.

Final Thoughts

Lovable's story changed how I think about "protecting" business logic.

The conventional wisdom—"don't open-source your core tech"—might be wrong in many cases. Or at least, more nuanced than we think.

Open-sourcing can be:

A proof mechanism
A marketing strategy
A community-building tool
A trust signal

Whether you can pull it off depends less on the risk calculation and more on your mission and philosophy.

So the question isn't just "Should I open-source?"

It's "What am I really trying to build, and for whom?"

References

If you want to dig deeper, here are the sources I used:

Lovable Official:

Interviews & Analysis:

Philosophy & Background:

GitHub:

gpt-engineer

I write more about these kinds of decisions and thought processes on my blog:

https://tielec.blog/

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