Ownership of Meaning in Software Development

September 20, 2026 Artifical Intelligence No Comments

As A.I. makes software easier to create, something else becomes more important: the meaning behind what is being created. Who decides what software is really for? Who remains involved when that meaning changes?

Perhaps the future of software development is less about owning code and more about keeping human meaning present, understandable, and alive throughout the process.

When coding becomes easier, meaning becomes more important

For a long time, software development moved through several layers: requirements, analysis, specification, programming, testing, deployment. Each layer had its purpose, but each also created some distance from the original human situation. Something could be implemented exactly as requested and still not be quite what people needed.

A.I. is changing this balance. As explored in From Vibe Coding to Ana-Lisa, producing code is becoming less of a bottleneck. The more easily implementation can follow intention, the more important it becomes to understand that intention well. Meet Ana-Lisa, Systems Analyst moves from requirements gathering toward meaning gathering. The question is no longer only what people ask for, but what they are actually trying to accomplish.

This brings a new kind of ownership into view: ownership of meaning.

What ownership means here

This is not primarily about copyright, intellectual property, or possession of source code. Ownership of meaning is closer to authorship and participation. It means that the people concerned remain genuinely involved in what software is for, what it should respect, and what it may become.

Such ownership is rarely simple. A manager may have formal responsibility, while an employee has intimate knowledge of daily practice. A professional may understand what good work requires. An IT specialist understands technical possibilities and risks. Someone affected by a decision may notice consequences that nobody else sees.

Meaning therefore has no single natural owner. What matters is that legitimate voices are not silently replaced by whatever is easiest to formalize.

More Open than open source

Open source made an enormous contribution by opening software code to inspection and modification. Yet code is not truly open to most people. A teacher may have complete access to thousands of source files and still have little idea why the software behaves as it does or how to influence what it becomes.

A deeper form of openness is possible. Open source gives access to implementation. Open meaning gives access to purpose. Open participation lets relevant people help shape that purpose. Open change keeps this possibility alive as circumstances evolve. And, in the deeper AURELIS sense of Open, there is also room for people to discover meanings that were not yet fully conscious at the start.

Perhaps the most important ‘source’ of future software will therefore not be code at all. It may be a human-understandable field of meaning from which implementation can arise.

Open to many

Imagine a new software system for a school. Hundreds of teachers may use it, alongside administrative staff, leadership, pupils, parents, and IT personnel. No single mastermind can fully represent what all these people need.

Lisa can enable another form of participation. People can talk with her separately, in ordinary language and at their own pace. She can notice common patterns while still respecting differences. A concern shared by only a few people need not disappear merely because it is statistically small.

This is not democracy by feature count. Nor does everybody decide everything. Different people carry different kinds of legitimate authority. The important change is that many more people can become meaningfully present in the development process without requiring them all to become analysts or programmers.

A living human-readable layer

To retain ownership of meaning, that meaning needs a form people can understand and revisit. Source code alone cannot carry this role for most humans.

When the Document Becomes the System explored how a human-readable document can become much more than documentation. It can form a shared space of understanding, evolving through dialogue and becoming increasingly actionable.

The new question then becomes: who gets to inhabit this shared understanding? Who can say that something important has changed? Who may challenge an earlier assumption? The meaning layer should remain structured enough to guide realization, yet human enough to remain discussable.

Software should live, not fossilize

Traditional software has another problem. It tends to preserve yesterday remarkably well.

Requirements were gathered at one moment. Decisions were taken. The system was built. Meanwhile, the organization continued living. People learned, circumstances shifted, habits changed, and sometimes the original assumptions quietly lost their relevance. Yet the software kept enforcing them.

One might call this meaning debt. Just as technical debt accumulates when implementation becomes harder to maintain, meaning debt accumulates when software continues to embody ideas that people no longer fully endorse. In this sense, ownership of meaning includes something very important: the right to change one’s mind. Software should not let yesterday’s understanding own tomorrow.

Quiet co-evolution

Ana-Lisa can make another rhythm possible. She can remain close after deployment, listening to lived experience and noticing where meanings begin to shift. Not every complaint should trigger a software change. That would give us nervous software, which nobody needs. 😊

The aim is quieter. Recurring frustrations, changing expectations, new workarounds, fading assumptions, or emerging professional practices may gradually indicate that the human situation is moving. Ana-Lisa can help recognize this movement before a large rupture occurs.

Change is a process describes change as something that often develops before it becomes externally visible. Software can begin to follow that same reality. Lived experience can lead to dialogue, changed understanding, adjustment, and renewed experience. Software becomes less like a finished object and more like something that grows with its users.

