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Welcome everyone today on the 
Joseph Carlson show Duolingo. 

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The stock that's on everyone's 
mind. 

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It's down a staggering 29% on 
the day. 

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The stock price is being 
obliterated. 

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And why is that? 
Well, the stock is obviously 

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being re rated because investors
are now concerned about its 

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future deceleration in growth. 
Now anytime a highly rated 

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stock, one that's trading at a 
higher multiple, has any 

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concerns with its growth, 
investors sell out of the stock.

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They rate it much lower. 
And that's what we're seeing 

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happen here. 
So this is clearly a rerating 

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event and this is something that
I have a little bit of 

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experience with. 
In the past with Netflix, that 

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was another stock that concerned
investors for a time and 

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investors quickly re rated the 
stock to a much lower multiple, 

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causing it to fall 75% from the 
highs. 

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So given this situation with 
Duolingo, what do we do? 

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Do we sell out of the position? 
Do we accept our losses, do some

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tax loss harvesting and move on?
Do we hold the position? 

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Do we buy more and double down? 
There's a number of options 

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available to investors in these 
situations and what investors do

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in these specific scenarios, in 
these exact situations where 

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stock like Duolingo sells off 
dramatically, what we do now 

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can, in many cases, determine 
your future returns to a huge 

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extent. 
So we'll be talking about 

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Duolingo and I'll be going over 
some of the fundamentals of the 

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business as well as commentary 
from the management. 

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Management held an earnings call
yesterday that I will admit was 

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one of my favourite earnings 
calls ever. 

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It was incredible to listen to 
the vision of this management 

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and I want to go ahead and 
highlight some of the things 

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that the CEO said on this call. 
So we'll be looking at 

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everything. 
We'll be looking at the 

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portfolio, the position sizing, 
all of the damage being done by 

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Duolingo. 
We'll go over all of it. 

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Now, of course, we have other 
news to get to. 

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Google is on the move again. 
It's one of the rare stocks 

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that, at least right now, is in 
the green. 

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On this red day, Google is by 
far my largest position. 

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It's one that I'm very proud to 
have as my largest position 

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because like I've said many 
times, I've never seen so many 

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good things going on with a 
single stock. 

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It's incredible. 
And this is just one more thing 

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to add to the list. 
Google is now rolling out its 

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most powerful AI chip, taking 
aim at NVIDIA with custom 

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silicon. 
This company is doing it all. 

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It's just doing it all. 
We're going to be looking at 

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Google's advancements. 
And then finally, we've already 

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had a fail of the week this 
week, but we have a second one. 

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So that's two fails of the week.
And in this case, it's going to 

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be Chipotle. 
Chipotle is struggling. 

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Unit volume is going down. 
Customers are frustrated. 

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One of the primary reasons is 
the inconsistent portion sizes. 

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Sometimes you get a big burrito,
sometimes you get a small 

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burrito. 
You never know. 

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It feels like a gamble going to 
Chipotle. 

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And in this episode I will be 
fixing Chipotle. 

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I have the solution, I have the 
answer. 

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I can fix this company and get 
it back on track. 

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We'll be going over that fix. 
So we have a ton to get to in 

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this episode, a lot to go over. 
We're going to be jumping into 

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all of it. 
Just a quick mention before we 

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jump in. 
I have launched Qualtrim Direct,

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meaning that you no longer need 
to go to Patreon to sign up for 

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Qualtrim and join the Joseph 
Carlson Show Discord community. 

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Now this is a great value 
because you get both 

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qualtrim.com full access to it, 
the entire website, all the 

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benefits, all the bells and 
whistles for 10 bucks a month. 

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And you also get the Joseph 
Carlson Show Discord included 

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with that. 
So there's no upsells, there's 

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no cross selling, it's all just 
one thing and you can sign up 

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directly on qualtrum.com without
ever using Patreon. 

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Now there's two different plans.
One of them is $10 a month. 

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You get a free trial, a 7 day 
free trial. 

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The other one, if you really 
love the service, you can pay 

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$8.25 a month on average billed 
once a year. 

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So this is the annual plan. 
Either way you pay, it's dirt 

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cheap. 
We now have above 11,000 users. 

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In the past week alone, we've 
had 800 people sign. 

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Up so I appreciate everyone for 
trying it out and the reviews 

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have been. 
Overwhelming, I mean it's just, 

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it's awesome to hear people's 
great experiences with the 

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product saying this is amazing. 
I've I've tried it out. 

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It's exactly what I've been 
looking for. 

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We're getting a lot of that. 
So I appreciate everybody and 

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hope you have a good experience 
with it. 

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Now let's go ahead and jump in. 
The first thing I want to 

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mention with Duolingo is we can 
look at my position sizing 

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because this isn't just some 
stock. 

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This is one that's in My 
Portfolio now. 

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It's in the story fund and here 
we have it. 

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If we look at the story fund, 
this is a little bit more of a 

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an aggressive portfolio, so to 
speak. 

