Category: Professional Practice

For a long time, I believed that seniority was largely about perspective. The more experience you gained, the further ahead you could see. You recognized patterns earlier. You connected seemingly unrelated issues. You developed a broader view of systems, organizations and change. This understanding is not wrong.

But recently I have started to suspect that it is incomplete.

The Traditional View of Seniority

Many professional careers appear to follow a familiar trajectory:

Operational → Tactical → Strategic

Early in our careers, we focus on execution. Later, we coordinate and manage. Eventually, we become responsible for strategy, direction and long-term thinking.

The implicit assumption is that seniority means operating at increasingly higher levels of abstraction. The higher you operate, the more senior you are. At least, that is what I used to think.

Seeing Further

Experience does bring perspective. An experienced consultant, architect or manager often sees things that others do not. Patterns emerge more quickly. Root causes become easier to recognize. The consequences of decisions become easier to anticipate.

This is one of the rewards of experience. You learn to see further. The problem is that seeing further can become a habit.

The Trap

Once you become accustomed to thinking strategically, it is tempting to view every problem through that lens. A process issue becomes a governance discussion. A delivery challenge becomes an operating model question. A local problem becomes a transformation initiative.

Sometimes this is exactly what is needed. Sometimes it is not. The customer may simply need help solving the problem directly in front of them. In those moments, the broader perspective can become a distraction rather than an advantage. Not because it is wrong. Because it is arriving at the wrong time.

A Different View of Seniority

This led me to a realization. Perhaps seniority is not primarily about operating at the highest level of abstraction. Perhaps it is about moving between levels of abstraction.

The truly valuable expert can discuss strategy in one conversation and execution in the next. They can connect long-term objectives to immediate actions. They can explain the bigger picture without losing sight of today’s challenges. Most importantly, they know which perspective is needed in a particular moment. That is a different skill altogether.

Meeting People Where They Are

Looking back, some of the most effective experts I have worked with shared a common trait. They did not feel compelled to demonstrate how much they knew. They did not constantly elevate discussions to the highest possible level.

Instead, they seemed remarkably good at meeting people where they were. If a strategic discussion was needed, they could provide it. If a practical solution was needed, they could provide that too. Their expertise was visible not because they operated above everyone else, but because they could connect different perspectives effortlessly.

The Paradox

This is where the paradox appears. Many people assume seniority means seeing further. I increasingly believe that true seniority means seeing further without losing sight of what is immediately in front of you.

The challenge is not reaching a higher level of abstraction. The challenge is knowing when to use it. And perhaps the most senior thing you can do is not demonstrate how far ahead you can see. Perhaps it is helping others take the next meaningful step.

An Open Reflection

I am still thinking about this. Partly because it challenges my own assumptions about expertise. For years, I associated growth with moving upward: from operational concerns toward strategic ones.

Today, I am beginning to suspect that maturity may look different. Not a ladder. More like a range. The ability to move freely between perspectives. To understand the larger pattern. And at the same time, remain fully engaged with the problem that is right in front of you.

That seems like a more useful definition of seniority. And perhaps a more difficult one as well.

For most of my life, I assumed that thinking happened before conversation. First, you form an opinion. Then you discuss it. First, you develop an idea. Then you explain it.

Recently, I have started to suspect that my own process works differently. In many cases, I do not seem to know what I think until I begin talking about it.

The Myth of the Blank Page

There are people who appear capable of sitting down with a blank sheet of paper and generating ideas. I have always admired that ability. I have also spent a considerable amount of time waiting for it to happen.

More often than not, it doesn’t. If I sit alone with a problem, I can certainly analyze it. I can gather facts. I can organize information. But genuinely new ideas seem to emerge elsewhere. They emerge in interaction.

Ideas Hidden in Conversation

Looking back, many of the ideas I consider valuable did not appear during solitary reflection. They appeared during discussions. A colleague asked an unexpected question. A customer challenged an assumption. A workshop revealed a pattern. A conversation connected two concepts that had previously seemed unrelated.

The idea was not fully present beforehand. The conversation helped create it. This realization has gradually changed how I think about thinking. Perhaps dialogue is not something that happens after reasoning. Perhaps, for some people, dialogue is part of the reasoning itself.