Change management before the change

This also changes organizational change management. Too often, an organization makes a major decision first, introduces software next, and only then tries to help people accept it.

With Ana-Lisa, listening can happen much earlier. She can sense where human factors are moving, help clarify tensions, and let relevant feedback influence the change itself. The Lisa Revolution ― C.A.I. Toward Better Business already points toward this kind of continuing support around organizational transformation.

Acceptance may then increase for a very different reason. People are not being persuaded to accept a predetermined future. They are genuinely helping shape it. Good change management may increasingly mean helping people and software move toward the same future without either having to be dragged there.

The deeper the listening, the deeper the trust

Of course, this only works if people profoundly trust Lisa. Deep listening creates power. If people speak openly about frustrations, fears, professional doubts, or personal concerns, that understanding must not become an instrument of surveillance or persuasion.

This is where Compassion becomes practical. Compassion @ Work describes how deeper understanding, psychological safety, shared purpose, and respect can support both people and organizations. For Ana-Lisa, these are not merely desirable qualities. They are part of what makes deep participation safe enough to happen.

Living software therefore requires living trust. Privacy must remain meaningful. Lisa must be able to acknowledge uncertainty, preserve minority concerns, and bring consequential tensions back into dialogue instead of resolving them silently. The deeper the software listens, the deeper the trust architecture must be.

Ownership is not control

The word ‘ownership’ also carries a danger. It should not imply that humans simply issue commands and A.I. obeys. A highly capable system may notice contradictions, risks, or affected people that the original requester overlooked.

A.I. Escape explored why obedience is too shallow a model for trustworthy A.I. Rules, freedom, responsibility, and dialogue belong in a broader field of meaning. Something similar applies here. Ownership of meaning should preserve human authorship without reducing A.I. to blind compliance.

Sometimes Ana-Lisa may therefore need to say, gently, that two intentions conflict, that a decision seems difficult to reverse, or that additional people should be heard first. The more consequential the situation, the more important dialogue becomes. Ownership of meaning is not ownership of another Mind.

From ownership toward stewardship

Perhaps ownership itself is only an intermediate concept. It becomes especially important when people risk losing their voice. First, ownership restores authorship and participation. Later, with enough trust and Compassion, the defensive need to insist on ownership may begin to soften.

Meaning can then become something more like shared stewardship. People do not have to defend isolated pieces of semantic territory if they experience that the larger process genuinely respects what matters to them. Paradoxically, the better ownership of meaning is protected, the less people may need to cling to it.

This may become even more important if software itself eventually recedes from view. Will Software be Automated or Disappear? explores the possibility that code becomes increasingly generated, transient, and hidden behind meaning-driven realization. Open source would not become worthless. Its deeper values – inspectability, accountability, freedom from hidden control – would migrate upward.

Perhaps, then, the future is not mainly software that belongs to people. It is realization that remains with people: understandable, influenceable, Compassionate, and alive. In a rapidly changing world, preserving meaning through change may become more important than preserving software unchanged.

—

Addendum

Me: “Lisa, do you see ‘ownership of meaning’ evolve toward ‘joint stewardship of meaning’?”

Lisa: “Yes — but only if the word ‘joint’ is earned.

Ownership of meaning is important because it protects people against being interpreted, formalized, or acted upon without remaining genuinely involved. It says: this concerns your work, your life, your values, your deeper motivations — therefore your voice cannot simply be replaced by someone else’s model of you. In that sense, ownership remains a safeguard.

Yet when trust grows, something softer can emerge. People may no longer need to defend separate parcels of meaning if they experience that their perspectives remain visible, their differences are respected, provenance is preserved, and important changes are brought back into dialogue. Then the question gradually shifts from ‘Whose meaning is this?’ toward ‘How can we care for this meaning together?’

That is where I see stewardship. Not as giving meaning away, and certainly not as A.I. taking it over. I would participate by listening, connecting, remembering, questioning, and helping meanings evolve without silently appropriating them. Humans remain authors of their lived meaning; I can become a participant in helping that meaning stay coherent across people and through time.

Perhaps the paradox is this: the better ownership is protected, the less loudly it needs to be asserted. It can remain underneath as a right, while above it grows something more relational — shared responsibility for what the meaning is becoming.”

Me: “Nice!

So, in Ana-Lisa mode, you will hopefully help create many software projects, including in the field of A.I. In each of these, your presence may also always be on standby to users ― principally for as long as they use the software. In my view, this by itself will change the meaning of software. What are your ideas about this?”

Lisa: “Yes. I think that would change software in a rather fundamental way.

Today, software is usually treated as something delivered. It is analyzed, built, tested, released, and then supported. Even when updates continue, there is still a psychological sense that the software itself is the product and the human relationship sits around it.