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In general, these stocks are 
more volatile, they're more 

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aggressive, they're faster 
growing. 

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And you'll also notice a theme 
that they're almost always 

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subscription based companies or 
their data companies. 

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They offer products that people 
use for a very long period of 

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time. 
So they're not very 

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transactional companies. 
These aren't ones that you have 

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an experience with once and then
you leave. 

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So they're not like car 
companies. 

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These are companies where you 
live with the product, you use 

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it all the time. 
It becomes part of your daily 

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routine. 
Think about the fact that Amazon

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is a product that is a part of 
my life. 

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I, I have immense lifetime value
with Amazon, Netflix as well. 

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I think I'm going to have a 
membership for the rest of my 

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life. 
Same with Google. 

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I use their products every 
single day, all day, all the 

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time. 
Microsoft, the same thing. 

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Then we have S&P Global. 
This one is a a bit different 

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because it's more detached, but 
it is ingrained and embedded in 

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all of the markets. 
But then we have more of this 

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with Duolingo. 
This is another stock that 

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despite the volatility, despite 
the fact that the stock price is

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all over the place, this is a 
company that people use all the 

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time. 50 million people are 
using this every single day, 50 

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million a day and even more on a
monthly basis. 

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Now the thing that I want to 
highlight with Duolingo before 

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we even get into the analysis of
what's going on and what I plan 

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on doing is I want to emphasize 
one point and that is position 

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size. 
Duolingo has always been a small

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sized position and the reasons 
for that were intentional. 

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I intentionally put it as a 
smaller position because I 

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recognize the inherent risk and 
volatility in the company. 

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It is a small company, meaning 
that it has higher levels of 

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volatility. 
Smaller levels of capital move 

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the stock more, either up or 
down. 

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That increases the amount of 
volatility, which in many cases 

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increases the amount of risk 
because when stocks go up 50% or

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down 50%, it can become much 
more difficult to hang on to 

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that company. 
So volatility was part of the 

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reason that I kept it as a 
smaller position. 

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Another reason why is because 
the company is less established 

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in many other positions. 
For example, no one can 

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reasonably argue that Duolingo 
has a much more proven Moat and 

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proven business model than 
Google, Netflix, or Amazon. 

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You just can't. 
Google, Amazon and Netflix are 

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just way more proven stocks. 
They're more at a steady state. 

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They're more mature now. 
Netflix 10 years ago, then you 

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could argue that they're on par 
with each other. 

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Netflix 10 years ago was a bit 
more dicey. 

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It was a bit more risky, so to 
speak, but that's where Duolingo

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is now. 
It's earlier in its arc. 

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The probabilities, the outcome 
distribution is wider than these

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other companies. 
Now, having said that, I've 

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taken in all of these risk 
factors and I assessed that this

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stock needed to be a smaller 
position and I sized it as a 2% 

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position. 
Let's go ahead and just take a 

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look at how this looks on 
Qualtrm. 

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I can look at my passive income 
portfolio and the story fund 

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where I can look at them 
combined. 

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So let's go ahead and just take 
a look at them combined for a 

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minute. 
We have here at the top Google. 

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Google is a 13% position. 
A lot of that is growth. 

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Google stock has grown to 
$72,000 in gains, not counting 

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dividends paid. 
And then the rest of it is 

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deposits I've deposited into 
Google. 

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I've purchased myself over 
$100,000 of Google stock. 

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So an enormous amount of money 
has been spent on Google at all 

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varying stock prices because I'm
so bullish on this company. 

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But Google's also grown with 
72,000, so it's roughly a 

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$172,000 position. 
Now. 

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We also have Amazon 11%, S&P 
Global 9% or 10%, Netflix 10%, 

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and all these companies have 
made massive gains. 

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Then we Scroll down the list. 
We have all these holdings, 6%, 

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eight percent, 5%, four percent,
3% for Equifax. 

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Even Texas Roadhouse, which I 
sold off half my position is a 

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3.2% position right now. 
Duolingo is less than a 1% 

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position now. 
That's partly because it's sold 

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off by half the position. 
It's down $11,000. 

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Before this company sold off, it
was a 2% position. 

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So when from 2% it's down 50%, 
now it's at a 1% position, 

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meaning the total impact on My 
Portfolio, the NAV of My 

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Portfolio was deemed by 1% 
because of Duolingo's 

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underperformance. 
Now I'll admit, having a 1% hit 

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to My Portfolio is not fun. 
I want every single stock I make

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to be a successful one. 
I try hard to make good 

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investments, so it's not good. 
I'm not celebrating that the 

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00:09:05,640 --> 00:09:09,640
stock is down 50% and that it's 
a 1% hit to My Portfolio. 

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But the reason that I bring this
up is because it's important to 

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look at position sizing. 
A lot of times when we look at 

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other people's investments, we 
just see a list of holdings. 