The Role of Friction

One possible explanation is that conversations introduce friction. A statement is challenged. An assumption is exposed. A contradiction becomes visible. A vague intuition is forced into words. Something that felt obvious suddenly turns out to be difficult to explain.

That friction is productive. It pushes thinking forward. Many of the insights I value most emerged not when someone agreed with me, but when they asked a question I could not immediately answer.

A New Kind of Dialogue Partner

Recently, I have found myself having more of these exploratory conversations with AI. That statement is easy to misunderstand. The interesting part is not that AI provides answers. Nor is it that AI replaces expertise. In fact, many of the observations, experiences and patterns still come from my own work.

What has changed is that there is now an always-available dialogue partner. A half-formed idea can be explored immediately. An observation can be challenged from different angles. A concept can be reformulated until it becomes clearer. A pattern can be tested against examples from other domains.

The value is not that the AI discovers the idea. The value is that the dialogue helps reveal it.

Dialogue as a Thinking Tool

The more I reflect on this, the less I see conversation as a way of communicating finished thoughts. Instead, I increasingly see it as a way of creating them. This applies equally to discussions with colleagues, customers, friends and AI. The common factor is not the participant. The common factor is the interaction.

Ideas become visible when they encounter another perspective. Even if that perspective exists only to ask questions, challenge assumptions or suggest alternative interpretations.

An Unexpected Realization

For years, I believed that I needed to become better at brainstorming. Perhaps that was the wrong goal. Perhaps my mind simply works differently. Perhaps my strongest ideas are not generated in isolation. Perhaps they emerge through dialogue.

If that is true, then conversations are not interruptions to thinking. They are one of the ways thinking happens. And in a world where AI can participate in those conversations, the opportunity may not be that we can get answers faster.

The opportunity may be that we can explore ideas more deeply, more frequently and with less friction than before. I am still trying to understand the implications of that. But the observation itself feels increasingly difficult to ignore.

Some people think by writing. Some people think by reflecting. I appear to think by talking.

I recently realized that I have been thinking about blogs in the wrong way. For most of my professional life, I assumed that writing followed a simple sequence:

Think → know → write

The purpose of a blog was to communicate something that had already been figured out. You learned something. You formed an opinion. You developed a framework. Then you wrote about it. The blog was a publishing mechanism. Nothing more.

The Reporting Blog

This is the type of blog most professionals write. Its purpose is to report existing knowledge. Examples include:

• Lessons learned from a project
• Explanations of a methodology
• Reviews of a framework
• Conference summaries
• Practical advice

The underlying assumption is: I know something that may be useful to others.

There is absolutely nothing wrong with this. In fact, most professional blogs should probably do exactly that. But recently I discovered another possibility.

The Discovery Blog

The second type of blog serves a completely different purpose. Instead of communicating conclusions, it helps generate them. The process looks more like this:

Observation → writing → reflection → insight

The author does not necessarily know where the idea will lead. Writing becomes part of the thinking process. The blog becomes a laboratory rather than a broadcasting platform. This was a surprising realization for me.

Thinking Through Dialogue

The insight became even more interesting when I connected it to something I have noticed about my own way of thinking. I have never been particularly good at sitting alone and brainstorming. Many people seem able to start with a blank page and generate ideas. My mind does not appear to work that way.

Instead, most of my useful ideas emerge through dialogue. A conversation introduces a question. An observation triggers a response. A challenge reveals an inconsistency. A pattern suddenly becomes visible. The thinking happens in the interaction. Only afterwards do I realize what I think.

This explains why some of my most valuable insights have emerged from discussions rather than solitary reflection. The dialogue itself becomes part of the reasoning process.

Writing as a Dialogue

Perhaps that is why the idea of a discovery-oriented blog feels so appealing. Writing does not have to be the final step. Writing can become another form of dialogue. Not necessarily with other people. Sometimes with oneself. Sometimes with future readers. Sometimes with an idea that has not fully formed yet.

A field note captures an observation. The act of writing clarifies the observation. New questions emerge. Those questions lead to new field notes. Over time, a line of thinking begins to develop. The blog becomes part of the conversation.

