Welcome back inside the kitchen. 🔥
😇 Ethics + Philosophy
This week’s take: AI is becoming less about doing more and more about avoiding more.
Most of the conversation around AI use focuses on time. How often are people using it? How many hours a day? Are students using it too much? Are workers relying on it too often? Those questions matter, but they don’t really get to the heart of it.
The real issue is not always the amount of AI use. It’s the role AI starts playing in your life.
Sometimes AI helps you do something you genuinely need help with. It can explain a confusing idea, clean up a messy email, help you organize your thoughts, or give you a starting point when you feel stuck. I don’t want to pretend that every use of AI is unhealthy or lazy. A lot of the time, it genuinely helps people move forward.
But there is another kind of use that is harder to notice.
AI becomes especially dangerous when it becomes the thing we reach for whenever life starts to ask something difficult of us. Not just difficult in the annoying sense, but difficult in the forming sense. The kind of difficulty that teaches patience, honesty, courage, responsibility, creativity, or judgment.
That is where this gets ethically interesting.
Writing is a good example. The hard part of writing is not always putting words on the page. Sometimes the hard part is figuring out what you actually think. A blank page forces you to sit with confusion for a while. It makes you sort through the mess in your own head. AI can help with that, but it can also let you skip it so quickly that you never really practice the struggle.
Relationships work the same way. AI can help you prepare for a hard conversation, and that can be useful. But if every uncomfortable conversation gets filtered through a chatbot first, there is a risk that we become better at crafting the perfect message than actually facing another person with humility. We may learn how to sound emotionally mature without doing the harder work of becoming more honest, patient, or responsible.
Even decision-making can change. When you are unsure what to do, AI can give you options, reasons, and reassurance. That can bring clarity. But if you keep asking for one more answer because you don’t want to feel the weight of choosing, the tool may be helping you avoid the very thing that builds judgment.
That is the line I think we need to watch.
There is a difference between using AI for support and using AI for escape. Support helps you return to real life with more clarity and courage. Escape helps you avoid the part of real life that is asking you to grow.
And the tricky thing is that escape can look productive. You are drafting the message, improving the essay, processing the conflict, organizing your thoughts, getting advice, and making a plan. On the surface, it all looks responsible. But underneath, AI may be quietly teaching us that we never have to sit very long with awkwardness, uncertainty, boredom, criticism, loneliness, or the frustration of not being good at something yet.
… And these are the place where growth often happens.
A person becomes a better writer by wrestling with unclear ideas. A person becomes better at relationships by learning how to have uncomfortable conversations without running away. A person becomes more mature by taking criticism without immediately defending themselves. A person develops judgment by making decisions without perfect certainty.
We squander that development if we turn to AI when anything gets hard.
So the issue is not that AI makes life easier. Some parts of life should be easier, and that’s great. Nobody becomes a deeper person because they spent three hours formatting a spreadsheet or rewriting the same basic email ten times.
But not all friction is the same.
Some friction is pointless. Some friction is formative.
The danger is that AI does not always know the difference, and honestly, neither do we when we are tired, anxious, lonely, or overwhelmed. We just know that the tool can make the discomfort go away for a moment.
That is why the better question is not simply, “Am I using AI too much?”, but “What am I hoping AI will keep me from having to face?”
Because if AI helps us face the right hard things with more clarity, that is a gift. But if it becomes a polished way to avoid the hard things that make us honest, courageous, patient, and wise, then the convenience comes with a real cost.
💰 Money
(This is for educational purposes only… not investment advice)
This week’s take: One of the more underrated AI trends in logistics is not self-driving trucks. It is making the trucks we already have much smarter.
Most people think the future of trucking is autonomous vehicles. That may eventually matter, but there is a quieter and more practical AI shift happening inside the freight network itself.
Less-than-truckload shipping, or LTL, is the perfect example. This is the kind of freight that is too big for UPS, but not big enough to fill an entire semi-truck. So carriers have to combine shipments from lots of different customers, move them through service centers, sort them, reload them, and keep the whole system moving without wasting space.
That makes LTL a giant optimization problem.
The challenge is not just “get this shipment from point A to point B.” It is figuring out how much trailer space the shipment actually uses, what route it should take, which service center should handle it, when it should be loaded, and how to price it so the carrier is paid fairly for the space, weight, distance, and complexity involved. Every cubic foot matters.
If a truck leaves with wasted space, that is lost revenue. If a shipment is priced incorrectly because the dimensions are wrong, margins suffer. If freight is loaded poorly, it can slow down the network or increase damage. This is where data, automation, and route-planning technology become quietly valuable.
The company I’m watching: Old Dominion Freight Line
Old Dominion is one of the strongest LTL carriers in the country, and its advantage is not just that it owns trucks. Its advantage is that it runs the network extremely well.
LTL freight is a hard business because small mistakes compound quickly. A few bad loads, inefficient routes, mispriced shipments, damaged freight, or slow service-center operations can eat into profits fast. Old Dominion has built a reputation for discipline, service quality, and efficiency in an industry where that is difficult to maintain.
This is where its technology investments matter.
Old Dominion uses tools like dimensioners to measure freight more accurately, route-planning systems to optimize movement, and dock and yard management systems to track shipments across its network. That may not sound like AI in the way Silicon Valley bros usually talk about AI, but it is exactly the kind of data-driven optimization that makes a physical business more profitable.
The simple thesis is this: Old Dominion is using technology to get more value out of every truck, route, dock, shipment, and cubic foot of trailer space.
That is why the company’s operating ratio is so important. In trucking, a lower operating ratio means the company is spending less to produce each dollar of revenue. Old Dominion’s Q2 2026 operating ratio was 70.1%, which is extremely strong for the freight industry.
That does not happen by accident. It comes from pricing discipline, network density, route efficiency, service quality, and smart use of data. While competitors chase autonomous trucking headlines, Old Dominion is using technology to improve the economics of freight today.
There are risks, of course. Freight is cyclical. If industrial demand slows, shipment volumes can fall. Not to mention, fuel costs remain incredibly uncertain and can massively cut into margins.
But the reason Old Dominion is an interesting company is that it shows a less obvious version of the AI industry. Not AI replacing the driver, but AI helping the whole freight network run with fewer wasted miles, fewer wasted inches, and better margins.
That may not sound futuristic, but in logistics, that is exactly where the shift is.
What was the temperature of this week's edition of Inside the Kitchen?
Hi — I’m Hunter, a PhD candidate whose work has appeared in major academic journals and popular tech outlets. I founded FryAI to make staying ahead of AI clear, accessible, and fun.
📧 Email me directly if you have any questions or want to chat!