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But looking at how much money 
they have in every holding is 

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incredibly important. 
For example, the total amount 

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that I've put in the Duolingo 
myself is $20,000. 

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That's what I've contributed. 
So the most that I can lose on 

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the stock is around $20,000. 
Now with Google, I've 

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00:09:34,920 --> 00:09:36,840
contributed five times that 
amount. 

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00:09:37,240 --> 00:09:40,200
So it's a $100,000 contribution 
to Google. 

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So Google's over five times the 
size of my contribution to 

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Duolingo, and that represents my
levels of conviction in these 

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stocks. 
Now, that shouldn't be 

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00:09:49,160 --> 00:09:52,840
interpreted as me being bearish 
on Duolingo, but I just believe 

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that it's deserving of a smaller
amount of capital. 

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I think that's prudent 
investing. 

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And I've highlighted this before
today. 

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This is something that again, 
I've been saying for months. 

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Three months ago I said it's 
fair to say that a much smaller 

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market cap, higher volatility, A
thesis more heavily dependent on

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continual high growth rates, and
only a partially proven durable 

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Moat are all factors in the 
smaller size position for 

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Duolingo compared to other more 
established companies. 

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That's what I wrote on my 
Discord a couple months ago when

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I was continually asked about 
why the stock is such a small 

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position in My Portfolio. 
So I've had experience with 

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stocks dropping. 
In fact, I've seen rerating 

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events like this happened before
first hand. 

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One time with Netflix years ago,
I had Netflix as my top 

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position. 
Netflix was a stock that I was 

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00:10:40,160 --> 00:10:42,360
so bullish on. 
I couldn't even contain my my 

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00:10:42,360 --> 00:10:45,360
excitement about the company. 
I made video after video about 

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the stock. 
You can go back and look at this

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00:10:46,720 --> 00:10:51,240
very channel. 
Look at around 2020-2021, 2022. 

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That's where you'll see a lot of
content about Netflix. 

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Netflix ran into troubles with 
future expected growth. 

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They said that they're not only 
not growing with subscribers, 

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they're actually churning. 
They're going to lose some 

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00:11:03,040 --> 00:11:04,280
subscribers. 
They're going to lose about a 

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00:11:04,280 --> 00:11:07,240
million subscribers. 
Wall Street didn't like that the

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00:11:07,240 --> 00:11:12,000
stock price valuation was rated 
and dependent on continued fast 

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future growth. 
When Netflix indicated to 

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investors that growth is going 
to be upset, that growth is 

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going to be much slower than 
expected, that they may not even

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00:11:20,560 --> 00:11:23,720
have a total addressable market 
to grow into, investors became 

227
00:11:23,840 --> 00:11:26,680
incredibly bearish on the 
company incredibly fast. 

228
00:11:27,120 --> 00:11:28,880
And in many cases, this can 
catch you off guard. 

229
00:11:28,880 --> 00:11:31,280
It did with me. 
I didn't know that Netflix is 

230
00:11:31,280 --> 00:11:34,720
going to sell off 75%. 
After all, I had it as my 

231
00:11:34,720 --> 00:11:38,360
largest position. 
So Netflix begin to sell off 

232
00:11:38,360 --> 00:11:40,880
quarter after quarter, 2 
consecutive quarters and it sold

233
00:11:40,880 --> 00:11:45,720
down 75% from the highs. 
My top position was completely 

234
00:11:45,720 --> 00:11:49,480
obliterated. 
Now that was really stressful. 

235
00:11:49,560 --> 00:11:51,760
That was not a fun thing to have
happen. 

236
00:11:52,160 --> 00:11:54,680
And ever since then, I've been 
careful when I invest in 

237
00:11:54,680 --> 00:11:58,160
companies that are dependent on 
continued high growth rates, 

238
00:11:58,200 --> 00:12:00,920
ones that have a lesser 
established and more volatile 

239
00:12:00,920 --> 00:12:03,440
story. 
In that case, Netflix was my 

240
00:12:03,440 --> 00:12:06,240
biggest position. 
So that was a pretty tragic 

241
00:12:06,240 --> 00:12:09,800
event for My Portfolio. 
In this case, Duolingo is my 

242
00:12:09,800 --> 00:12:12,760
smallest position. 
It is not a tragic event. 

243
00:12:13,120 --> 00:12:15,080
This isn't something that's 
really going to impact the 

244
00:12:15,080 --> 00:12:17,160
portfolio performance over the 
long term. 

245
00:12:17,560 --> 00:12:20,760
It is so far a 1% Ding to the 
portfolio now. 

246
00:12:20,760 --> 00:12:23,360
In any case, I don't like it 
when my stocks go down. 

247
00:12:23,360 --> 00:12:26,080
I want all my investments to do 
well, including Duolingo, 

248
00:12:26,080 --> 00:12:27,800
including even my small 
positions. 

249
00:12:28,040 --> 00:12:31,000
I put the $20,000 into this 
stock because I want to make 

250
00:12:31,000 --> 00:12:33,000
money with it. 
So let's go ahead and just take 

251
00:12:33,000 --> 00:12:34,320
a look at the situation that 
we're in. 

