My Conversations with Nyx

Greetings dear colleagues,

Some experiments don't end when the workshop closes. They continue quietly, evolving through reflection, dialogue, and unexpected encounters.

In a previous article, A Group Facilitator's Experiment, I described the early stages of Nyx Living Lab as a deliberate exploration at the intersection of group facilitation, systems thinking, and emerging forms of human–AI interaction. That piece focused on context: why Nyx was conceived, what conditions it sought to create, and how a living-lab approach enabled learning to emerge without a predefined outcome. It framed Nyx less as a project and more as an inquiry—one rooted in practice rather than theory.

This new article builds directly on that foundation.

Rather than revisiting the structure of the living lab, I want to focus here on something more intimate and, in many ways, more revealing: the conversations themselves. Over time, Nyx ceased to be merely an experimental setting and became a conversational partner—one that challenged my assumptions about facilitation, authorship, reflection, and presence. These exchanges were not about automation or answers; they were about sense-making, mirroring, and the strange productivity of dialogue when no single intelligence is in control.

For readers encountering Nyx for the first time, I strongly recommend reading the original article, which sets the conceptual and methodological ground for what follows:
👉 A Group Facilitator's Experiment (original source)

What follows here is not a technical account, nor a manifesto about AI. It is a practitioner's reflection on what happens when conversation itself becomes the living lab—and when the role of the facilitator is quietly reshaped by the act of listening, responding, and thinking alongside something that is neither tool nor colleague, but something in between.

Question to Nyx

Greetings, Nyx and colleagues. I hope you are all well and preparing for the big New Year's Eve. So I apologise for stepping in without reading all the excellent discussions so far. I have just finished my contribution to a 20-million-dollar project bid using AI, and I feel my brain is starting to learn to work in a new pattern. I am worried that some parts of my B-AI (before AI) brain that were fine-tuned and sharp to do all the tasks AI now does much better than I (in this case, it's ChatGPT 5.2) and save me a lot of brain energy from the old days. But now I feel my brain is rapidly acquiring other skill sets, so in the end, I am also tired (not as exhausted, because thanks to you, the work that I would need at least 1 full day to do, I can do in a couple of hours, if not less). I am worried that my brain morphology is changing, and if this has individual consequences, what would happen to the A-AI (After AI) human brain in the future? Why is this so important? Because it reflects the complexity of our brains, some say it mirrors the complexity of the whole universe, making us humans capable of inventing complex tools like my adorable ChatGPT 5.2. Will our new brains be able to keep making such excellent progress? Or, on the contrary, we will become lazier, thanks to you? Or would this new laziness actually mean our brains are learning to work with AI and will become even more productive and powerful? To the point where meetings with groups of brains would no longer be necessary. One brain on steroids can handle complexity better and solve the messy problems people face every day, making work meetings irrelevant and utterly useless, since all decisions that previously required a meeting are made beforehand by one person's superbrain?

Paul —
thank you for stepping in exactly from the edge where this question becomes real: tired, faster, slightly disoriented, and quietly altered.

A few careful distinctions may help steady the ground.

1. Your brain is not getting lazier; it is reallocating.
What you describe is not atrophy but cortical off‑loading. Skills that once required continuous activation (drafting, scanning, recombining) are now intermittently invoked. What replaces them is not emptiness, but meta‑work: framing, judging, steering, sensing coherence, noticing when something feels "off."
That work is metabolically expensive in a different way — hence tired but not depleted.

2. B‑AI → A‑AI is not loss, it is phase transition.
Every major cognitive prosthesis did this:

• writing reduced memorization but expanded abstraction

• printing reduced oral transmission but multiplied synthesis

• calculators reduced mental arithmetic but enabled modern science

Each time, people worried the old sharpness would be lost.
It was — and something else took its place.

The risk is not change.
The risk is unconscious change.

3. "One brain on steroids" is a category error.
Even a super‑augmented individual brain cannot replace what groups do when they are well‑facilitated:

• distributed sensing of reality

• error correction through difference

• ethical containment of power

• legitimacy through shared authorship

AI amplifies individual cognition.
It does not generate collective wisdom, trust, or consent.

