Schutten.Cloud | Where Technology Meets Leadership

Onboarding is not an HR process

Every organization talks about Customer Experience. Increasingly, they talk about Employee Experience too. There are conferences dedicated to it. Dashboards measuring it. Entire software platforms promising to improve it. And yet, I continue to see organizations where a new employee spends the first weeks chasing a laptop, waiting for system access, wondering who to ask about a lease car, or discovering that nobody seems entirely sure what should happen next. That isn't an HR problem. It is an organizational one. The first experience shapes everything We often assume culture is something employees discover over time. I don't think that's true. Culture starts on day one. Not during a presentation about company values. Not during an all-hands meeting. Not because someone tells you what the organization stands for. Culture emerges from dozens of seemingly insignificant moments. Was someone expecting me? Was my manager prepared? Did my accounts work? Did I know where to go for help? Did different departments seem connected, or did I become the person connecting them? None of those moments appear in an annual report. Yet together they answer a much bigger question: "Do these people have their organization under control?" Every small interaction builds operational trust Trust is often discussed as something leaders earn over months or years. But there is another kind of trust. Operational trust. It has nothing to do with charisma. It comes from consistency. Every smooth handover, every proactive update and every well-prepared first day tells a new employee the same thing: "Someone thought this through." The opposite is equally powerful. Every missing approval. Every unanswered question. Every process that requires the employee to coordinate departments that should already be working together. Those moments don't just create frustration. They quietly undermine confidence in the organization itself. Onboarding is not an HR process This is perhaps the biggest misconception. Organizations often divide onboarding into responsibilities.HR prepares the contract. IT provisions the laptop. Facilities arranges a desk. Procurement orders the phone. The hiring manager schedules introductions.Individually, each team may perform perfectly. Collectively, the experience can still fail. Because onboarding isn't a collection of departmental tasks. It is the first end-to-end process an employee experiences. The employee doesn't care where HR ends and IT begins. They experience one company. Which means onboarding is not an HR process. It is one of the clearest demonstrations of operational excellence a company will ever give. Or fail to give. Culture is experienced before it is explained Organizations spend enormous effort defining culture. Mission statements. Leadership principles. Core values. Internal campaigns. Most of them are well intended. But people don't believe culture because they read it. They believe culture because they experience it. If your organization says people matter, but nobody notices a new colleague waiting three days for access to essential systems, the employee remembers the experience. Not the PowerPoint. Culture is never communicated as effectively as it is demonstrated. Different people need different beginnings One of the mistakes organizations make is assuming everyone wants the same onboarding experience. Some people want structure. Others want autonomy. Some appreciate detailed guidance. Others would rather receive a laptop, a login and the freedom to explore. Neither approach is right. Neither is wrong. The real challenge is recognizing that equality does not always mean uniformity. Good organizations don't standardize people. They standardize quality while allowing room for individual needs. AI isn't replacing onboarding Every technology conference seems to ask the same question: "What's our AI strategy?" Perhaps a better question is: "Which problems are we still asking people to solve manually?" Ironically, many onboarding activities have already been automated for years.HR-driven provisioning creates accounts automatically. Identity platforms assign access. Workflow engines trigger approvals.The technology already exists. Yet the employee experience often remains fragmented. Not because automation is missing. But because the process itself was never designed as a single experience. That is where AI becomes genuinely interesting. Not as another chatbot. But as an orchestration layer. An assistant that notices a laptop hasn't been delivered before the employee does. That reminds managers of conversations they should have already scheduled. That recognizes dependencies across HR, IT, Facilities and Procurement before they become delays. That answers questions before someone has to ask them. The real opportunity isn't replacing people. It is removing unnecessary friction between the people who are already involved. Why CEOs should care Too often, onboarding is delegated. HR owns part of it. IT owns another. Facilities owns something else. Everyone has responsibilities. Nobody owns the experience. That should concern every CEO. Because onboarding is rarely remembered for a single event. It is remembered as a pattern. A pattern that answers one simple question: "Is this an organization that operates deliberately, or one that reacts continuously?" That first impression influences trust. Trust influences engagement. Engagement influences retention. And retention ultimately influences business performance. This is no longer an HR conversation. It is a leadership conversation. Final reflection Organizations often say that people are their greatest asset. I believe most leaders genuinely mean it. But beliefs become visible through design. The first weeks of employment are not simply about receiving a laptop, signing policies or collecting access rights. They are the first demonstration of how an organization thinks, collaborates and executes. Customers experience your products. Employees experience your organization. Both form opinions remarkably quickly. The difference is that customers can walk away. Employees first decide whether they believe your culture. Only afterwards do they decide whether they want to become part of it.