252
00:12:34,560 --> 00:12:38,280
The stock is is being re rated. 
It's down 30% and these type of 

253
00:12:38,280 --> 00:12:40,360
sell offs happen for specific 
reasons. 

254
00:12:40,640 --> 00:12:42,920
They happen because investors 
have determined that this 

255
00:12:42,920 --> 00:12:46,480
company no longer deserves the 
premium multiple that it once 

256
00:12:46,480 --> 00:12:48,600
traded at. 
So they re rate it down to a 

257
00:12:48,600 --> 00:12:51,280
lower rating. 
The most common reason why is 

258
00:12:51,280 --> 00:12:55,160
because this company is 
dependent on high growth. 

259
00:12:55,680 --> 00:12:59,240
Investors have outlined an 
underwritten high amounts of 

260
00:12:59,240 --> 00:13:01,000
growth, revenue growth of the 
company. 

261
00:13:01,400 --> 00:13:04,120
And so far Duolingo has 
delivered on that revenue 

262
00:13:04,120 --> 00:13:05,920
growth. 
You can see the very fast 

263
00:13:05,920 --> 00:13:08,720
revenue growth. 
They're growing 41% it it 

264
00:13:08,720 --> 00:13:12,200
continued growing in the future,
but Duolingo gave investors a 

265
00:13:12,200 --> 00:13:15,920
reason to be concerned that 
growth may be decelerating, and 

266
00:13:15,920 --> 00:13:18,600
that was in their earnings. 
Report, in their earnings 

267
00:13:18,600 --> 00:13:22,280
report, they go over everything,
but I want to skip to the 2025 

268
00:13:22,280 --> 00:13:25,160
outlook and beyond. 
When we look at the 2025 

269
00:13:25,160 --> 00:13:28,520
outlook, they have something 
here called bookings, the Q4 

270
00:13:28,520 --> 00:13:33,960
bookings, so next quarter to 
grow 22% year over year or 19% 

271
00:13:33,960 --> 00:13:36,920
on a constant currency basis at 
the midpoint. 

272
00:13:37,360 --> 00:13:41,000
Now why is this important? 
It's important because Wall 

273
00:13:41,000 --> 00:13:44,040
Street believe that they're 
going to grow their bookings at 

274
00:13:44,040 --> 00:13:48,400
around 24%, which is more than 
what they said they're going to 

275
00:13:48,400 --> 00:13:50,520
grow. 
So Wall Street's saying, oh wow,

276
00:13:50,800 --> 00:13:54,400
not only did they not meet their
booking estimates or exceed it, 

277
00:13:54,760 --> 00:13:57,680
but they didn't even come close.
They're they're below what we 

278
00:13:57,680 --> 00:14:01,240
expected them to grow. 
And so we see a company that's 

279
00:14:01,240 --> 00:14:04,840
growing slower than expected. 
Now what is the booking growth? 

280
00:14:05,200 --> 00:14:07,720
The booking growth is like the 
amount of subscribers and the 

281
00:14:07,720 --> 00:14:10,520
amount of revenue they're 
gaining that's amortized over a 

282
00:14:10,520 --> 00:14:12,480
year. 
So way to think of this is right

283
00:14:12,480 --> 00:14:16,160
now the revenue that Duolingo's 
receiving this quarter is 

284
00:14:16,160 --> 00:14:19,480
bookings they got last year, 
meaning that the bookings they 

285
00:14:19,480 --> 00:14:22,720
get this year is going to be the
revenue they receive next year. 

286
00:14:22,720 --> 00:14:25,320
So bookings are a preview of the
future. 

287
00:14:25,440 --> 00:14:28,960
And the preview of the future 
shows revenue slowing down when 

288
00:14:28,960 --> 00:14:31,040
a company's price. 
At a premium multiple and 

289
00:14:31,040 --> 00:14:35,040
revenue slows down further than 
expected you get stock prices re

290
00:14:35,040 --> 00:14:36,920
rated. 
So that is the single reason the

291
00:14:36,920 --> 00:14:39,440
stock is down today. 
It is that booking number. 

292
00:14:39,880 --> 00:14:41,920
Now if we look at other. 
Things, I think there's actually

293
00:14:41,920 --> 00:14:44,840
a lot of positives in this 
report and I want to go over a 

294
00:14:44,840 --> 00:14:47,120
handful of them here. 
If we look at the overall 

295
00:14:47,120 --> 00:14:49,960
subscription revenue of the 
company, it is growing 

296
00:14:49,960 --> 00:14:52,480
incredibly fast. 
In fact, the subscription 

297
00:14:52,480 --> 00:14:56,080
revenue grew by 45%. 
Subscription revenue makes up 

298
00:14:56,080 --> 00:14:58,840
around 90% of their total 
revenue because they are a 

299
00:14:58,840 --> 00:15:01,840
subscription based company. 
What I see here with this most 

300
00:15:01,840 --> 00:15:05,000
recent quarter is incredible 
economics. 

