The Builder-Parent Paradox

What it feels like to build AI systems while raising the humans who will inherit them.

TL;DR: I work inside AI every day and I have two kids. I call this the Builder-Parent Paradox: I am one of the people best positioned to protect them precisely because I help build it, and I still do not know enough to confidently say what the future will look like. Inside access gives me responsibility, not certainty. Here is how I study the machine while using it, what I am betting on, and what I refuse to write.

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I spend a lot of time inside AI systems.

Not casually.

For the last several years, I’ve worked at the edge of AI product development, ethical AI, and AI-assisted building.

I manage AI products alongside brilliant researchers, engineers, and compliance leads, so I see the full product chain up close: research decisions, engineering tradeoffs, ethical tradeoffs, and security risks. The product choices that tell you what a company thinks people are for.

I build indie products on the side.

I’ve read every frontier model release note since 2022. Four years of it. OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, xAI, Perplexity, Qwen, the long tail.

And I also have two children.

Some nights I kiss them good night and I don’t know whether the world I’m helping build will let them have a job, a craft, a sense of slow attention, or the kind of boredom that turned me into an ambitious adult.

I open the laptop and I keep building anyway. I haven’t figured out how to stop doing both of those things in the same evening.

The Builder-Parent Paradox

Inside access gives me responsibility, not certainty.

There isn’t a name for the thing I live inside, so I’m going to give it one.

The Builder-Parent Paradox: the realisation that I’m one of the people best positioned to protect my kids from AI precisely because I help build it, and I still don’t know enough to confidently say what the future will look like. The paradox is that inside access gives me responsibility, not certainty.

It’s not the Parents’ Paradox. Not Gopnik’s gardener.

It brings a specific kind of guilt: the guilt of participating in something I also have to help my children question, resist, and live with.

I don’t know how to put the guilt down and I don’t want to. It turns out to be a useful instrument. It keeps me from numbing myself into a cleaner, easier, less honest version.

The people who left the industry to protest from outside don’t get to shape what their kids inherit. The people inside, building carefully, do.

That’s the Builder-Parent Paradox, and it applies to anyone shipping AI with skin in the next generation’s game. Founders, PMs, engineers, teachers using the tools in classrooms. Regulators with kids in those classrooms.

If you have professional authority over a thing whose long-term effects on the people you love are unclear, you live in this paradox.

AI Is the Biggest, Most Ambiguous, and Unevenly Distributed Technology Shift of Our Time

Many writers focus on the size of the shift.

Of course it is big. You don’t need a newsletter to tell you that.

The two parts I keep thinking about are the ambiguity and uneven distribution.

Ambiguity

I don’t see AI as something that neatly fits into one moral category.

• It’s not simply good.

• It’s not simply bad.

We can use it to learn faster, build faster, design faster, research faster, and test ideas that would have stayed stuck in a notebook for years.

But I can also see how the same systems concentrate power, weaken craft and judgment, slop the internet, and remove the kind of entry-level work that used to teach people what thinking even is.

S&P Global’s 2026 labour analysis now describes AI’s employment impact as modestly negative, after a more neutral-to-positive picture in 2025.

Challenger’s May 2026 report found that AI was cited in 40% of US job cuts announced that month, up from 7% in January.

Uneven Distribution

The rural pharmacist who can use AI to double-check a prescription against medical references in seconds is gaining something real.

So is the founder outside the usual tech hubs who can build and ship software without needing an expensive team.

So is the child learning calculus, English, or computer science from a model running on her family’s only smartphone.

But the American copywriter losing their job to a model that produces 70% of the same output for 1% of the cost is unambiguously losing.

So is the junior designer whose entry-level path just got automated.

Both are happening at the same time. The technology is the same technology. What changes is who pays the cost, and who gets to turn it into power.

Things I Will Not Write in This Essay, and Why

This is the list of sentences the AI commentariat keeps writing that I’m explicitly refusing. If you have written any of these, no judgment. I have probably written most of them too. I’m trying to stop.

• I will not write "AI is just a tool." AI is part of a larger system of model choices, product decisions, business incentives, policy constraints, ethical tradeoffs, and human consequences.

• I will not write “the technology is neutral.” Because the technology was built by a small number of people with very specific incentives.

• I will not write “we are still early.” “Early” is the word this industry uses when it wants applause for the future and immunity for the thing it already sells.

• I will not write “the future is uncertain but exciting.” Because it’s only exciting for people who don’t have to live with the downside.