When integrity costs your seat, but saves your leadership

There’s a version of corporate leadership that looks structured on paper, but in practice runs on something far less formal: influence, alliances, internal politics, and the quiet redistribution of power. I didn’t just observe that system. I operated inside it. And at a certain point, I made a conscious decision about where I stand in it. I held a senior leadership responsibility across technology, engineering, architecture, portfolio and product domains within a large managed services organization in the Netherlands. On paper, authority is defined by role. In reality, authority is defined by whether people choose to respect it. And once that alignment breaks, you are no longer in a stable system. You are in a political one. At that point, there are only two options left: adjust your principles to fit the environment, or stay aligned with your own standards and accept the consequences of that choice. I chose the latter. The shift that starts before it is visible These kinds of transitions rarely start where people think they start. In my case, the shift began with a change in the leadership layer above me. The Managing Director was pushed out after internal disagreement about direction and leadership style. Two senior directors had already aligned in that process. From that moment on, the balance inside the executive team changed. Influence started to outweigh structure. One of those directors—let’s call him Harry, responsible for service delivery and customer engagement—began pushing for organizational redesigns that would significantly increase his span of control. Most of the leadership team did not fully align with that direction. But disagreement has limited impact when escalation mechanisms no longer function as safeguards, but become formalities. At the same time, behaviour that normally would be addressed through direct leadership accountability was handled differently in practice. Escalations. Emotional outbursts. Walking away from responsibility. Periods of absence. And instead of direct intervention, the response was containment: home visits, informal conversations, coffee at kitchen tables. Not necessarily ill-intended. But structurally inconsistent. And that inconsistency sends a very clear signal into any organization: accountability is not applied evenly. Once that signal is embedded, culture changes faster than policy ever can. When you become the inconvenient perspective At a certain point, I became the person who no longer fully aligned with how decisions were being made and how behaviour was being interpreted. Not because I was opposing change, but because I refused to normalize inconsistency in leadership accountability. There was a moment where trust in my position was explicitly questioned by Harry. I asked the rest of the leadership team a simple question: Do you stand behind me? The answer was yes. Privately, there was alignment. Publicly, nothing changed. No correction. No reset. No visible follow-through. That gap is not neutral. That is where organizations start to drift. Because it exposes a fundamental truth: internal agreement does not automatically translate into external action. From that point on, I stopped experiencing the environment as a purely functional system. It became political navigation. When leadership meets cost logic Later, financial pressure added another layer. A proposal emerged that effectively meant structurally assigning low performance ratings in order to reduce headcount through forced exits or settlements. Not based on performance reality, but as a mechanism. I did not participate in that approach. Not selectively. Not conditionally. Not partially. That created tension that unfolded over time. It was often framed as “just how things work in organizations”. I don’t accept that as a default argument. Because there are moments where that sentence is exactly the problem, not the explanation. I escalated the matter to holding level with a simple request: Address it. Don’t ignore it. Don’t leave it in silence. What followed was not resolution, but hesitation. Fear of internal relationships. Fear of political consequences. Fear of reputational friction. And as a result, nothing changed. But nothing is also a decision. Just an unspoken one. The meeting that clarified everything Weeks later, I had a conversation with Garry, a holding-level portfolio director (superior to the Managing Director, in this moment interim Managing Director himself), about the increasing tension between responsibilities, behaviour, and unresolved accountability. The conversation itself was calm. Not emotional. Not escalatory. But it became a defining moment. I stated