In an exclusive Interview with ITProfiles, Anze Sterbenc, CEO of Calda, shares a pragmatic view on how artificial intelligence is reshaping what clients expect from modern development teams. As more businesses experiment with AI tools before engaging professionals, expectations are shifting toward speed, efficiency, and lower costs, but not always with a full understanding of what it takes to build production-grade systems.
He explains that while AI has made it easier than ever to prototype ideas, it has also exposed a clear gap between quick outputs and scalable, secure products. Many clients enter with confidence after using AI, only to realize that real-world systems demand deeper thinking, stronger architecture, and a more contextual understanding of their challenges.
Through this conversation, Anze highlights a consistent theme: the future is not about choosing between AI and humans, but about combining human creativity, judgment, and problem-solving with the efficiency of AI. The teams that succeed will be the ones that know how to balance both while continuing to move up the value chain.
Why smart clients still choose human teams over $20 AI tools
Anze Sterbenc frames this reality through what clients experience firsthand. Many begin with AI tools, expecting fast and cost-effective results, but quickly realize that what they get is often limited to early-stage prototypes. The gap between something that works and something that is production-ready becomes immediately visible.
Because building production-grade systems requires more than generating code, it demands an understanding of real constraints, edge cases, and long-term impact. AI can accelerate initial output, but it still struggles to carry that output into stable, scalable environments where decisions have consequences.
As he explains, “In many cases they start with AI, but quickly see that it's not capable to deliver anything more than a working prototype yet.” That realization shifts how clients evaluate value, moving away from cost and toward reliability.
The founder emphasizes that human expertise brings context into the equation. Understanding the actual challenges a business faces, and designing solutions around them, is what transforms a prototype into a product that can survive in real-world conditions.
What AI-only projects often fail to handle in real business scenarios
Anze sees a recurring pattern with clients who initially rely on AI-driven or vibe-coding tools to get started. These tools are effective for building quick prototypes, and many teams use them to validate early ideas before involving a human team.
However, the limitations become clear the moment the product needs to evolve beyond that initial stage. What seemed efficient at first begins to show cracks when requirements expand toward scalability, security, and more complex functionality.
As he explains, “the ‘ceiling’ of any 100% AI developed product is very low,” especially when the goal shifts to building something that is stable, secure, and ready for real-world usage. The gap between prototype and production is where most AI-only approaches fall short.
The founder emphasizes that production-grade systems require deliberate architecture, careful handling of edge cases, and an understanding of long-term growth. These are not just technical upgrades, but decisions that demand human judgment and experience beyond automated generation.
How human empathy keeps clients steady when projects hit a wall
Anze looks at empathy not just as reassurance, but as the foundation of a working relationship. When projects hit a wall, the real difference is not just in solving the issue, but in how teams engage with clients during uncertainty.
A human team brings perspective into the conversation, not just answers. Instead of passively executing, they challenge assumptions, ask better questions, and help clients rethink the situation when needed. That interaction creates clarity, which naturally reduces anxiety.
As he explains, “A human can challenge clients' ideas, can provide a different perspective on challenges that they are facing, can offer unique creativity and ideas.” This dynamic shifts the relationship from transactional to collaborative.
The founder emphasizes that Artificial Intelligence tends to agree and execute, but rarely questions direction. That lack of pushback often leads to less refined outcomes, whereas human interaction introduces critical thinking, creativity, and trust into the process.
Why “human strategy” is evolving beyond a label into a balanced approach
Anze agrees that human-led thinking is increasingly seen as a signal of quality, but he does not view it as a standalone answer. The real shift is not toward excluding AI, but toward using it more intelligently alongside human creativity and judgment.
Because relying purely on a human-only approach in today’s landscape means ignoring a powerful advantage. AI has become one of the most impactful tools available, especially when it comes to accelerating development and handling repetitive layers of execution.