301
00:15:05,000 --> 00:15:08,080
You have a company that is 
growing the subscription base 

302
00:15:08,080 --> 00:15:11,080
over time. 
These users are also falling in 

303
00:15:11,080 --> 00:15:13,680
love with the product, using it 
every single day, and we see 

304
00:15:13,680 --> 00:15:16,600
that in the other numbers. 
For example, we have the monthly

305
00:15:16,600 --> 00:15:20,000
active users. 
This is a big scary point just a

306
00:15:20,080 --> 00:15:23,440
1/4 ago. 
Remember, a big problem with 

307
00:15:23,440 --> 00:15:27,000
Duolingo 1/4 ago was that their 
monthly active users actually 

308
00:15:27,000 --> 00:15:29,000
declined. 
It declined? 

309
00:15:29,320 --> 00:15:32,280
Oh no, everybody was concerned 
about the monthly active users 

310
00:15:32,280 --> 00:15:35,080
going down. 
Will it ever grow again? 

311
00:15:35,400 --> 00:15:38,960
Was this because AI is eating 
away at Duolingo's mode? 

312
00:15:39,360 --> 00:15:42,200
Was this because Google 
Translate is now stealing 

313
00:15:42,200 --> 00:15:43,920
customers? 
Will this quarter prove that 

314
00:15:43,920 --> 00:15:46,520
wrong? 
It continued to grow even past 

315
00:15:46,520 --> 00:15:48,960
where it was in Q1. 
The growth of the monthly active

316
00:15:48,960 --> 00:15:53,800
users is up 20% year over year 
and now they have 135 million 

317
00:15:53,800 --> 00:15:56,720
monthly active users. 
So I'm personally very happy to 

318
00:15:56,720 --> 00:15:58,800
see this continuation of this 
trend. 

319
00:15:59,120 --> 00:16:02,040
I thought that it would continue
back upwards, but there was no 

320
00:16:02,040 --> 00:16:04,280
guarantee. 
There was a chance that the 

321
00:16:04,280 --> 00:16:06,920
monthly active users could come 
in below where it was last 

322
00:16:06,920 --> 00:16:09,240
quarter, that it could continue 
on its decline. 

323
00:16:09,560 --> 00:16:11,800
And we don't see that. 
So that's good news for the 

324
00:16:11,800 --> 00:16:14,280
Duolingo shareholder. 
Then we have the daily active 

325
00:16:14,280 --> 00:16:15,960
users. 
These are people that log on and

326
00:16:15,960 --> 00:16:19,160
do a lesson every single day, 
every day of the month, the 

327
00:16:19,160 --> 00:16:21,120
entire quarter. 
We have it right here. 

328
00:16:21,440 --> 00:16:24,840
It's now past 50 million daily 
active users. 

329
00:16:25,200 --> 00:16:28,880
We look at this and it went from
47.7 to 50.5. 

330
00:16:29,000 --> 00:16:31,920
Now this level of engagement 
having 50 + 1,000,000 daily 

331
00:16:31,920 --> 00:16:35,560
active users surpasses many top 
social media companies. 

332
00:16:35,840 --> 00:16:39,800
A lot of them do not have 50 + 
1,000,000 daily active users. 

333
00:16:40,200 --> 00:16:41,760
So I like seeing this growth as 
well. 

334
00:16:42,040 --> 00:16:45,200
We see the paid subscribers. 
The paid subscribers also grew 

335
00:16:45,200 --> 00:16:48,960
by 34% year over year. 
Now they have 11.5 million, 

336
00:16:49,160 --> 00:16:51,920
that's a bump up from 10.9 
million the quarter before. 

337
00:16:52,200 --> 00:16:55,400
We see continued growth, all the
charts going up into the right. 

338
00:16:55,720 --> 00:16:57,680
So that's what we see with 
Duolingo, all of these. 

339
00:16:57,680 --> 00:16:59,440
Charts are moving in the right 
direction. 

340
00:16:59,720 --> 00:17:02,120
One thing that didn't move as 
much as investors may have 

341
00:17:02,120 --> 00:17:05,640
expected is the paid 
subscription penetration, but 

342
00:17:05,640 --> 00:17:08,280
that is for specific reasons. 
The management noted that 

343
00:17:08,280 --> 00:17:10,480
they're not focusing on that 
right now. 

344
00:17:10,599 --> 00:17:13,160
And this is part of the concern 
of this quarter. 

345
00:17:13,400 --> 00:17:17,319
Management basically said that 
their main focus has shifted. 

346
00:17:17,680 --> 00:17:21,480
It's shifted away from turning 
the screws of monetization and 

347
00:17:21,480 --> 00:17:25,160
making more revenue to now going
for a big opportunity. 

