Anti-Anti-AI

On hot takes, hunting, and where the value actually lives

Growing up in Minnesota in the 1990s, in a sports family, meant a lot of car rides tuned to KFAN sports talk radio. The hosts were celebrities back then, giants of the local public sphere. My Grandpa Jack was a die-hard Vikings, Twins, and Timberwolves fan despite living in Western Wisconsin, and he loved his fandom so much that he fell asleep every night to KFAN coming through low and fuzzy on a red LED Casio clock radio with faux wood paneling. It stayed on until morning.

The king of the scene was Dan “The Common Man” Cole. Common, to everybody. We loved him for the ridiculous bits, the one-of-a-kind personality, and a genuine love of our local teams. Minnesota didn’t win much, so the material was plentiful. The bits wrote themselves.

One of the mainstays of his show was the monikers. Common never took a call from Bill in Woodbury. It was Billy the Bass Guy who owns a Ranger boat, frequents Cabella’s, and loves to chat weekend fishing on one of Minnesota’s 10,000 lakes. Everyone who called in was a guy or a gal, self-proclaimed, and when a familiar one came through the speakers your ears perked up, because Common was about to razz them into a good rant and you were in for a treat.

The best moniker of all time belonged to my uncle Jeff: the Anti-Anti-Hunting Guy.

Jeff called in whenever Common or a guest brought an anti-hunting take to the air, and he had the standing to do it. He grew up waking before school to trudge into the fields and swamps of Wisconsin, and then he never stopped. He has lived his whole adult life as an outdoorsman, hunting and fishing through every season, harvesting only what he was going to eat, deeply passionate about nature and the animals in it. The moniker was a bit, but it was a truthful bit with an agenda. He wanted people to hear what hunting and fishing really were from someone who lived them and loved them, instead of from the caricature.

I’m telling you this for two reasons. The first is that it’s fun to dig back through these nostalgic memories. The second is that the moniker market never closed. It went national.

The machine went national

Sports talk radio was the hot-take economy before anyone had the phrase. Takes were the currency. Razzing was the content. Conflict was the format. Common understood all of it decades before an algorithm did.

But two things were different then. Everyone was in on the bit and the stakes were the Vikings.

Then media got democratized. Podcasts handed every ordinary Joe and Jane a platform, and the distribution algorithms learned what talk radio always knew: division holds attention better than agreement does. The architecture survived. The wink did not. And the stakes climbed from whether the Twins could hit left-handed pitching to AI, data centers, employment, IP law, and whether we keep control of the most powerful technology humans have ever built.

Same machine, different soul. On the questions that matter most, nearly everyone with a microphone has indexed hard to Pro or Anti and made it their whole bit, because that’s what the platforms pay for. The people offering genuinely nuanced middle-ground positions get dismissed as biased before anyone listens. The conversation we need is the one the format ignores.

Anti-anti is not pro

Look closely at what my uncle’s moniker actually says, because there’s something hiding in it.

In a logic class, a double negative collapses into a positive. In real life it doesn’t. Anti-Anti-Hunting never meant pro-killing-animals. Jeff was against the caricature, the cartoon version of hunting that the anti-hunting position needs in order to exist. What the double negative defends is the real, conditional thing: conservation, self-sufficiency, eating what you harvest, the grit and compassion that come from a life spent in the field. The caricature flattens all of that. The anti-anti position restores it.

So call me the Anti-Anti-AI Guy.

That does not make me a booster. The accelerationists who treat every concern as a moral panic have a caricature problem of their own. The Anti-Anti-AI position holds three things at once: the technology is real, the risks are real, and the truth about both belongs to the people who practice it.

Priced out, not argued out

The AI conversation has sorted itself into two camps with names now. Boomers, or accelerationists, on one pole, doomers on the other. The writer Casey Mock described the two brands as “superficially opposed, structurally identical,” and he’s right. Both are selling confidence because confidence is what the attention economy buys. The catastrophe fits in a tweet. The utopia fits in a tweet. The conditional truth needs three paragraphs and your patience and the format doesn’t sell patience.

The squeeze on the middle is structural and it’s measurable. Researchers at NYU who studied more than half a million social media posts found that each additional moral-emotional word in a post increased its spread by roughly twenty percent. Philip Tetlock spent decades scoring expert predictions and found that the confident hedgehogs got the airtime while the self-critical foxes got the accuracy, with fame and accuracy running in opposite directions. The middle didn’t lose the argument. It lost the format.

Sometimes the pole is right

Honesty requires a concession here, because the middle isn’t automatically virtuous.

Sometimes the sharp pole is correct and the reasonable middle is the trap. The tobacco industry understood this better than anyone and weaponized it for decades. “Doubt is our product,” reads the infamous internal memo. Manufactured balance, both-sides coverage, endless calls for more research, all of it engineered to delay a verdict everyone already knew. The anti-tobacco hardliners were right. The reasonable moderates were being played.

So the middle has to be earned. There’s a difference between a lean and a hedge. A lean is a position built through contact with the thing itself, and you can say out loud what would change your mind. A hedge is a place to hide. “It depends” can be honest calibration or it can be cowardice wearing calibration’s clothes, and the test is whether there’s practice behind it. Jeff’s middle was never a hedge. He had sharp opinions and decades of mornings in the swamp backing them up.

Where the value lives

Here is what the discourse misses while people are busy at the poles. Attention and value trade in two different markets. The poles capture the attention. The middle captures the value. Right now the mispricing is enormous.

I see it every day. At Levver we build revenue systems across many businesses, in many markets, industries, and verticals, and when you do that work you see the inside of the game. AI is very good, and continually getting better, at specific mechanisms: prospect research, document ingestion and data extraction, mining call transcripts for what actually happened in a deal, and dozens of other tasks that used to eat human hours. Build those efficiencies into the system so the humans can do what humans do best, and you’re running the strategy that has won every time a new technology has arrived. Reduce the cost of moving a deal through the pipeline and closing it, and the unit economics improve. Same story in ops workflows. Same story in customer success process and engagement. Find the places where improvement is meaningful and AI can genuinely help, and that’s where the value is. Not everywhere – there.

Notice the pattern: it works here, it fails there, and here’s how we test it. That takeaway isn’t trendy or trending but it’s the only one worth money.

And notice who holds it. The people who use these tools every day trend toward cautious optimism, while the wildest takes cluster among people who barely use them at all. The poles are full of spectators. The middle is full of operators. Jeff knew the truth about hunting because he practiced it, and the same rule applies here. It’s why my lean is openly optimistic: used correctly, AI is a tool set and a capability that humans have never had before, and that’s amazing. That lean was earned deployment by deployment, including the ones that didn’t work.

The lines are open

When I first started writing this, I ended on a question. Who bridges the divide? Who’s the Anti-Anti-AI guy or gal who sees the promise of this technology and the vision for how it could make humanity better, but takes the downsides seriously and thinks hard about ushering it into society in a way that protects human beings and this beautiful, flawed experience of being here?

I’ve stopped waiting for that person to show up on a podcast. The divide won’t be bridged from a pole, and the Anti-Anti-AI guy was never going to be a pundit. He’s the operator who already lives in the middle, doing the conditional work the format can’t sell. There are a lot more of us out here than the algorithm lets you hear.

The lines are open. The moniker’s available.

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