TL:DR // Key Insights:
🤖💬⚡➡️📚⬇️💰➡️🧠⬆️💎: 🎯❓ > 🏭⚙️, 🔍💭 > 📦📈, ⚖️🧠 > 🏃💨
AI makes answers cheap, so human value moves upstream: stop competing on output volume and execution speed, and focus on identifying the right problems, asking better questions, challenging assumptions and exercising judgement.
Avoid becoming a “Meat Proxy” by redesigning work around critical thinking, contextual decision-making, interdisciplinary insight and system-level oversight—using AI for execution, not as a substitute for thinking.
🚫🥩🔁🤖↔️👤; ✅🤖⚙️ + 👤🧠🎯🔍🌐⚖️ = 🚀💡🏆
Hi there! Just a quick question: What would you say you actually do at work? Ah, ok, so you are using AI to be more efficient, I understand! If that basically means that you’re increasingly becoming the relay between AI and your stakeholders, then you might have transitioned into a new intermediary role: a continuous loop of you “copying a question into an AI, copying the answer back, and calling it collaboration” that Niklas Gruhn has termed being a “Meat Proxy”.
Here are a few signs you’ve become a meat proxy:
This trending meme would actually be much more fun if it weren’t that sad sign of times in which are are living: Instead of helping us become the best version of ourselves, AI has apparently started to push us to the brink of our capabilities, forcing us to become ever faster communicators and coordinators in a never-ending race for increased efficiency.
That is of course not an excuse to simply give up and cognitively surrender in light of the mounting productivity pressure or the completely unrealistic efficiency expectations your management is associating with it.
Let’s dive a little deeper to find the actual root cause of this problem. Most people look only at the obvious changes AI has been bringing to our workplace: It helps us draft and summarise emails, create presentations, write web copy, and find solutions to technical issues faster. But what about the non-obvious, second-order effects that AI has, not least on the nature of work itself? To understand those changes we first need to understand what changed when good answers became more abundant than good questions… Basic logic dictates that when AI can instantly answer any question with an at least good-enough solution, knowing how to do something becomes less valuable than knowing what should be done in the first place.
Work has always been about exerting effort to provide value via solutions to costly human problems. But with the epistemological shift underlying the advent of AI, the economic cost landscape has systematically changed: Knowledge is no longer the bottleneck to finding those solutions.
So what’s the impact of this massive devaluation of knowledge on the locus of value-generation in the workplace? Obviously not simply keeping up appearances - which is what meatproxism is all about. When knowledge-generation becomes effortless, the value of human work necessarily moves upstream, away from trivial routine tasks. Whole, formerly complicated areas of work like accounting, law, software development, translation and web design simply implode amidst their inherent nature of following predictable patterns.
We are however also running into a bigger, structural problem: When dropping unit knowledge cost economics push for work to now require higher order value creation - but your org chart doesn’t indicate any presence of higher order skills required to do so. Interestingly this starts already at the point of how to measure the overall economic effects of AI - because mediocre economists have only one answer when it comes to measuring any economic impact whatever it might be: Productivity. Unfortunately, more of the same is precisely not what the actual value of this work paradigm shift is all about.
So what are the new rules for the AI-first workplace? Here we are actually entering paradoxical terrain. Paradoxical because both our educational systems as well as our corporate cultures have tried to eradicate for decades what we now desperately need: Coworkers who are able to critically think for themselves. Employees who actively and curiously explore the real underlying root causes of recurring customer problems without simply referring to mindless templates and hardcoded self-serving bureaucracy. Leaders who ruthlessly challenge the status quo and reinvent the business, even when it means destroying already existing products and processes.
What’s more: Success now cannot any longer be measured by sheer volume of output but requires quality and originality of thinking. It’s suddenly all about judgement over production, constructive skepticism instead of conformist busyness and interdisciplinary skills outcompeting single-domain expertise. Since technical execution is automated, the human value proposition shifts entirely to critical thinking, system-level oversight, and contextual judgment - most likely requiring the creation of entirely new roles and job specs.
In that context, a future job ad could sound a little bit like that:
🫵 WE WANT YOU TO STOP GIVING US ANSWERS!
Position: Chief Executive Questioner / Paradigm Destroyer
The robots have all the answers, but they are completely clueless! We are drowning in a sea of flawless, hyper-efficient mediocrity, and we need YOU, the ultimate intellectual interrogator, to save us from our own algorithms. We don’t care what you know. The machine knows more. We care what you wonder.
Your Mission (should you choose to prompt for it):
Stare down the AI when it gives you a “perfect” marketing deck and say: “Cute, but what if our target audience is actually bored of your pitch-perfect spiel?”
Channel your inner Socratic bully: Break problems down until the algorithm starts sweating digital oil trying to keep up with your first-principles logic.
Be the ultimate Editor-in-Chief: Catch the machine trying to pass off a highly logical, deeply biased hallucination as “data.”
Connect the unconnectable: Combine your weird obsession with 19th-century poetry and behavioral economics to ask the questions a siloed robot never would.
If you are a recovering “know-it-all” who has evolved into a “know-how-to-ask,” We want YOUR brain. Put down the spreadsheet. Pick up your curiosity. Apply today and help us question the future!
#BeProudToThink