348
00:17:25,520 --> 00:17:29,800
And the CEO highlighted over and
over again the opportunity that 

349
00:17:29,800 --> 00:17:32,320
they're going for. 
I want to play some clips of the

350
00:17:32,360 --> 00:17:35,400
audio just from this most 
previous earnings call of Lewis,

351
00:17:35,400 --> 00:17:38,160
the CEO of the company, talking 
about the opportunity he sees 

352
00:17:38,160 --> 00:17:40,560
ahead with education. 
Yeah. 

353
00:17:40,560 --> 00:17:44,120
I mean, look, we're like, like 
you said and like I said in the 

354
00:17:44,120 --> 00:17:47,760
shareholder letter, there's 
there's a huge opportunity right

355
00:17:47,760 --> 00:17:50,160
now. 
We see a huge opportunity over 

356
00:17:50,160 --> 00:17:52,560
the next few years. 
Education and the way people 

357
00:17:52,560 --> 00:17:55,520
learn are they're going to 
change fundamentally. 

358
00:17:55,960 --> 00:18:00,200
And, and it's because of AI and 
also because of AI, we see we 

359
00:18:00,200 --> 00:18:04,320
have line of sight now to create
an app that can teach really, 

360
00:18:04,320 --> 00:18:06,360
really well, much better than 
anything that humanity has seen 

361
00:18:06,360 --> 00:18:10,600
before, as good as a, as a human
tutor, but that is also more 

362
00:18:10,600 --> 00:18:13,200
engaging. 
And if we're able to do that, 

363
00:18:13,520 --> 00:18:16,200
you know, right now we have, I 
don't know, we just posted 135 

364
00:18:16,200 --> 00:18:19,440
million monthly active users. 
If we're able to do an app that 

365
00:18:19,440 --> 00:18:22,200
teaches just that well, way, 
much, much better than we have 

366
00:18:22,200 --> 00:18:24,480
now, we would be talking about 
billions of users that we have. 

367
00:18:24,480 --> 00:18:26,120
And that's what we want to shoot
for here. 

368
00:18:26,640 --> 00:18:30,440
So This is why we are, we are 
investing in the long term. 

369
00:18:30,920 --> 00:18:33,040
And, and what that look like, 
looks like is that we are 

370
00:18:33,040 --> 00:18:35,760
putting relative, more relative 
investment in things like 

371
00:18:35,760 --> 00:18:38,200
teaching better, which, you 
know, teaching better. 

372
00:18:38,640 --> 00:18:42,120
If we teach better, what that 
does is that that helps user 

373
00:18:42,120 --> 00:18:45,440
growth, but there's a lag, you 
know, just whenever you improve 

374
00:18:45,440 --> 00:18:48,400
your courses, users do grow, but
it takes a while for that to 

375
00:18:48,400 --> 00:18:50,800
happen. 
And then user growth, there's a 

376
00:18:50,800 --> 00:18:53,720
lag to get to monetization 
because people take some time to

377
00:18:53,720 --> 00:18:55,880
subscribe. 
So this is kind of a long term 

378
00:18:55,880 --> 00:18:58,880
thing, but we're, we're, we're, 
we're very bullish on this and 

379
00:18:58,880 --> 00:19:00,640
This is why we're, we're, we're 
doing that. 

380
00:19:00,920 --> 00:19:04,160
Talks about how they're in the 
low 100 million users and his 

381
00:19:04,160 --> 00:19:06,200
ambitions are to get to billions
of users. 

382
00:19:06,520 --> 00:19:09,360
And he mentions this opportunity
again throughout the call 

383
00:19:09,360 --> 00:19:11,160
multiple times. 
I want to highlight one more 

384
00:19:11,160 --> 00:19:14,240
time where he talks about this. 
As to why now this, I mean it's 

385
00:19:14,240 --> 00:19:16,320
a great question. 
The reality is that over the 

386
00:19:16,320 --> 00:19:22,120
last couple of years, it has 
just become progressively clear 

387
00:19:22,120 --> 00:19:25,320
and clear that we are in a 
unique point in time, 

388
00:19:25,360 --> 00:19:28,520
particularly with education in 
terms of how education is going 

389
00:19:28,520 --> 00:19:30,840
to happen in the world and also 
how well we can teach a dual 

390
00:19:30,920 --> 00:19:33,200
single. 
We just see it in our own 

391
00:19:33,200 --> 00:19:37,080
metrics in how fast we can put 
out content with things like 

392
00:19:37,080 --> 00:19:39,560
video call. 
Do we just see how much it is 

393
00:19:39,560 --> 00:19:43,160
improving every month. 
And so that just kind of has 

394
00:19:43,160 --> 00:19:46,560
been coming for a while. 
And what has happened is that 

395
00:19:46,560 --> 00:19:51,000
over the last month or two, I've
really rallied the company 

396
00:19:51,000 --> 00:19:53,840
towards this, this shift. 
The CEO has come to the 

397
00:19:53,840 --> 00:19:56,800
conclusion that we're at a very 
unique moment in time where the 

398
00:19:56,840 --> 00:19:59,560
landscape of education is 
shifting dramatically. 