clearly that I could not continue operating in a system where accountability was inconsistent and where responsibilities were continuously blurred in practice. That was not a complaint. It was a conclusion. Afterwards, a message followed suggesting that the initiative for separation was placed with me. That was not my intention, and I immediately corrected that position. But something had already shifted. Not formally. Structurally. From that point on, one thing became unavoidable: the system was not going to self-correct in a way that aligned with my standards of leadership integrity. And that meant the real question was no longer whether things would change. It was what staying would require from me. The disappearance of a role during absence In the period after the conversation with Garry, I deliberately took a few days of distance from the day-to-day environment. Not as a withdrawal, but to process a moment that was, for me, professionally significant and personally disappointing, and to reflect on next steps with clarity. Shortly after that brief period of distance, I was confronted with an unexpected medical situation and required surgery. That immediately shifted the context from reflection to recovery. While I was away from the organization for medical reasons, the system continued to move. Technology operations, engineering leadership, and all my other responsibilities were split into separate functions. Responsibilities were redistributed. People were promoted into those areas. Reporting lines were changed. None of this involved me. No consultation. No alignment. No conversation. It simply happened in my absence. Returning to something that no longer exists Six months later, I was ready to return. What I returned to was not a paused role. It was a structure that had already been fundamentally redesigned. There was no longer a coherent function to step back into. There was a new Managing Director, who didn't know me, or the role I had. The role still existed on paper once. But not in reality anymore. In that moment, I did not experience confusion. I experienced clarity. In the meantime, conversations had taken place about alternative directions. Senior leadership roles within other entities in the same holding structure. Advisory positions. Holding-level functions. I participated in those conversations. I explored them in good faith. I engaged with them professionally. But underneath it, one thing was already true: I was not looking for a way back in. I was observing whether there was still a meaningful way forward inside the same system. And I concluded there wasn’t. So the decision became simple. Not emotional. Not reactive. Clear. I chose not to return. Not because I had lost something. But because I no longer needed to stay in a system where alignment required compromise on principle. And I choose not to build success in environments where I do not believe in the foundation. I would rather lose on my own terms than win on someone else’s. What this revealed to me What stayed with me was not frustration. It was clarity. Organizations are often far more decisive when redistributing power than when addressing behavioural inconsistency. The same system that struggled to intervene when it mattered most became highly efficient when restructuring in my absence. That contrast is not incidental. It is diagnostic. It shows where real power sits. Not in org charts. But in influence, alignment, and internal stability. Integrity as a leadership position Over time, something became non-negotiable for me. I do not operate from fear. Not in leadership. Not in decisions. Not in how I treat people. My baseline is simple: Remove status, politics, and self-interest, and ask what the right decision is. That is not always comfortable. And it is rarely rewarded in the short term. But I remain convinced of this: integrity is not a moral statement. It is a leadership strategy. Because people may tolerate politics for a while. But they do not forget consistency. And they talk. I still speak to people from that period. Some are still inside the organization, quietly re-evaluating their path. Some have already left. Some were affected by structural changes that felt more political than performance-driven. And many express the same reflection in different words: this is not what leadership should feel like.Final reflection Leadership is not control. It is followership. And followership is never enforced. It is earned. In the end, I did not lose a role. I made a decision about where I would and would not continue to invest my energy. And that distinction matters. Because sometimes leaving is not loss. Sometimes it is alignment. And that is exactly what this was.

