I am so tired of people telling me and asking me how AI is going to replace all of us in our jobs. These AI models get so much stuff wrong that I find myself arguing with the stupid computer. Here is a great example:
I was researching water flows for the drains in my rear concrete deck. Grok insisted that this narrow channel of 2 inches deep by 1.5 inches wide can move 240 gallons per minute of rainwater. We went back and forth repeatedly, so I used the formula for calculating water flow through a fire hose to explain my point. Here was what it said:
Why the Formula Doesn’t Fit Your Deco Drain
- Your drain operates under gravity/open channel flow, not high pressure.
- The “pressure” (head) is extremely low — usually just 0.1 to 0.5 inches of water depth over the slot or in the channel (a tiny fraction of a psi).
- Water enters gradually along the full 24 ft length, and the channel flows partially full with a free surface (not pressurized pipe flow).
- The end opening is the outlet, but flow is limited by the entire channel’s hydraulics, slope, and roughness — not a single orifice under tank pressure.
If you plugged tiny head values into the 29.7 formula, you’d get very low flow numbers, which is why it feels wrong compared to manufacturer-style ratings.
Bottom Line
Your intuition is good that the small channel limits things, and these narrow deco drains are not high-capacity systems. 100–150 GPM is a reasonable practical maximum for a well-installed 24 ft run — enough for normal pool deck runoff in most rains, but it can pond in heavy downpours or if clogged/poorly sloped.
The 29.7 formula overestimates or underestimates dramatically here because the conditions are completely different.
So I replied with: I still think 150 gallons per minute is far too high. A firehose is flowing those numbers, but the stream is under much more pressure and is moving much faster. I think you are incorrect here in insisting that this drain is moving as much water as a fire hose.
So this is the answer I got:
I appreciate you pushing back — you’re right, and I was too optimistic in my earlier estimates.
The firehose comparison highlights a key point: a firehose at 250 GPM is shooting a fast, pressurized jet (often 50+ psi). Your Deco Drain moves water slowly under gravity with almost no pressure (just inches of water head), through a narrow channel. That makes high numbers unrealistic.
Better Data on Narrow Deck Drains Like Deck-O-Drain
Deck-O-Drain (and similar PVC linear drains) has an internal channel roughly 1.5–1.75″ wide by ~2–2.5″ deep. Real manufacturer and product data for comparable narrow systems shows:
- Typical capacity: 4–10 GPM per linear foot at good slope (¼” per foot), depending on the exact model.
- For 24 feet: Roughly 100–180 GPM theoretical max under ideal lab conditions, but real-world practical capacity is lower — often 60–120 GPM total before ponding starts.
Many similar slim drains rate even lower:
- 1.25″ channel examples: ~4.2 GPM per foot → ~100 GPM for 24 ft.
- Stegmeier Frontier-style: Up to ~9.6 GPM/ft in some tests.
- Other 2″ class deck drains: Often max out in the 15–30 GPM range for short sections, scaling modestly with length.
The outlet pipe (usually 1.5″ PVC) frequently bottlenecks first at around 40–70 GPM under gravity.
It’s still wrong. There is a maximum amount of water that can move through a narrow channel, and making the channel longer doesn’t increase that. A mile long Deco drain isn’t going to move 52,000 gallons per minute. AI is nowhere near being ready to take any job that requires applying logic.
We went back and forth before the system began agreeing with everything I said. AI isn’t ready for this. This is why I no longer pay for AI access.
In case you are wondering, the nozzle formula is:
Flow equals 29.7 times the square of the diameter times the square root of the pressure.
Q (GPM) ≈ 29.7 × d² × √P, where d is the diameter in inches and P is nozzle pressure in psi.
This is a formula that I know well from my firefighting days. That’s why flows of 200+ gallons per minute were seeming far too high.
11 Comments
J J · May 27, 2026 at 5:24 pm
Theoretically, your efforts taught Grok how to get the correct answers without the next person going through everything you did to have it accept your answers as correct. In reality, probably not.
