Here's how to Captain your AI - by Michael Carroll

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Here's how to Captain your AI<br>The AI chatbot paradigm demotes productive humans to button-pushers. Leverage your judgement and ownership from the captain's chair instead — reviewing the ship's logs, not approving every turn.

Michael Carroll<br>Aug 09, 2026

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This is part 2 of 2 on the Captain Strategy. Part 1 argued that we’re all using AI to become the bosses we hate — micromanaging assistants instead of building functions with defined inputs and reviewable outputs. Now, how to get to AI functions? It starts with changing the entire way you interface with agents.

First, your bi-weekly dose of AI news (as if you aren’t inundated with it already):

Here’s a new news category I’m sure you will see more of:<br>Add AI to Old, Boring Thing & Turn it Into News<br>The boring thing : A hedge fund overleverages itself and implodes.<br>Why it’s boring : Yes, these are a lot of fun to watch, especially when the hedgie in question is young with a very chiseled, instantly unlikeable face. But we basically get a new story of “hedge fund takes on too much debt and firesells everything“ every 3-5 years since the 90s. It’s more predictable than presidents campaigning on tax cuts.

How AI got added to it : The guy making the bets wrote essays on AI (like 90% of the Internet today). He bought heavily into the AI bubble (like 90% of Wall Street today). He used to work for an AI company (which, if you believe the press releases, are 90% of all companies). Apparently all of that equals “big AI scoop”.

Verdict : 🙄 but with a pleasing dose of schadenfreude

HBR: AI agents are cheaper and faster than assistants<br>I wrote about this last week. Maybe you didn’t believe me? Well Harvard Business Review & Perplexity folks helpfully crunched the data and put it in a chart for you.

Worth reading the whole article!

NYT primer on tokenomics<br>You know a tech trend is going mainstream when the NYT writes about it.

Somehow, though, every “expert” quoted in the article seems focused on convincing how hard of a problem determining value of AI is. You can practically hearing them sharpening their knives as they position themselves to charge enterprise exorbitant “AI tokenomics” consulting fees.

Well, not to be left out, here’s my shameless plug: Coolhand Labs gives you basic token/cost calculations you can stand on for free. No need to spend six figures on consultants. We will give it to you for free. (You are welcome.)<br>Now, let’s talk about how to manage your AI workloads like a captain!

What a captain actually does

A ship’s captain doesn’t do every job on the ship. In fact, you could be forgiven for wondering if they do any job at all.<br>Captains DON’T:<br>❌ stand in the engine room adjusting valves<br>❌ personally trim the sail<br>❌ take the wheel and steer... unless, of course, the ship is sinking.

Better put: if you are doing every single job on a boat to make it sail, you aren’t captaining a ship: you are rowing a canoe.<br>In my last post, I talked about why people aren’t finding productivity or satisfaction with agents: they’ve used AI to go from rowing the canoe to shouting realtime commands at whoever’s holding the paddle. It’s a management anti-pattern that’s been around so long that Dr. Seuss parodied it sixty years ago, in I Had Trouble in Getting to Solla Sollew:

But “Go left, go right, all day and all night” is exactly where we end up when we use chatbot interfaces! Nobody in that picture is a captain — and the chap furnishing the brains isn’t getting to his destination any faster for it.<br>Spoiler Alert: None of the people in that book ever get to Solla Sollew.<br>An actual captain’s job is to provide direction to the crew. Sometimes they give it in realtime — navigating a storm — but typically they give it by reviewing the crew’s reports at the end of the day.<br>The Captain Strategy asks you to approach using AI the same way: instead of parking yourself on top of every turn the AI takes, move to reviewing the AI’s final outputs — or, at most, the one genuinely critical gate the AI can’t clear on its own, because it lacks information only a human has or because something must be verified before the rest of the work can safely proceed.<br>Captains SHOULD:<br>✅ set the course<br>✅ review the outcomes of the crew’s daily work<br>✅ give feedback and, if necessary, dig into the details of systemic problems<br>✅ with any spare time, hunt down inefficiencies across the whole operation (always easy to find if you bother to look)

This isn’t a workflow tweak. It’s a re-architecture of the job’s entire UX — from “micromanaging a worker” to “captaining a process.”<br>What’s holding most people back from this? It’s often not that they love micromanaging too much — it’s that they don’t have their AI processes set up in a way that can enable this. So let’s talk about how you get there.<br>The Everything Engineer is free — now and forever — so subscribe to join 100s of AI engineers &...