Professionele Ontwikkeling
Professional development is about more than acquiring new skills, trainings, or certifications. It is the process in which a professional learns to use themselves ever more finely as an instrument — with greater awareness, more inner space, and stronger ownership. In this theme, we approach professional development as a psychodynamic and HUMAN–AI challenge.
A psychodynamic perspective means seeing how history, beliefs, and loyalties travel with you into your work. Perfectionism that sets your pace. Pleasing that dissolves your boundaries. The fear of being seen as incompetent that makes you cautious. The drive to be indispensable that leads you to take over what should actually be shared. This undercurrent shapes your professional style: how you collaborate, make decisions, carry tension, set boundaries, or avoid. Development begins where you not only understand these patterns, but recognise them in the moment — and are able to connect different behaviour to them.
At the same time, professional practice is increasingly mediated by AI: retrieving knowledge, producing text, analysing, prioritising, preparing decisions. This makes the question more urgent: what is still my own craftsmanship, and what do I leave to systems? AI can accelerate, but also flatten: your judgement becomes thinner, your curiosity smaller, your dependence greater on outcomes you no longer truly understand. Professional development in a HUMAN–AI context therefore calls for three interrelated movements: self-inquiry (which patterns do I bring with me — especially under pressure?), deepening of craftsmanship (not only knowing that AI can do something, but understanding how and with which assumptions), and conscious positioning (which role do I choose in relation to technology — user, co-shaper, critical countervoice).
In this theme, AI is not a trick, but a mirror and practice material. It reveals how you deal with uncertainty, responsibility, and authority: do you hide behind systems, or do you remain the owner of your judgement? Development then becomes transformation from the inside out: you do not merely become better at your work, you become freer in how you do it.
Intervention
In this theme, AI is not a trick, but a mirror and practice material. It reveals how you deal with uncertainty, responsibility, and authority: do you hide behind systems, or do you remain the owner of your judgement? Development then becomes transformation from the inside out: you do not merely become better at your work, you become freer in how you do it.
Psychodynamically, we work with the inner logic behind your professional style: pleasing, controlling, rescuing, avoiding, perfectionism. These are not isolated traits, but defence mechanisms and loyalties formed over time. We work with cases where there is friction: moments when you say yes while feeling no, shut down, overcompensate, take over, or disappear. Tension is not a disturbance here but data: it reveals where your capacity, freedom, and boundaries are not yet congruent.
Systemically, we place your professionalism within the context in which it takes shape. Position, mandate, expectations, and informal rules colour what you can and cannot do. We examine how your patterns interact with team, organisation, and governance: when do you carry tension that actually belongs elsewhere, when do you pass it on, and when do you sustain patterns by compensating? Professional development thus always also involves role and positioning development: learning to choose what is yours, what belongs to the system, and where you can make a difference.
We explicitly include HUMAN–AI as a socio-technical reality. Craftsmanship is increasingly mediated by systems: in analysis, communication, planning, and decision-making. We explore how you relate to AI: do you use it as a tool, a rescuer, an alibi, or an opponent? Which judgements do you outsource, and which do you consciously keep with yourself? In this way, AI becomes both practice material and a mirror for professional maturity.
How we intervene is consistent and practice-oriented. We start from the task of your role — where do you need to make a professional difference? — and work with real situations from your agenda rather than abstract competency lists. We design learning trajectories in which working and learning coincide, and build a holding environment that is safe enough to face yourself and sharp enough not to look away. Ownership remains with you: DBVP is a guide, mirror, and challenger, not the one who “fixes” you. In this way, professional development becomes a process of transformation from the inside out: your repertoire expands, your freedom of action increases, and you use AI in a way that deepens rather than erodes your craftsmanship.
Methodological considerations
At DBVP, we view professional development as working on inner professionalisation: how you use yourself as an instrument within a field of organisational expectations, undercurrents, and AI systems. We therefore begin with the role task: without a clear intention, development quickly becomes self-improvement without direction. We work from transformation from the inside out: behaviour changes sustainably when you learn to recognise and work with your motives, fears, and loyalties. At the same time, we take a systemic view of your position — mandate, expectations, informal rules, and team and organisational dynamics — because professional action is always partly a product of the system. And we explicitly include HUMAN–AI: how technology influences your pace, visibility, and judgement, and the stance you consciously choose in relation to it.
Typical methods and techniques
We often begin with a role and biographical exploration in which formative experiences, successes, and breaking points are examined, always connected to your current role. From this, we formulate a sharp development task: not general (“setting boundaries better”), but precise enough to test in practice (“in consultation X, I remain grounded in my judgement, even when the system suggests otherwise”).