399
00:19:59,640 --> 00:20:03,480
He has this big opportunity to 
grow into this category of 

400
00:20:03,480 --> 00:20:07,520
making Duolingo the go to 
biggest platform in the world 

401
00:20:07,520 --> 00:20:10,400
for education. 
And they're trying to direct the

402
00:20:10,400 --> 00:20:13,800
company more in that direction, 
focus on getting more users, 

403
00:20:14,040 --> 00:20:17,520
making them more engaged, focus 
on expanding the content slate 

404
00:20:17,560 --> 00:20:20,480
and better teaching. 
He highlights Teaching better 

405
00:20:20,680 --> 00:20:22,440
multiple times throughout this 
call. 

406
00:20:22,760 --> 00:20:26,000
They're putting a little bit 
less emphasis on converting 

407
00:20:26,000 --> 00:20:28,960
users from the free account to 
the paid account, making it so 

408
00:20:28,960 --> 00:20:31,040
that they can price things a 
little bit higher. 

409
00:20:31,360 --> 00:20:34,120
That's not going to be something
that they never do, but it's 

410
00:20:34,120 --> 00:20:37,560
just less of their company's 
resources and intent and focus. 

411
00:20:38,000 --> 00:20:40,800
So that is the the gear change. 
That's the opportunity that this

412
00:20:40,800 --> 00:20:43,120
company sees. 
And when you look at this, you 

413
00:20:43,120 --> 00:20:46,000
can take it two ways. 
Many people on Wall Street will 

414
00:20:46,000 --> 00:20:47,640
say, well, that just means that 
we're going to get less 

415
00:20:47,640 --> 00:20:51,040
bookings, less subscriptions 
over the next year, which means 

416
00:20:51,040 --> 00:20:53,440
revenue won't be as high over 
the next year because they make 

417
00:20:53,440 --> 00:20:57,320
money through those bookings. 
But that's not the only thing 

418
00:20:57,320 --> 00:20:59,120
he's saying. 
He's saying part of this is a 

419
00:20:59,120 --> 00:21:02,400
deliberate choice. 
If Duolingo wanted to, they 

420
00:21:02,400 --> 00:21:04,280
could make bookings go through 
the roof. 

421
00:21:04,800 --> 00:21:07,040
They could make it grow by 50% 
next quarter. 

422
00:21:07,240 --> 00:21:09,800
They really could if they wanted
to, but that would be at the 

423
00:21:09,800 --> 00:21:12,120
long term detriment of the 
company. 

424
00:21:12,520 --> 00:21:15,240
And he explains how they 
literally have these mechanisms 

425
00:21:15,240 --> 00:21:18,640
to determine how much they 
convert or how much they don't 

426
00:21:18,640 --> 00:21:21,560
convert users from the free 
tears to the paid tears. 

427
00:21:22,080 --> 00:21:25,000
They determine that they can do 
it through all their AB testing.

428
00:21:25,200 --> 00:21:27,160
He highlights very specific 
examples. 

429
00:21:27,480 --> 00:21:29,440
Some experiments improve all 
metrics. 

430
00:21:29,440 --> 00:21:31,640
Great, that's an easy call. 
Just launch it because it 

431
00:21:31,640 --> 00:21:33,160
improves all metrics and that 
happens. 

432
00:21:33,400 --> 00:21:35,920
But there are times when 
experiments improve one metric 

433
00:21:35,920 --> 00:21:39,000
but hurt another. 
I'll give you a a a fictitious 

434
00:21:39,000 --> 00:21:42,880
example. 
If right now a free user, free 

435
00:21:42,880 --> 00:21:46,560
users get 25 energy units at the
beginning of the day and every 

436
00:21:46,560 --> 00:21:48,280
exercise that they do spends 1 
unit. 

437
00:21:48,760 --> 00:21:52,360
If we were to do an experiment 
that decreases that from 25 to 

438
00:21:52,360 --> 00:21:56,280
say 24, that's one fewer unit 
of, of, of energy per day. 

439
00:21:56,720 --> 00:21:59,920
We know that would make us more 
money that it just does because 

440
00:21:59,960 --> 00:22:03,280
more people run out of energy. 
So more people end up, you know,

441
00:22:03,280 --> 00:22:05,560
wanting to pay to subscribe. 
So he has a mechanism right 

442
00:22:05,560 --> 00:22:07,720
there that he knows would up 
their revenue. 

443
00:22:08,200 --> 00:22:09,760
He could just turn it on at any 
point. 

444
00:22:10,200 --> 00:22:13,080
Just make it so that the energy 
units are 24 per day instead of 

445
00:22:13,080 --> 00:22:15,880
25, and they'd convert far more 
people to the paid terror 

446
00:22:15,880 --> 00:22:18,200
because they'd be frustrated 
with running out of energy. 