A Different Relationship with Uncertainty

The discovery blog also changes the role of uncertainty. In a reporting blog, uncertainty can feel like a weakness. The expectation is that the author knows the answer.

In a discovery blog, uncertainty is often the starting point. A good field note can begin with:

I noticed something.

Or:

I am not sure why this keeps appearing.

Or:

These two things seem related, but I do not yet understand how. The goal is not to provide closure. The goal is to make progress.

An Unexpected Possibility

The most surprising realization is that a blog may be useful long before there is anything important to report. In fact, it may be most useful before that point.

Instead of documenting finished ideas, it can help create them. A field note becomes a record of an investigation. A collection of field notes becomes a trail of reasoning. And occasionally, several observations converge into something larger. A hypothesis. A framework. Perhaps even a genuinely new idea.

I used to think that blogs existed to share what we know. I am beginning to suspect that some blogs exist to help us discover it.

This wasn’t supposed to happen.

A few weeks ago, all I wanted was a better CV.

After many years in software development, testing, quality engineering and organisational assessments, my CV had become what many long careers become: a chronological list of projects, responsibilities and technologies. Accurate enough, but not particularly insightful. So I asked an AI to review it.

I expected editorial assistance. Better wording. Better structure. Perhaps a few suggestions on what to remove or emphasize. Instead, something rather unexpected happened.

The conversation moved from my CV to my LinkedIn profile. From there, it became a discussion about recurring themes in my career and what seemed to distinguish me from others with similar backgrounds. Then came a SWOT analysis. Then conversations about positioning and professional identity. Then questions about what kind of work I genuinely enjoy, where I add the most value and, perhaps more importantly, where I don’t.

Somewhere along the way I realised we were no longer talking about my CV at all. We were talking about me. Or more specifically, about the story my career told when viewed as a whole rather than as a sequence of individual jobs.

The discussion became increasingly reflective. If I have another decade or so left in my professional career, how do I actually want to spend it? What do I want to be known for? What kind of problems do I most enjoy solving Where can I contribute something that isn’t simply another pair of experienced hands?

What surprised me most wasn’t that AI could rewrite sentences or suggest bullet points. It was that it could synthesise years of information, recognise patterns across them and offer perspectives that I hadn’t previously articulated myself. Sometimes it asked excellent questions. Sometimes it challenged my assumptions. Sometimes it proposed interpretations that immediately resonated.

Not every suggestion was right. Many weren’t. But enough of them were insightful that they changed the direction of the conversation. And, in a very real sense, they changed the direction of my thinking.

Eventually, the discussion turned into ideas for articles. Then themes. Then potential series of posts. And eventually, almost without noticing it, I found myself planning a blog. That’s why you’re reading this.

This won’t be a blog about AI, although AI will undoubtedly appear from time to time. It’s a blog about software delivery, quality engineering, organizational assessments and continuous improvement. It’s about understanding complex systems, identifying patterns and helping organisations become better at building software.

Ironically, that’s also what happened to me. An exercise that started with improving a CV became an assessment of something much larger: my own experience, strengths, motivations and direction. It also left me with a hypothesis that I suspect will appear repeatedly in future posts.

The most interesting outcomes don’t necessarily come from humans or AI working in isolation. They come from the interaction between the two. I started the conversation expecting editorial assistance. I ended it with a clearer understanding of my own career and a completely new set of ideas about where to take it next.

Why this blog

I’ve spent much of my career assessing and improving software delivery organizations. Along the way, I became increasingly interested in the assessment itself: What constitutes evidence? How should confidence be communicated? Are we assessing processes, or capabilities? And can assessment methodology be separated from domain knowledge?

This blog is a collection of field notes rather than finished theories. It’s where I explore ideas, question assumptions, and try to develop clearer concepts based on practical experience and ongoing reflection.

While many examples come from software quality and testing, my interest is broader: evidence-based assessment of organizational capabilities and the models we use to understand them.

Why “Field Notes”

These aren’t polished frameworks or universal truths. They’re observations from practice, hypotheses in development, and attempts to make sense of recurring patterns I’ve encountered over the years. Some ideas will mature. Others will be discarded. The purpose is not to be right, but to make my thinking visible and open to scrutiny.