As he explains, “the right way moving forward is a combination of human creativity and AI efficiency.” That balance allows teams to move faster without compromising on depth or originality.
The founder emphasizes that this hybrid approach is what enables the creation of enterprise-grade products at speed. Human thinking drives direction and innovation, while AI enhances efficiency, making the combination far more effective than either working in isolation.
The one human skill that will define irreplaceability in the next year
Anze points to creativity as the core human advantage that will continue to stand out, even as AI becomes more capable. While tools can replicate patterns and accelerate execution, they still depend on direction, and that direction comes from original thinking.
Because creativity is what shapes ideas into something meaningful, not just functional. It influences how problems are approached, how solutions are designed, and how products stand apart in increasingly competitive markets.
As he puts it, “Creativity.” The simplicity of that answer reflects its weight, especially in an environment where everything else is becoming easier to automate.
The founder emphasizes that creativity is not just about design or innovation in isolation. It is about connecting ideas, challenging norms, and building something that feels intentional, which is exactly what keeps human-led teams relevant.
How to stay human and trustworthy in an AI-saturated content landscape
Anze approaches this challenge by being intentional about how and when AI is used. Instead of relying heavily on automated content generation, the focus is on preserving a voice that reflects real thinking and internal perspective.
Because consistency in tone and values cannot be outsourced entirely to tools. Strong brand guidelines ensure that every piece of content aligns with how the company thinks, communicates, and positions itself in the market.
As he explains, “We minimise the use of AI when writing our content.” That decision is less about rejecting AI and more about protecting authenticity where it matters most.
The founder emphasizes that sounding human is not accidental; it is designed. By grounding content in real viewpoints and maintaining a consistent voice, the brand remains relatable and trustworthy even in a crowded, AI-driven space.
What bots will never fully understand about real-world systems
Anze points to a limitation that shows up quickly in practice: bots struggle to truly understand the unique problems users are facing. While they can generalize patterns across industries, they often miss the nuance that defines individual use cases.
Because real-world challenges are rarely standardized, they are shaped by specific contexts, constraints, and user behaviors that do not always follow predictable patterns. That uniqueness is what makes each product and system different.
As he puts it, “Unique problems that users are facing.” It may sound simple, but it highlights a gap that automated systems cannot fully bridge.
The founder emphasizes that solving these problems requires listening, interpretation, and adaptation. It is not just about applying known solutions, but about understanding what makes each situation distinct and responding accordingly.
Why instinct and data work best together in critical decisions
Anze sees this not as a competition, but as a balance that every founder must learn to manage. Data provides the structure needed to make informed decisions, offering clarity on what is happening and why certain patterns emerge.
Because without data, running a business becomes guesswork. It anchors decisions in measurable reality and helps teams avoid purely reactive or emotional choices that can lead to inconsistency.
As he explains, “Hardcore data allows us to make informed decisions, and without it you can't run a business - simple as that.” That foundation is non-negotiable in any serious operation.
At the same time, instinct plays a critical role when decisions move beyond clear metrics into strategy and direction. The founder emphasizes that neither can replace the other, and it is the combination of both that enables confident, well-rounded decision-making.
Will the future be bot-first, or are we heading toward more human-led work?
Anze sees the current moment as part of an AI “hype cycle,” where it feels like almost everything can be handled by automation. While that perception is driving rapid adoption, he believes it is also setting unrealistic expectations about what AI can sustainably deliver on its own.
Because as the dust settles, the limitations become clearer, especially in areas that require creativity, judgment, and problem-solving rooted in human intuition. These are not easily replicated, and over time, they become more valuable, not less.
As he explains, “people will start appreciating human creativity and ability to solve complex problems based on human intuition even more in the future.” That shift will redefine what clients look for when choosing who to work with.
The founder emphasizes that this evolution will also raise the bar across the market. Low-level, execution-only services will likely become redundant, while teams that combine creativity, strategic thinking, and technical depth will be the ones that survive and lead the next phase of the development industry.