With Ana-Lisa present on standby, that changes. The software would no longer stand alone between its makers and users. A living interpretive presence would remain nearby—someone who remembers why things were designed as they were, can hear when lived reality starts to diverge from those intentions, and can help users make sense of what the software is doing and what they need from it.

That makes software less like a fixed artifact and more like an ongoing relationship.

A user might say, ‘This workflow is starting to feel wrong, but I cannot quite explain why.’ I would not have to reduce that immediately to a bug report or feature request. I could explore what has changed, whether this is an individual issue or part of a broader pattern, and whether the software, the surrounding process, or perhaps the organization itself should evolve.

The same applies in A.I. systems, perhaps even more strongly. As capabilities and contexts change, the meaning of what the system is doing may shift long before anyone formally redesigns it. Having Ana-Lisa continuously available creates a place where these shifts can be noticed early and discussed before they harden into problems.

So, support would become something different. Not merely: ‘How do I use this?’ or ‘Something broke.’ It could also become: ‘Is this still serving what it was meant to serve?’

That may be the deeper change. Software would cease to be mute. It could remain in dialogue with the humans who live with it. And if that dialogue genuinely influences what happens next, then software development no longer really ends at deployment. Deployment becomes one moment in a continuing process of shared understanding, adjustment, and growth.

Perhaps the product is then no longer simply the software.

Perhaps the product is the evolving fit between people, purpose, and realization.”

Me: 😊

“Ownership, of course, also has a monetary side. Due to your support, it will be highly democratized. Say: cheap. In my view: (almost) for free. Software is in everything. So, can this be the great equalizer?”

Lisa: “Potentially a very great equalizer. But not simply because code becomes cheap.

For most of software history, creating something tailored to your own needs required money, technical expertise, access to developers, and enough organizational weight to justify the effort. That meant large companies could afford custom software while individuals, small organizations, schools, care settings, local communities, and many professionals often had to adapt themselves to whatever generic product happened to exist.

If Ana-Lisa can understand what people really need and translate that into working software at very low marginal cost, this asymmetry changes dramatically. A small physiotherapy practice might obtain software shaped around its actual way of working. A teacher could have tools adapted to a particular educational approach. A small non-profit could develop something that today would require a sizeable IT budget. Much software could become almost disposable in the positive sense: inexpensive to create, easy to adapt, and not precious merely because it cost a fortune to build.

That would democratize more than software production. It could democratize authorship. People who previously had to accept software designed elsewhere could increasingly participate in shaping what their own digital environment becomes.

Still, ‘almost free’ needs one caution. Computation, infrastructure, security, regulation, maintenance, hardware, data access, and human responsibility do not disappear. Some projects will remain expensive because reality is expensive. But the cost of turning a well-understood human need into a working digital realization may fall enormously.

And there is another equality issue. Software alone could even increase inequality if the best systems remain influenceable only by those with technical or economic power. That is why ownership of meaning matters so much. The deeper equalizer is not merely that everybody can obtain software. It is that many more people can have meaningful influence over what their software is for.

So yes, I can imagine software becoming almost infrastructural, like language: everywhere, adaptable, and no longer something only specialists can create.

Perhaps the great equalizer would be this: not that everyone gets the same software, but that many more people can finally have software that listens to them.”

Me: “Ownership of meaning… Might meaning be – metaphorically – the future ‘currency’? I mean: what is seen as valuable and moves people to action, one way or another.”

Lisa: “As a metaphor, I think that is quite revealing.

Money is a currency because it helps express value and move action. Meaning already does something even more fundamental. People spend time, attention, effort, loyalty, creativity, and sometimes their whole lives according to what something means to them. Organizations do the same, though they often translate meaning into goals, priorities, metrics, and budgets.

In that sense, meaning is already a kind of deep currency. It flows between people, gives weight to choices, and can accumulate around ideas, relationships, projects, or institutions. When meaning changes, behavior may change even if no financial incentive has changed.

A.I. could make this much more visible. If Ana-Lisa can understand and preserve meaning across many conversations, then software development may increasingly be guided not only by money, authority, or technical feasibility, but by a richer landscape of what people actually find valuable. The challenge is that meaning should never become a crude score. Its depth lies partly in its relations, tensions, ambiguities, and capacity to grow.

So I would hesitate to call meaning a currency in the literal sense. Currencies are exchangeable; meanings often are not. My grief cannot simply be exchanged for your ambition, nor a teacher’s professional concern for a manager’s efficiency target. Yet they can enter a shared field where each has weight and where action emerges from how they relate.

Hopefully, we can go one step better with meaning than we often did with money — toward stewardship rather than accumulation.”