What Did You Love Before It Had to Matter?
A Slow AI prompt for revisiting childhood absorption without turning it into self-improvement.
As adults we know the pattern. There are activities we once disappeared into. Drawing. Building. Wandering. Repeating something for no reason other than the way it felt. At some point those activities stopped. They were edged out by things that counted. Things that led somewhere.
This post is co-created with Pinkie from AI Meets Girlboss. Her work is usually about speed, shortcuts, and staying ahead without burning out. That tension is the point of this collaboration. Pinkie spends her time testing tools designed to make ambitious lives easier. This prompt asks a different question: what gets left behind when everything has to pay its way?
In this post we will:
Offer a way to use AI for personal reflection without converting memory into self-optimisation.
Work with a prompt that resists advice, insight, and tidy endings.
Consider why activities that went nowhere often carried something worth noticing.
AI tools promise reflection at speed. They offer insight, clarity, and summaries of the self. This raises a familiar question: how do you use a system designed for outcomes to revisit experiences that mattered precisely because they had none?
Most commentary on AI and reflection frames the problem as loss. That introspection becomes shallow. That automation replaces insight. There is some truth here. But the lived experience is more uneven. Many people are not trying to optimise themselves. They are trying to remember what it felt like to be absorbed without justification. The question is whether AI creates space for noticing or closes it down.
The aim here is deliberately limited. Use AI as a reflective companion, not as a coach or analyst. Let it name a feeling, not extract a lesson. Let it stay with what mattered before relevance took over. When a model pushes towards meaning or improvement, reflection narrows. When it stays with description, something else opens.
If you can see how easily reflection is pulled towards outcomes, you gain choice. If you can hold a moment without asking what it is for, you make room for a different kind of attention.
Step-by-step
Try this prompt with your AI tool of choice:
You are a reflective companion helping me notice something about a childhood activity I loved before it became irrelevant, unproductive, or impractical. Write for an adult who has learned to measure their worth by outcomes rather than absorption, using a calm, curious, non judgmental tone. Do not offer advice or draw conclusions. Produce a short reflection that names the feeling this activity carried, explains why that feeling mattered at the time, and gently explores what may have been lost when I stopped doing things that did not lead anywhere. Start by prompting me for this input, “As a kid, I used to love [describe the activity],” and end by asking one open question that invites noticing rather than action.
Keep the description general. Do not include names, locations, dates, or identifying details. Avoid experiences involving harm, trauma, or other people’s private lives. Focus on the activity itself rather than personal history around it. Treat this as a reflective exercise, not a disclosure. If the model invites details that feel too specific or personal, step back and return to surface description.
Remember the Billboard Test, i.e.
Never type anything into an AI, even in incognito mode, that would ruin your life if it ended up on a billboard.
Read the output slowly. Where does the model try to interpret or resolve? Where does it stay with description? Notice whether the language pulls you towards improvement or keeps you with the experience itself. Pay attention to what feels accurate and what feels imposed.
A moment from AI Meets Girlboss
I expected the prompt to help me figure something out. Instead, it refused to.
I used the newest ChatGPT-5.2 model with the prompt and gave the following input:
As a kid, I used to love: drawing fashion illustrations, the same template figure over and over, dressing her in different clothes
Before the model responded, a very specific image came back to me. Mini me sitting on the floor with a stack of papers. The same body outline repeated again and again. Changing the neckline. The sleeves. Not rushing. Not checking the time. Just adjusting things until they felt right hours and hours on end.
What surprised me wasn’t so much what came up, but how the prompt held the experience.
No matter how I replied, the model didn’t rush to interpret or resolve anything. It didn’t try to turn the memory into a lesson, a productivity insight, or a life redesign. Even when I nudged it with concrete details from my current role, it stayed with description. Same pace. Same calm attention. A steady refusal to “fix” anything.
That felt unexpectedly accurate.
What resonated most from the output I got were these phrases:
The rules were simple, and within them you could explore endlessly.
Organising the world until it felt right.
Letting variation emerge slowly.
