The Human Brain in the Age of AI
The Human Brain in the Age of AI
Written by Stuart McClure • Oct 3, 2025
A Straight Talk on AI
Friends, my apologies up front but you do know me and my “Exposed” style. So let's have a candid conversation about AI. The hype is off the charts. If you believe the vendors, it’s a magic wand that will solve every problem. But as you’ve seen recently, the failures are growing at a geometric rate: Replacing Humans with AI is Going Horribly Wrong
As someone who has built and sold an AI company and is now building the next generation AI Future of Work, let me give you the ground truth: AI is a phenomenal tool, but it's not a thinker. It's a hyper-specialized calculator. The most powerful, creative, and adaptable processor you have is the one sitting in this room between your ears. It’s the human brain.
The real question isn't "how do we replace people with AI?" it's "how do we stop wasting the brilliance of our people on tasks a machine should be doing?" Here’s how I see the landscape and the plays you need to make:
#1: The Efficiency Mirage
We're being told to throw massive computational resources at problems, but the human brain runs on a 20-watt lightbulb while training a single AI model can power a small town. Think of the Apollo engineers calculating orbital mechanics with slide rules versus the millions in cloud credits it takes to train a model today. Before you greenlight any AI project, mandate a simple assessment: is this a problem of brute-force scale, or is it a problem of nuanced thought? Use AI for the former and your people for the latter, and ideally a confluence of the two to unlock the REAL potential of Human + AI.
#2: Missing Human Understanding
AI is brilliant at pattern recognition but has zero common sense. An autonomous vehicle can drive millions of miles but still get confused by a construction worker waving traffic in a non-standard way, something a human driver understands instantly. This is the same gap I saw in cybersecurity, where a human analyst had to first understand a hacker's novel intent before an algorithm could be taught to find the pattern. Your strategy should be a symbiosis: use AI for the first 80% of data analysis, then deploy your top human talent to do the final 20% of interpretation and decision-making where the real value is created. Think of the Human as the Orchestrator, and the AI as the Helper and potentially the Actor.
#3: True Innovation Comes From People
You’ve probably heard this a few times but AI does not innovate (yet - but I have reservations with Transformer Neural Networks ever doing this but…). Instead it mimics. The Post-it Note wasn't invented by an algorithm; it was born from a failed experiment for a super-strong glue and a frustrated choir singer who needed a better bookmark. That collision of unrelated ideas is a uniquely human capability. Your next billion-dollar idea won't come from a prompt. It will come from a person who is free to think. Your job is to use AI to automate the drudgery that drains your best people so they can do the work of invention. Only humans can apply abductive reasoning to any problem, and that’s because we have learned from experience largely.
The Call to Action: Measure What Really Matters
Here’s the real tough question: If human ingenuity is your most critical asset, how are you measuring and managing it?
For decades, we’ve managed our people with gut feelings and pure guesswork. We build teams based on who's available or “good people”, not who's truly highly performant or optimal for a particular function or project. We're trying to win a Formula 1 race while treating our drivers and engineers like interchangeable parts. It's absolute madness. This is the next frontier. If you accept that your people are the engine of innovation, then you must accept the need to understand that engine with the same analytical rigor you apply to your financials.
The Future: Stop Guessing, Start Quantifying
This is precisely the problem we're solving with WethosAI. We've built a way to quantify the very human traits and cognitive biases that make your people tick and build the patterns and instincts of decision making and action. We can finally see who your natural innovators are versus your meticulous executors, why one team gels while another struggles, and if you're putting your best people in roles where they can actually thrive. The future isn't about replacing humans with AI. It's about using a new kind of AI to finally understand, align, and unleash the full potential of our people.
Stop guessing. Start quantifying the human element. That’s how you build a company that dominates the age of AI.
Written by Stuart McClure • Oct 3, 2025
A Straight Talk on AI
Friends, my apologies up front but you do know me and my “Exposed” style. So let's have a candid conversation about AI. The hype is off the charts. If you believe the vendors, it’s a magic wand that will solve every problem. But as you’ve seen recently, the failures are growing at a geometric rate: Replacing Humans with AI is Going Horribly Wrong
As someone who has built and sold an AI company and is now building the next generation AI Future of Work, let me give you the ground truth: AI is a phenomenal tool, but it's not a thinker. It's a hyper-specialized calculator. The most powerful, creative, and adaptable processor you have is the one sitting in this room between your ears. It’s the human brain.
The real question isn't "how do we replace people with AI?" it's "how do we stop wasting the brilliance of our people on tasks a machine should be doing?" Here’s how I see the landscape and the plays you need to make:
#1: The Efficiency Mirage
We're being told to throw massive computational resources at problems, but the human brain runs on a 20-watt lightbulb while training a single AI model can power a small town. Think of the Apollo engineers calculating orbital mechanics with slide rules versus the millions in cloud credits it takes to train a model today. Before you greenlight any AI project, mandate a simple assessment: is this a problem of brute-force scale, or is it a problem of nuanced thought? Use AI for the former and your people for the latter, and ideally a confluence of the two to unlock the REAL potential of Human + AI.
#2: Missing Human Understanding
AI is brilliant at pattern recognition but has zero common sense. An autonomous vehicle can drive millions of miles but still get confused by a construction worker waving traffic in a non-standard way, something a human driver understands instantly. This is the same gap I saw in cybersecurity, where a human analyst had to first understand a hacker's novel intent before an algorithm could be taught to find the pattern. Your strategy should be a symbiosis: use AI for the first 80% of data analysis, then deploy your top human talent to do the final 20% of interpretation and decision-making where the real value is created. Think of the Human as the Orchestrator, and the AI as the Helper and potentially the Actor.