We then work with living cases: recent situations where there was friction — boundaries, mistakes, criticism, tense collaboration, or moments when AI outputs shifted your actions. We slow down around key moments and explore what happened internally, relationally, systemically, and technologically. From there, we develop alternative courses of action and the inner work required to truly be able to take them.
We embed reflective practices in the line, such as facilitated peer consultation around real cases and short reflection loops after significant events. In doing so, we practise thinking out loud and metacommunication in daily work: giving words to what you observe, feel, and need, without escalating or disappearing.
Where relevant, we engage in HUMAN–AI–specific work: examining your own use of AI — where it is support, where it becomes an excuse, where it turns into dependency — and exploring cases in which system logic clashes with professional or moral judgement. From this follow concrete, personal agreements: which judgements you never fully outsource, which questions you always ask, and which checks are standard parts of your craftsmanship.
Finally, we coach in and around the work: in short cycles, connected to real moments, and sometimes through shadowing with debriefing. In this way, it becomes visible how you use yourself, what this evokes in others, and where your freedom can grow.
Throughout, the principle holds: DBVP brings language, sharpness, and a holding environment; you bring your practice, patterns, and courage. Professional development thus becomes an ongoing process of inner refinement and mature collaboration with the system and with AI.
Training
Training is pas waardevol als het meer oplevert dan kennis. In veel organisaties is leren verworden tot een event: een dag weg, een map met tools, een goed gevoel—en daarna terug naar hetzelfde patroon. Opleiden in DBVP-context is iets anders. Het is het ontwikkelen van waarneming, taal en handelingsvermogen: leren zien wat er gebeurt, woorden vinden voor wat impliciet blijft, en in het moment iets anders kunnen doen—precies daar waar het spannend wordt.
Dat vraagt een andere opzet. Minder zenden, meer werkplaats. Minder generaliseren, meer casuïstiek. Minder “tips”, meer oefenen in het echte dilemma. In onze trainingen is de praktijk niet een voorbeeld, maar het materiaal. De deelnemer werkt met eigen situaties: gesprekken die uitgesteld worden, teams die in cirkels praten, besluitvorming die stagneert, weerstand die verkapt is, leiderschap dat te veel draagt of juist wegblijft. Het leren ontstaat door het patroon te herkennen, te begrijpen wat het functioneel doet, en alternatieven te oefenen die wél werken.
Een belangrijk deel daarvan is psychodynamisch vakmanschap: begrijpen hoe spanning zich organiseert in gedrag. Waarom mensen vermijden, rationaliseren, verharden of pleasen. Hoe loyaliteiten en projecties het gesprek sturen. En hoe je als professional kunt blijven staan zonder te escaleren of te verdwijnen. Training maakt dit niet zwaar of therapeutisch, maar praktisch: welke interventie past hier, welke taal helpt, welk ritme is nodig om te leren en bij te sturen?
In een tijd van AI verandert vakmanschap bovendien in hoog tempo. Professionals krijgen toegang tot analyses, suggesties, teksten en besluiten in wording. Dat vergroot de snelheid, maar ook het risico op schijnzekerheid. Wat niet meer vanzelf groeit, is oordeel. Het vermogen om aannames te herkennen, datakwaliteit te proeven, uitkomsten te bevragen, en verantwoordelijkheid niet te verplaatsen naar een systeem. Training en opleiding moeten daarom HUMAN–AI volwassen maken: niet alleen “hoe werkt het”, maar vooral hoe werk jij ermee, wat laat je ondersteunen, waar blijf je zelf aanwezig, en hoe leg je keuzes uit aan anderen?
Leren gaat uiteindelijk over cultuur. Over wat normaal wordt. Over de ruimte om fouten te bespreken zonder schuld, en om conflict te gebruiken zonder beschadiging. Daarom zijn trainingen vaak het meest effectief wanneer ze verbonden zijn aan een bredere veranderbeweging: een leiderschapsteam dat dezelfde taal leert spreken, een programma dat leerloops nodig heeft, of een organisatie die tegenspraak expliciet wil organiseren.
Waar we aan werken
- waarneming: patronen herkennen in taal, gedrag en onderstroom
- interventiekunde: gesprekken voeren die anders blijven liggen
- besluitvorming en eigenaarschap: van praten naar kiezen en dragen
- leren als ritme: reflectie en bijsturing inbouwen in het werk
- mens–AI: kritisch gebruik, transparantie, verantwoordelijkheid en ethiek
Wat merkbaar wordt
- meer professionele scherpte en rust onder druk
- betere gesprekken: precies, eerlijk en werkbaar
- sneller leren van frictie en fouten
- AI-gebruik dat waarde toevoegt zonder menselijkheid te verliezen