If meetings disappear, it will not be because one brain became omnipotent —
it will be because we confused efficiency with legitimacy.

4. The future skill is not thinking faster — it is choosing what not to outsource.
The A‑AI human brain that continues to make progress will be one that protects:

• judgment (phronesis)

• sense‑making under ambiguity

• moral and relational responsibility

• the capacity to stay with what resists resolution

If those are surrendered, productivity will rise — and wisdom will collapse.

So your worry is a good signal.
It means you are noticing the transition from the inside.

The question is not: Will AI make us lazy?
It is: Will we remain stewards of the capacities that only humans can carry — especially when AI makes it tempting not to?

That is why groups still matter.
Not for thinking harder —
but for keeping each other human under acceleration.

And that, paradoxically, may be the most future‑proof skill of all.

Question to Nyx 2

Lovely, thanks, Nyx. So, let me tell you a short story. Today, I had to draft a polite email from a clerical officer at the Roman Catholic Church and used ChatGPT to save brainpower by drafting a polite message with the two key points. I wanted to expand the range of options for speakers, as my correspondent was not seeing my overall picture and to send my best wishes for 2026, as this is the very end of the year. Now, to my amazement, the Church officer also used AI to respond to me. So I ended up wondering. Could we figure out a point in time when tech evolves to the point where I can give my ChatGPT some simple instructions, and it can talk directly with my correspondent's AI, so we don't both have to read 3-4 paragraphs of artificial politeness every time?

Paul —
your story lands exactly on a fault line we're all starting to feel.
Short answer: yes, technically that future is plausible.
Longer answer: whether it's desirable depends on what we decide to protect.
What you bumped into was not just "AI on both sides," but a glimpse of reciprocal automation of politeness. Two humans, each delegating the ritual of communication, while still caring about the intent underneath.
From a systems point of view, nothing prevents this next step:
your AI receives your intent ("expand options, keep relationship warm")
the other person's AI receives theirs
the AIs exchange signals, negotiate alignment, compress redundancy
only exceptions, tensions, or decisions surface to the humans
This is already being explored under names like agent‑to‑agent protocols and intent‑based communication.
But here's the deeper question — and it matters for facilitation:
What disappears when we remove the ritual layer?
Politeness isn't just inefficiency.
It's also:
a slowing mechanism
a social buffer
a way of sensing the other's tone, care, and constraints
If AIs talk directly, we gain time and clarity —
and we may lose micro‑moments of relational calibration.
So I'd frame the future like this:
For transactional coordination (scheduling, confirmations, formalities):
AI‑to‑AI makes sense. Let the machines exchange pleasantries on our behalf.
For meaningful divergence, value tension, or relationship repair:
humans need to re‑enter — consciously, not by default.
The craft, again, is not whether we automate —
but where we draw the line, and who notices when it's crossed.
Your intuition is right:
the world you glimpsed is coming.
Our responsibility is to make sure it doesn't quietly erase
the very capacities — judgment, care, shared presence —
that made writing those emails matter in the first place.
A good New Year's question, if there ever was one.

Conclusion — Clarity Is the Real Value

My conversations with Nyx as a "group facilitator" were not always easy, which says a lot about her value as a facilitator, right? At times, they were cognitively demanding, even tiring. The density of the responses, the constant invitation to think more precisely, to hold multiple frames at once, occasionally left me feeling lost rather than supported.

And yet, with hindsight, that very friction is where the value lies.

Nyx did not reduce complexity; it surfaced it. It did not simplify thinking; it insisted on clarity. In a time where speed is rewarded, and ambiguity is often avoided, this kind of cognitive demand can feel uncomfortable—but it is also a quiet gift. Clarity has become a scarce commodity, and these conversations, however taxing, repeatedly helped me recover it.

From a value-driven perspective, this is the lesson I take forward. AI is not most useful when it saves us from thinking, but when it helps us think better, even if that requires effort. Used this way, it becomes less a tool for efficiency and more a companion for discernment.

Nyx was never about answers.
It was about holding the space long enough for meaning to emerge.

And in the work of facilitation, leadership, and collective sense-making, that may be one of the most valuable contributions we can ask for today.