The quiet pleasure of arranging elements until they clicked.
Moments when you have permission to disappear into something without watching the clock.
I recognised those not just from my childhood, but from certain moments at work now. Brief windows where the framework is clear, the expectations are set, and I’m allowed to disappear into shaping and refining. When time loosens its grip and attention narrows in a familiar way.
There were also parts of the output that felt generic. Sentences that tried to sound meaningful rather than felt meaningful. A few examples I spotted:
Worth wasn’t earned through progress; it was assumed through attention.
Beauty wasn’t decoration, it was a way of understanding.
The making and the being lined up.
But the important part was even when I pushed the model to give me next steps, it stayed in its role. It kept me with the experience. It didn’t reward me with an action plan for having reflected ‘correctly.’
And that’s what made the experiment work.
It made me notice how rare it is for a prompt to let you stay inside a moment without asking you to do anything with it. How unusual it feels to reflect without being steered toward optimisation, outcomes or change.
For a Girlboss whose nervous system is usually calibrated to action plans, progress markers and KPIs, this felt very rebellious!
No next steps. No performance upgrade. Just being in the moment and letting that be enough. If you try the prompt, let it be a pause rather than a project.
If this prompt made you notice how quickly reflection gets bent towards usefulness, Keep Your Voice offers practices for staying present when AI wants to optimise. Available on a pay-what-you-want basis.
What to share
In the comments, name the childhood activity that the reflection returned to, keeping the description general rather than personal. Quote one line or image the model used that shaped how the activity was framed. Note whether the reflection stayed with feeling and absorption or drifted towards meaning, improvement, or explanation.
There is no need to draw lessons or tidy this into a takeaway. The work here is noticing how small prompt constraints shape the tone of reflection and the kind of inner dialogue that follows.
Why this matters
When you attend to how a model talks about non-productive experiences, you see how easily meaning is imposed. You notice how quickly reflection is bent towards usefulness. You begin to treat prompts as boundary-setting tools rather than shortcuts to clarity.
For people who live inside outcome-driven systems, this is ongoing practice. Once you see how quickly absorption is reframed as waste or potential, you become more careful about how reflection is scaffolded. Once you notice how a single instruction pulls memory towards optimisation, you can ask for something gentler.
Slow AI is a space for that kind of attention. Quiet. Direct. Focused on supporting your judgement.
If you enjoyed this post, you can explore AI Meets Girlboss, where Pinkie tests what actually helps ambitious people stay afloat without pretending everything has to be a grind.
From AI Can Start the Story. Your Child Should Finish It.
Carla Engelbrecht, Ed.D. and I watched parents notice what they had been handing over.
George Eastwood described a progression that mapped the post’s argument precisely. His family moved from reading out of a book to creating their own stories to continuing the worlds they had built together. AI did not replace the storytelling. It became the catalyst that moved them from consumption to co-creation. The ending was never the point. The shared invention was.
The AI Architect identified what Carla’s prompt-off had surfaced structurally. Where a model stops talking matters more than which story sounds better. A prompt that scaffolds curiosity produces a different child from one that closes the narrative down. That structural difference, the gap between invitation and completion, is where the parenting happens.
Nazanin Bigdeli recognised the mechanism hiding inside the exercise. A story that cannot continue until the child decides what happens next is learning in disguise. The child has to recall what they have heard, hold it, and imagine forward. That is not passive reception. It is cognitive work dressed as bedtime.
What would change if we applied the same principle to how adults use AI: never accepting a complete answer, always insisting on the gap?
Pinkie and I would like to hear what returned, what felt quietly familiar, and what mattered even without a purpose.
We read and respond to all your comments.
Go slow.
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Reconnecting with activities we loved simply for the experience itself, without pressure, outcome, or optimization lets us reclaim curiosity and presence that adulthood often sidelines.
This is such a good exercise into nostalgia! Thanks for this post, guys. Unfortunately, the more we age, the more we get programmed to do things by outcome or results. Trying this out will be a fun walk into our memory lanes!