Through Another Lens Podcast
A note before you start. This one comes with a song called “Nine Feet Up.” Read first and let the song land after, or listen first and let it set the room. Either order works. Duey Freeman rides a horse named Moon, and when he does, the top of his head is nine feet off the ground. He spent sixteen years on search and rescue in Colorado, and when the terrain got too rough for vehicles, they sent crews of six or eight horses out in formation across the plains and into the boulder fields. From that height, you could see three times what a person on foot could cover. But the real advantage wasn’t the altitude. It was the silence. You could hear people. Sometimes it was shouting, sometimes it was crying, and sometimes, in the worst cases, it was just breathing. That sound, a human being making the smallest possible noise to signal they were still alive, is what found them in the places where nothing else could. Then the drones came, and that part went away. Duey is clear that drones are remarkable. They go where horses can’t, they cover ground faster, and with the right equipment, they can read heat signatures through terrain no human team could navigate. The tool genuinely solved a problem. But the drone’s rotors make noise, constant noise, and that noise filled the very silence that used to carry the signal. You gained a camera and lost an ear. The team got more altitude and less contact. Those two things happened simultaneously and they weren’t separate events. They were the same event. Every Tool Upgrade Is a Sense Trade Every tool upgrade is a sense trade. It sharpens one kind of perception and dulls another, in the same motion, no exceptions. This isn’t a complaint about technology, it is just the architecture of how tools work. A tool extends one capability by concentrating energy there, and that concentration always costs something on the other side of the ledger. The drone designers weren’t careless. They were solving the visibility problem, and they solved it. The hearing problem wasn’t in their design brief. It wasn’t even visible to them as a problem, because they had never been nine feet up on Moon in a boulder field listening for someone’s exhale. The tool doesn’t know what it is missing. That isn’t a flaw in the tool. It is the definition of a tool. The flaw only enters the picture when the person operating the tool forgets that the tool’s ignorance isn’t the same as their own, and stops trusting what sixteen years in the boulder fields already taught him. Having the Tools Isn’t Having the Taste Having every tool in the kitchen doesn’t make you a chef. The knives, the pans, the right burner, none of that turns out a good plate. What turns out a good plate is having cooked the same dish wrong a thousand times until you know, by smell and by feel, when it’s finally right. That’s taste. It doesn’t come from the equipment. It comes from having been in it long enough to trust your own judgment over anyone else’s, including the machine’s. The Trust Problem This is where the conversation about AI lands, and lands hard. There is a version of working with these systems where the reps you’ve put in are still the final judge of what’s good, where the tool’s speed serves your taste instead of replacing it. Then there is the other version, the one worth worrying about, where you stop trusting what you know and start trusting what the system hands you, simply because it arrived fast and looks finished. You take the output at face value instead of running it through everything you’ve earned. That isn’t a tool problem. It’s a trust problem, and the trade is yours to make or refuse. How the Habit Moves In Handing your taste to the tool isn’t a dramatic failure. It happens in small increments, each one reasonable in isolation. You let the AI draft the language because it sounds close enough, so you stop asking whether it actually sounds like you. Absence stops registering. Not because you stopped caring. Because the machine kept moving, and it was easier to let it. The habit doesn’t announce itself either. It just moves in, one skipped question at a time, one place where your own taste would have caught something and didn’t get asked to. The crying goes unheard. Not once, loudly, in a way you could catch and correct. It goes unheard at scale, quietly, across everything you are producing, and the gap between what your work used to carry and what it carries now widens without announcing itself. The Leaders Worth Watching The leaders worth watching right now are the ones who still trust the thousand reps over the machine’s confidence. They use capable tools, and they bring something the tool can’t access: a long memory of what the work felt like before the tool arrived, a calibrated sense of what a real result sounds like versus a plausible one, and the discipline to stay in the search even when the drone is already in the air covering ground. You can see it in the small habits. They read the draft twice, not once, the second time listening instead of scanning. They ask what’s missing before they ask what’s polished. They trust the plate they know how to cook, not the recipe the machine just handed them. They aren’t Luddites. Duey still gets calls sometimes, years after he stopped riding search and rescue. People want to know how he found the ones nobody else did. He never says the equipment. He says the ear. The ear caught the exhale nobody else heard, once, under a downed pine, in weather that would’ve grounded any drone, and the ear only knew what to listen for because of sixteen years spent trusting it. Refined taste isn’t about selecting better tools. It’s about trusting what your own experience already taught you, over whatever the tool hands you first, and refusing to serve the plate before you’ve tasted it yourself. Nine feet up in the silence is where you learn the difference. Listen to “Nine Feet Up” on Suno: https://suno.com/s/kNwnXcCGuwRQ99ZJ Get full access to Through Another Lens at marksylvester.substack.com/subscribe [https://marksylvester.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]
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