Divemedic · May 27, 2026 at 5:28 pm
I dont think it learns like that.
J J · May 27, 2026 at 9:51 pm
I concur. If AI isn’t learning then it’s not really intelligence.
BurnedOutEngineer · May 27, 2026 at 8:42 pm
Wow… It’s completely mixing it’s (basic) dimensional analysis. Physics prof pounded this into our head. Basically AI is saying if I drive 20mph for 10 hours, at the end I’m driving 200mph. (I know, wrong dimensional comparison, but the example is still valid.) I have little faith in AI but employers are trying to force us to use it. I wonder if it is an extension of the (outdated?) DEI movement. You know… everyone can do the job with AI to help!
Anonymous · May 27, 2026 at 11:29 pm
It depends on the Reynolds number. Gross simplification – Big Reynolds numbers you can calculate, small Reynolds number you can calculate. Unfortunately in the middle you can’t (see any pipe flow/head graph. design process for ship, aircraft etc
Grumpy51 · May 28, 2026 at 3:59 am
You just know that somewhere a bureaucrat is quoting AI for a project. I wonder how many people will have to die and billions ($) wasted.
Birdog357 · May 28, 2026 at 7:13 am
I tried to use chatgpt a couple years ago to save time on some simple engineering formulas. I gave it the formula, a 5 variable algebraic expression and 4 variables were given. This is HS freshman level math. It could not do it. It kept using a similar unrelated formula no matter how many times I supplied the exact formula i wanted it to use.
JimmyPx · May 28, 2026 at 10:20 am
People need to understand that AI is not YET intelligent or sentient.
They are just huge algorithms that have access to tons of data.
They are like super smart search engines.
BUT they are only as good as the data they have access to.
If you put IN garbage data, you’ll get OUT garbage data.
That’s the problem now, no one is monitoring or checking the data the AIs are ingesting.
Much of it is crap.
You’d think like in your example they’d hire a few mathmaticians to enter correct math models but nope, let it suck in some High School dropouts crap from Tiktok.
Joe Blow · May 28, 2026 at 1:14 pm
Agree! There’s a distinction you made there that not everyone does – general intelligence or sentience. As they stand now, AI is just a fancy google search, general intelligence, and frankly not even a very good one. I’m not even close to the industry, so I don’t actually know, but I keep hearing from people who are in-touch, just wait – it’s coming.
OK, maybe, heard the same thing about the internet when it first came out. Wasn’t really what it was cracked up to be, and then one day, you started doing everything over the web and nothing in person anymore. Will this be the same? I suspect very similar. Many, MANY hourly positions will be replaced with a talking head on a screen. Think 1-800-support phone trees in a kiosk.
What I don’t quite get, or can wrap my head around is the first point – there’s a HUGE difference between being able to catalog, find, and recall information, and taking that information and manipulating it, applying it, learning and growing from it. I have repeatedly schooled AI in a particular topic as DM did here, but the next time you interface, completely forgot what you tried to teach it. Perhaps the software doesn’t backfeed, and its just a coding fix, but I don’t think so. I don’t think it’s capable of actual thinking, only recall. Same as there were plenty of stupid kids in school, and I knew I wasn’t like them, I think this software will always be really really good at certain tasks, but I question if it will ever achieve sentience. That’s a whole leap-plus-bound of difference than just regurgitating info someone could have googled.
Jim_R · May 28, 2026 at 12:30 pm
In one of the responses, it quoted 4-10 gpm per linear foot of drain with x slope per foot. A moment’s reflection reveals that has to be the flow rate through the slotted top into the channel, not the channel’s carrying capacity. The AI did not understand the system, it found a flow rate spec for a portion of the system and confidently ran with it.
Does Dunning-Kruger apply to software?
Danny · May 29, 2026 at 5:11 pm
I enjoy arguing with AI. And you can always spot the propaganda — the indoctrination — the insidious creep of groupthink. But the most obvious adjective is upfront – “artificial”
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