#3: True Innovation Comes From People
You’ve probably heard this a few times but AI does not innovate (yet - but I have reservations with Transformer Neural Networks ever doing this but…). Instead it mimics. The Post-it Note wasn't invented by an algorithm; it was born from a failed experiment for a super-strong glue and a frustrated choir singer who needed a better bookmark. That collision of unrelated ideas is a uniquely human capability. Your next billion-dollar idea won't come from a prompt. It will come from a person who is free to think. Your job is to use AI to automate the drudgery that drains your best people so they can do the work of invention. Only humans can apply abductive reasoning to any problem, and that’s because we have learned from experience largely.
The Call to Action: Measure What Really Matters
Here’s the real tough question: If human ingenuity is your most critical asset, how are you measuring and managing it?
For decades, we’ve managed our people with gut feelings and pure guesswork. We build teams based on who's available or “good people”, not who's truly highly performant or optimal for a particular function or project. We're trying to win a Formula 1 race while treating our drivers and engineers like interchangeable parts. It's absolute madness. This is the next frontier. If you accept that your people are the engine of innovation, then you must accept the need to understand that engine with the same analytical rigor you apply to your financials.
The Future: Stop Guessing, Start Quantifying
This is precisely the problem we're solving with WethosAI. We've built a way to quantify the very human traits and cognitive biases that make your people tick and build the patterns and instincts of decision making and action. We can finally see who your natural innovators are versus your meticulous executors, why one team gels while another struggles, and if you're putting your best people in roles where they can actually thrive. The future isn't about replacing humans with AI. It's about using a new kind of AI to finally understand, align, and unleash the full potential of our people.
Stop guessing. Start quantifying the human element. That’s how you build a company that dominates the age of AI.
Written by Stuart McClure • Oct 3, 2025
A Straight Talk on AI
Friends, my apologies up front but you do know me and my “Exposed” style. So let's have a candid conversation about AI. The hype is off the charts. If you believe the vendors, it’s a magic wand that will solve every problem. But as you’ve seen recently, the failures are growing at a geometric rate: Replacing Humans with AI is Going Horribly Wrong
As someone who has built and sold an AI company and is now building the next generation AI Future of Work, let me give you the ground truth: AI is a phenomenal tool, but it's not a thinker. It's a hyper-specialized calculator. The most powerful, creative, and adaptable processor you have is the one sitting in this room between your ears. It’s the human brain.
The real question isn't "how do we replace people with AI?" it's "how do we stop wasting the brilliance of our people on tasks a machine should be doing?" Here’s how I see the landscape and the plays you need to make:
#1: The Efficiency Mirage
We're being told to throw massive computational resources at problems, but the human brain runs on a 20-watt lightbulb while training a single AI model can power a small town. Think of the Apollo engineers calculating orbital mechanics with slide rules versus the millions in cloud credits it takes to train a model today. Before you greenlight any AI project, mandate a simple assessment: is this a problem of brute-force scale, or is it a problem of nuanced thought? Use AI for the former and your people for the latter, and ideally a confluence of the two to unlock the REAL potential of Human + AI.
#2: Missing Human Understanding
AI is brilliant at pattern recognition but has zero common sense. An autonomous vehicle can drive millions of miles but still get confused by a construction worker waving traffic in a non-standard way, something a human driver understands instantly. This is the same gap I saw in cybersecurity, where a human analyst had to first understand a hacker's novel intent before an algorithm could be taught to find the pattern. Your strategy should be a symbiosis: use AI for the first 80% of data analysis, then deploy your top human talent to do the final 20% of interpretation and decision-making where the real value is created. Think of the Human as the Orchestrator, and the AI as the Helper and potentially the Actor.
#3: True Innovation Comes From People
You’ve probably heard this a few times but AI does not innovate (yet - but I have reservations with Transformer Neural Networks ever doing this but…). Instead it mimics. The Post-it Note wasn't invented by an algorithm; it was born from a failed experiment for a super-strong glue and a frustrated choir singer who needed a better bookmark. That collision of unrelated ideas is a uniquely human capability. Your next billion-dollar idea won't come from a prompt. It will come from a person who is free to think. Your job is to use AI to automate the drudgery that drains your best people so they can do the work of invention. Only humans can apply abductive reasoning to any problem, and that’s because we have learned from experience largely.
The Call to Action: Measure What Really Matters
Here’s the real tough question: If human ingenuity is your most critical asset, how are you measuring and managing it?
For decades, we’ve managed our people with gut feelings and pure guesswork. We build teams based on who's available or “good people”, not who's truly highly performant or optimal for a particular function or project. We're trying to win a Formula 1 race while treating our drivers and engineers like interchangeable parts. It's absolute madness. This is the next frontier. If you accept that your people are the engine of innovation, then you must accept the need to understand that engine with the same analytical rigor you apply to your financials.
The Future: Stop Guessing, Start Quantifying
This is precisely the problem we're solving with WethosAI. We've built a way to quantify the very human traits and cognitive biases that make your people tick and build the patterns and instincts of decision making and action. We can finally see who your natural innovators are versus your meticulous executors, why one team gels while another struggles, and if you're putting your best people in roles where they can actually thrive. The future isn't about replacing humans with AI. It's about using a new kind of AI to finally understand, align, and unleash the full potential of our people.
Stop guessing. Start quantifying the human element. That’s how you build a company that dominates the age of AI.