• I will not write “humans will adapt.” Because some humans, yes. Mine, I don’t know yet. People gaining access to capability they never had before, probably. The copywriter whose work just became cheaper to replace, possibly not.

• I will not write “AI will free us to focus on what matters.” Because the people saying this are usually not the ones losing their jobs.

These are the claims I can confidently refuse as someone inside the Builder-Parent Paradox.

Studying the Machine While Using the Machine

Studying, in my case, is not a metaphor. It’s a workflow.

Every frontier release note gets logged with the date and my private commentary about what the company is signalling about:

• who they think their user is now

• whose work just got cheaper to automate

• what new aspects of critical AI literacy I should explore next

• what that changes in the “who do you want to become when you grow up” discussion with my kids

• how I plan the next moves of my own career

The first three become topics for my Substack. The last two are why I have a Substack.

That is what studying looks like for me.

What I’m Betting On

These are things I would put real money on.

• I’m betting that critical AI literacy will be a bigger career moat in 2028 than any specific AI tool.

• I’m betting that the builders (big or small) who document publicly will outlast the VC-funded sprinters.

• I’m betting that my kids will need taste and judgment more than they will need to learn to code.

• I’m betting that the writers who refuse the smooth version will become disproportionately citable.

• I’m betting that the next five years of AI value creation will skew heavily to the Global South. More than six billion people are already online, and more than 1 billion people now use AI monthly. The European-American discourse keeps missing this. The product opportunities will not.

If I’m wrong on any of these, I will write the essay called Where I was wrong about AI in 2026. I will publish it, I promise.

The part I can’t bet on is whether I’m raising my kids the right way for the world these bets describe.

What I’m Doing About It

Here is the unglamorous list of what I’m doing:

• I write with a builder’s hands and a product strategist’s brain: practical workflows, sharper product judgment, and deeper insight into how AI systems are built and positioned.

• I write the harder version. I analyse AI product launches without the hype, through the lens of someone who builds AI for a living.

• I test and systemise pretty much everything, then document what broke, not just what worked.

• I share what I build: code, prompts, workflows, tools, mistakes, and decision points. Other builders can copy it, fork it, or argue with it.

• I let my kids see me struggle with it. The version where I’m pacing the kitchen trying to decide whether a release is worth covering or if it’d only add to hype. They need to see what it looks like when an adult sits with a hard question.

• I keep one foot outside, binge-watch TV shows, garden, cook badly and take my kids to the woods. Keeping a self that AI can’t touch.

Am I on the Right Side of This?

I don’t know if I’m on the right side of this.

I think most people working in tech don't know either, and the ones who say they do are often the ones I would not let near a real decision.

What I know is this: I’m going to keep learning, keep writing about it, and keep my attitude. I’m going to try to leave my kids a world where curiosity, judgment, and the ability to think for themselves still count for something.

If you remember nothing else from this essay, remember this: inside access gives me responsibility, not certainty. That is the Builder-Parent Paradox. If you have professional authority over a thing whose long-term effects on the people you love are unclear, you live in it too. Act accordingly.

FAQ

What does it mean to think about AI as a builder and a parent at the same time?

It means you cannot read a release note as just a release note. Every product decision becomes a question about the world your kids will grow up inside. It adds weight, and it also kills naivety fast.

Is AI good or bad?

Neither, and both. AI is the biggest and most ambiguous technology shift of our time. It can expand human ability and it can quietly remove the conditions that built that ability. The honest answer is to hold both truths at once and act carefully.

What should non-technical people do about AI in 2026?

Build something. Even one small thing. The fastest way to stop being passive about AI is to make something with it, break it, fix it, and notice what it does and does not understand. Literacy follows building, not the other way around.

Why is “ambiguity” the right word for AI right now?

Because the benefits and harms are tangled at the root. You cannot pull one out without the other coming with it. Calling it “ambiguous” is not fence-sitting. It is the most accurate description of the technology in mid-2026.

How do you stay sane working inside AI?

I keep one foot outside. I write the harder version. I let my kids see me struggle with it. And I treat the guilt as an instrument, not a problem to solve.

I’m Karo Zieminski. AI Product Manager and builder. I write Product with Attitude, an AI newsletter for thousands of subscribers developing critical AI literacy the only way it sticks: through practice.

We don’t just use AI. We build workflows, automations, and products with it, while studying how AI itself is built, positioned, and woven into our work. Subscribe here.

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