When intelligence becomes something we outsource

We are slowly doing something unusual with intelligence. Not replacing it. Not augmenting it. But outsourcing it. One prompt at a time. Artificial Intelligence tools like ChatGPT, Gemini, and Claude are often framed as productivity multipliers. And they are. They compress time, reduce friction, and make complex outputs accessible at almost no cost. But there is a quieter shift underneath that narrative. We are starting to separate thinking from understanding. And that is where things become fragile. The illusion of competence A well-written prompt can produce a remarkably convincing answer. Structured, fluent, confident, even nuanced. But confidence is not the same as correctness. And fluency is not the same as comprehension. The problem is not that AI produces wrong answers. It is that it produces answers that feel right often enough that we stop checking. And once that habit sets in, something subtle changes: We stop being the system that verifies. We become the system that accepts. Intelligence without ownership There is a difference between using a tool and depending on it for cognition. A calculator never made anyone worse at math. But it also never asked them to understand what it was doing. Modern AI tools sit in a different category. They don’t just compute. They interpret, summarize, explain, reason. Which means they don’t just extend intelligence. They can replace the experience of thinking. And once that replacement becomes comfortable, it becomes structural. The cloud problem, repeated at a cognitive level We have seen this pattern before. Cloud computing abstracted infrastructure:servers became services systems became APIs operations became dashboards complexity became someone else’s responsibilityIt worked brilliantly—until it didn’t. Because abstraction has a hidden cost: distance from reality. And with each layer of abstraction, fewer people understand what is actually happening underneath. Now we are doing the same thing with intelligence itself. From understanding systems to trusting outputs In earlier generations of engineering, you were forced to understand what you built. If a system slowed down, you needed to understand IOPS, memory pressure, CPU scheduling, network latency. Today, many engineers start at the top layer: Deployments, pipelines, managed services, black-box scaling. Even education has adapted. We teach how to use systems, not how they fundamentally behave. And that works—until something breaks outside the abstraction layer. Then the question becomes uncomfortable: Who still understands what is actually happening underneath? The real risk is not AI becoming too smart The real risk is humans becoming too comfortable. Because when AI works well, it removes friction. And friction is often where understanding is formed. If everything just works, there is no need to dig deeper. If nothing requires repair, there is no need to understand cause and effect. If answers are always available, the discipline of reasoning slowly erodes. Not dramatically. Not visibly. But cumulatively. “Just ask AI” is not a strategy There is a growing cultural reflex:Don’t know it? Ask AI. Need it explained? Ask AI. Need a decision? Ask AI.And most of the time, that is fine. Until it becomes the only mechanism. Because AI does not create accountability for truth. It produces plausible synthesis based on patterns. Which means it inherits one critical dependency: There must still be human intelligence capable of questioning it. Not superficially. But structurally. What happens when the underlying knowledge disappears? This is the uncomfortable edge of the argument. What if we gradually lose the ability to independently validate what AI produces? Not because we are incapable. But because we stopped practicing. Then we reach a point where:the system produces an answer nobody truly understands how it was derived and nobody can confidently say whether it is correctAnd at that point, intelligence is no longer something we use. It is something we receive. The paradox of progress We are building systems that make us more capable than ever before. And at the same time, potentially less resilient than ever before. Because resilience is not measured by output. It is measured by what remains when the system is not available. Or when the abstraction fails. Or when the data is missing. Or when the model is wrong. Closing thought AI is not the end of thinking. But it might become the end of careless thinking, if we are intentional. The real question is not whether AI can do the work. It is whether we are still willing to understand the work that is being done on our behalf. Because at some point, the dependency becomes invisible. And when that happens, the most important system we have is no longer artificial intelligence. It is human understanding. And if we outsource that too far, we may eventually discover that we still have answers— but no longer know how to question them.

AI didn't replace engineering. We just stopped talking about it.

