About our Mission, our Core Values, our Manifesto & more

What means 'Own Your Code' to us?

No-code platforms like Webflow and Wordpress offer quick setup but limited control. Owning your code means having full control over your technology and business.

No-code works for simple updates, but structural changes require code access. This reduces vendor lock-in and enables deeper system integration.

Most importantly, owning your code enables effective AI integration - custom data pipelines and model implementations that no-code platforms simply cannot support.

Why do we do QA on (almost) Everything?

Too many projects fail due to insufficient quality assurance. We integrate QA into every step of development.

We test everything: code, pipelines, design, content, and infrastructure. Each element gets measured, monitored, and continuously improved.

AI enhances our QA through automated test generation, anomaly detection, and predictive analysis - finding issues humans might miss.

Why do we attempt to think small and pragmatic?

The best code is the code not written - it introduces no bugs and needs no maintenance.

We build incrementally, starting with minimal solutions that solve core problems. This reduces cost, accelerates value delivery, and allows for adaptation.

AI supports this approach by enabling rapid prototyping and data-driven refinement, helping us deliver value faster.

What means to follow the masses for us?

System design changes are expensive. We select technologies based on community strength, proven reliability, and talent availability rather than novelty.

We favor open source over closed source to reduce vendor lock-in and improve system integration options.

This doesn't mean avoiding innovation - we innovate in business logic while building on stable foundations. For AI especially, widely-used frameworks benefit from collective improvement and extensive testing.

Why should we not use hammers for scaling?

When all you have is a hammer, every problem looks like a nail. This bias is particularly dangerous for scaling decisions.

We scale iteratively, focusing on specific bottlenecks rather than applying generic "scaling solutions." Every system has unique scaling characteristics that demand custom approaches.

Before scaling, we question whether it's truly necessary. Often, optimization or requirement refinement eliminates apparent scaling needs without added complexity.

Why should we embrace asynchronous communication?

Asynchronous communication reduces interruptions and enables focused work. It creates documented decision trails and allows collaboration across time zones and work styles.

We use tools like GitHub, Slack, and documentation systems to minimize real-time dependencies while maintaining team alignment.

AI enhances this approach through intelligent summarization, prioritization, and knowledge extraction, making our async communication more effective.

Why do we emphasize data-driven decision making?

Imagine you're navigating an unfamiliar city without a map - it's hard to know where to go unless you trust the data in front of you. That's why every significant decision we make is backed by data.

From day one, we set up analytics systems that act like signposts, helping us gauge what's working and what isn't. Think of A/B testing as a taste test for your product features, where the results guide us to the best recipe. With AI as our co-pilot, we unlock hidden insights and make informed, impactful choices, ensuring we stay on the right track every step of the way.

Why is security by design crucial?

Building software without considering security is like building a house without locks—inviting trouble. For us, security is not an afterthought; it’s part of our blueprint.

We integrate security checkpoints at every stage of development, much like a series of toll gates on a highway to ensure safe passage. Regular audits, AI-powered threat detectors, and security training ensure we proactively address risks, leaving no door unlocked. This approach creates robust solutions—secure from the moment they’re deployed.

Why treat documentation as code?

Good documentation is like a compass—it keeps everyone moving in the same direction. To us, documentation isn’t a dusty manual sitting in the corner. Instead, it’s a living, breathing entity that grows alongside our code.

By version-controlling our documentation and automating its generation, we ensure it stays as relevant and useful as a GPS in a modern car—not an outdated paper guide. AI tools act as grammarians, refining and polishing our docs to make them easily navigable for both technical teams and stakeholders.

Why focus on sustainability in software development?

Technology shouldn't just work well—it should use its resources responsibly, like driving an electric car instead of a gas guzzler.

We optimize for energy efficiency, reduce wasteful practices like excessive technical debt, and use green hosting. AI lends a hand, like a resourceful sous-chef minimizing food waste, ensuring we get the best results with minimal environmental impact.

Why is effective change management crucial?

Change in technology is like sudden weather shifts — it’s inevitable, and being unprepared can throw you off balance. Structured change management acts like a sturdy umbrella to help us weather these shifts.

We assess the impact of change meticulously, communicate transparently, and learn from every implementation. AI tools act as meteorologists, predicting the outcomes of changes, helping us stay proactive and adaptable.