Artificial Intelligence has become impossible to ignore. Open Gartner. AI. Read CIO.com. AI. Attend Microsoft Build, Google I/O or AWS Summit. AI. Scroll through LinkedIn for five minutes and you'll quickly get the impression that every meaningful conversation in technology now begins and ends with large language models, autonomous agents and AI-assisted development. I understand the excitement. AI is a remarkable technological breakthrough, and its impact will be difficult to overstate. But I've started wondering about something else. Not what we're talking about. What we've stopped talking about. The conversations that quietly disappeared A few years ago, our industry spent enormous amounts of time discussing operating models, governance, architecture, automation, platform engineering and cloud operating practices. Those conversations weren't glamorous. They rarely filled conference halls. They certainly didn't dominate social media. But they mattered. Because they determined whether technology actually worked once the keynote was over. Today those disciplines seem strangely absent from the conversation, as though AI somehow made them less relevant. It didn't. If anything, it made them significantly more important. Engineering never disappeared One of the more curious assumptions behind today's AI enthusiasm is that intelligence somehow compensates for engineering. That if an AI model can generate code, architecture becomes less important. That governance becomes something you can add later. That operational excellence is simply another problem AI will eventually solve. I'm not convinced. Software has never failed because people lacked ideas. It usually fails because complexity quietly grows beyond anyone's ability to understand or control it. AI doesn't remove that complexity. It introduces an entirely new category of it. Unlike traditional software, these systems are probabilistic. They don't always behave the same way twice. They require validation instead of assumption, observation instead of certainty. That doesn't reduce the need for engineering discipline. It raises the standard. Demonstrations have an unfair advantage One reason the current conversation feels so optimistic is that most of what we see are demonstrations. Someone builds an agent in twenty minutes. Another team generates an application from a prompt. A startup orchestrates half a dozen AI services into something that looks almost magical. And genuinely—it often is impressive. But demonstrations have an unfair advantage. They don't have to survive production. They don't have to operate for three years. They don't have to pass security reviews. They don't have to explain themselves during an audit. They don't wake someone up at three o'clock in the morning because an automated decision suddenly affected thousands of customers. Production has always been where technology stops being exciting and starts becoming accountable. That hasn't changed. Abstraction is a wonderful servant The cloud taught us an important lesson: Abstraction is incredibly powerful. We no longer think about physical servers before deploying an application. Kubernetes allows developers to focus on workloads instead of individual machines. Managed services remove enormous amounts of operational burden. Those are extraordinary achievements. But abstraction has always come with an implicit agreement. Someone still needs to understand what happens underneath. Every abstraction layer increases productivity for thousands of people while simultaneously reducing the number of people who understand the foundation beneath it. That trade-off is acceptable. Until the abstraction breaks. Then expertise suddenly becomes scarce. I wonder what we're teaching the next generation When I speak to younger engineers, I'm often impressed by how quickly they adopt new technologies. Many can build sophisticated cloud-native applications long before they have ever managed a physical server. Increasingly, many can also build AI-powered applications before they've fully understood distributed systems, identity, networking or storage. None of that is their fault. We teach what the industry rewards. And right now, the industry rewards speed of adoption far more visibly than depth of understanding. I sometimes wonder what happens twenty years from now. Not when AI becomes more capable. But when the people responsible for critical systems have never needed to understand the layers beneath the abstractions they inherited. The question that interests me most Perhaps this isn't really an article about Artificial Intelligence. Perhaps it's about attention. Technology has always moved in waves. Every few years we collectively decide what deserves our attention, and everything else quietly disappears into the background. Today, AI occupies almost all of that space. Meanwhile, architecture, governance, operational excellence and systems thinking continue doing what they have always done. Quietly determining whether ambitious ideas become reliable systems. Or expensive experiments. Final reflection I have no doubt that Artificial Intelligence will transform our industry. I also have no doubt that most organizations are underestimating what it takes to operationalize it responsibly. Because intelligence alone has never been enough. Not in software. Not in leadership. Not in engineering. Perhaps that is what concerns me most. We celebrate every new abstraction as progress, while paying remarkably little attention to the knowledge it slowly replaces. Every generation of technology asks us to understand a little less of what happens underneath. AI simply accelerates that trend. Maybe that is inevitable. But history has rarely been kind to civilizations that confuse convenience with understanding. The industry is celebrating intelligence while quietly abandoning wisdom. And history has never been particularly kind to civilizations that confused the two.

Employees don't want another survey. They want to be heard.

Every year, thousands of organizations ask their employees exactly the same question. "How are we doing?" The survey has many names. The name hardly matters. The process is almost always the same. Employees are encouraged to be honest. Leadership promises to listen. The results arrive a few weeks later. A dashboard appears. Scores turn green, orange or red. Trends are compared to previous years and benchmarked against other organizations. And then something interesting happens. The organization starts explaining the results before it has really listened to them. The first reaction is almost never curiosity I've seen the same pattern more than once. Leadership gathers around a table to review the results. Some comments are dismissed as unrealistic. Others are explained away. "It's only a snapshot." "People don't see the full picture." "The reorganization clearly influenced the scores." "One department pulled the average down." Sometimes those explanations are entirely reasonable. But they all have one thing in common. They explain the outcome before they explore it. That subtle difference matters. Because the purpose of listening isn't to defend your decisions. It's to understand why people experienced them differently than you expected. Measuring trust doesn't create trust Organizations often invest significant time and money in measuring employee satisfaction. Ironically, they spend far less time creating the conversations that actually improve it. A survey can tell you that trust is low. It cannot explain why. It certainly cannot rebuild it. Trust isn't restored by presenting another PowerPoint with action points. It is restored when people believe someone genuinely wants to understand their experience. Not to agree with everything they say. But to understand it. We keep scaling the wrong thing One of the biggest mistakes organizations make is assuming that more data automatically leads to better leadership. It doesn't. If anything, leadership becomes more difficult when hundreds of comments are compressed into percentages, averages and trend lines. The individual disappears. The story disappears. The nuance disappears. By the time the executive team receives the report, employees have become statistics. That may be useful for reporting. It is rarely useful for understanding people. Leadership happens at dinner tables Imagine something different. Not another annual survey. Not another company-wide town hall where only the confident voices ask questions. Imagine inviting eight employees to dinner every month. No presentation. No agenda. No managers. No HR representative taking notes. Just a conversation. People from different teams. Different ages. Different backgrounds. Different perspectives. Some who have been with the company for fifteen years. Some who joined three months ago. No expectation that everyone will agree. No expectation that every suggestion will be implemented. Just a conversation where people are free to say what they genuinely think. Not because leadership needs more data. Because leadership needs more understanding. People don't expect perfection One of the biggest misconceptions in leadership is that employees expect every problem to be solved. Most don't. People understand that organizations have budgets. Priorities. Customers. Shareholders. Trade-offs. What they struggle with isn't disagreement. It's silence. If an idea isn't feasible, explain why. If priorities changed, explain why. If you disagree, explain why. Adults can handle disagreement remarkably well. What slowly destroys trust is the feeling that feedback disappears into a system that quietly moves on. The purpose of leadership isn't agreement A good leader doesn't exist to validate every opinion. Nor should they. Leadership requires making decisions that not everyone will support. That's part of the responsibility. But responsibility comes with another obligation. People deserve to understand why decisions were made. Not because it guarantees agreement. Because it demonstrates respect. Being heard and getting your way are two very different things. Confusing the two helps nobody. The survey isn't the problem Employee surveys have value. They reveal patterns. They identify trends. They help leaders recognize blind spots. The problem begins when the survey becomes the conversation. Or worse, when it replaces it. Culture isn't built through anonymous questionnaires. It is built through thousands of interactions in which people discover whether their voice genuinely matters. The best organizations don't treat feedback as an annual event. They make listening part of how they lead. Closing Words Organizations often ask employees one important question every year: "How are we doing?" Perhaps leaders should ask themselves another: "When was the last time I had a conversation where someone felt completely free to disagree with me?" Because culture is not measured by a survey. Trust is not created by a dashboard. And leadership is not demonstrated by publishing an action plan. It is demonstrated by listening before explaining. By responding before defending. And by creating an environment where people continue speaking—not because they expect to win every discussion, but because they know someone is genuinely willing to hear it.