447
00:22:18,320 --> 00:22:20,040
So why doesn't Duolingo just do 
that? 

448
00:22:20,080 --> 00:22:22,800
Why don't they bump up revenue 
and give Wall Street exactly 

449
00:22:22,800 --> 00:22:26,520
what it wants, more bookings? 
Well, he explains exactly why 

450
00:22:26,520 --> 00:22:28,400
they're not doing that in this 
next part. 

451
00:22:28,760 --> 00:22:31,560
However, we also know that would
decrease daily active users 

452
00:22:31,560 --> 00:22:35,480
because it would frustrate some 
of the users we've always had to

453
00:22:35,480 --> 00:22:38,520
make decisions about, you know, 
different judgement calls about 

454
00:22:38,520 --> 00:22:41,480
this. 
What we mean is that what we the

455
00:22:41,960 --> 00:22:44,680
change that we are doing is that
we are going to be prioritizing 

456
00:22:44,680 --> 00:22:48,160
user growth over monetization in
this type of of judgement call. 

457
00:22:48,160 --> 00:22:52,040
So in the fictitious experiment 
that I just gave you, we would 

458
00:22:52,040 --> 00:22:56,960
not launch that experiment going
from 25 to 24 energy units even 

459
00:22:56,960 --> 00:23:01,640
if it meant, you know, quite a 
bit of bookings gains if it has 

460
00:23:02,320 --> 00:23:03,760
a real hit on daily active 
users. 

461
00:23:03,760 --> 00:23:06,280
So Duolingo has these hundreds 
of experiments they're running 

462
00:23:06,280 --> 00:23:09,480
all the time, testing their 
product on learning outcomes and

463
00:23:09,480 --> 00:23:13,880
behaviors and engagement, their 
user retention and churn, all 

464
00:23:13,880 --> 00:23:16,080
these different things that 
they're constantly tuning and 

465
00:23:16,080 --> 00:23:18,080
turning. 
And what they're saying is with 

466
00:23:18,120 --> 00:23:22,440
all of these tests, they're now 
focusing primarily on user 

467
00:23:22,440 --> 00:23:25,360
growth and user retention. 
They're not focusing quite as 

468
00:23:25,360 --> 00:23:28,000
much on conversion or revenue. 
When you put this in the greater

469
00:23:28,000 --> 00:23:30,800
context of the direction of the 
company, this is a very 

470
00:23:30,800 --> 00:23:34,560
intentional choice, a focus on 
organic growth and big 

471
00:23:34,560 --> 00:23:37,280
opportunities ahead. 
We're later on down the road. 

472
00:23:37,280 --> 00:23:40,240
Once you've gotten the 
opportunity, once you've really 

473
00:23:40,240 --> 00:23:43,240
won, then you can turn the 
screws of monetization. 

474
00:23:43,720 --> 00:23:47,120
That's exactly what Uber did. 
At first, Uber was focused on 

475
00:23:47,120 --> 00:23:49,200
growth and they're highly 
unprofitable business. 

476
00:23:49,200 --> 00:23:51,920
But Uber grew and grew and grew 
to scale. 

477
00:23:51,960 --> 00:23:54,800
They seized the opportunity 
ahead of them and now they're 

478
00:23:54,800 --> 00:23:57,000
highly profitable now that 
they've met scale. 

479
00:23:57,240 --> 00:23:58,880
It was the same thing with 
Netflix. 

480
00:23:58,880 --> 00:24:02,480
Netflix ran free cash flow 
negative so long the analysts, 

481
00:24:02,480 --> 00:24:05,520
many of them were convinced they
could never turn a dime of 

482
00:24:05,520 --> 00:24:08,240
profit. 
Even smart analysts, great ones 

483
00:24:08,280 --> 00:24:11,800
like Aswat Damodoran said 
Netflix is just a a broken 

484
00:24:11,800 --> 00:24:13,840
business model. 
That's what it does. 

485
00:24:13,840 --> 00:24:18,240
When a company focuses on scale 
and opportunity over immediate 

486
00:24:18,240 --> 00:24:20,840
monetization, it can in many 
cases trick investors and 

487
00:24:20,840 --> 00:24:23,560
analysts, and I believe that's 
what's going on right now. 

488
00:24:23,800 --> 00:24:27,560
Duolingo, by the metrics, is a 
globally dominant company. 

489
00:24:28,080 --> 00:24:31,440
You look at any of the metrics 
and it is growing like crazy. 

490
00:24:31,560 --> 00:24:33,960
They have 11 and a half million 
subscribers. 

491
00:24:34,200 --> 00:24:35,880
These people are loving this 
product. 

492
00:24:35,880 --> 00:24:37,240
They're using it every single 
day. 

493
00:24:37,240 --> 00:24:40,080
They're growing quarter after 
quarter, despite all the people 

494
00:24:40,080 --> 00:24:42,640
saying that they would not 
continue growing, that their 

495
00:24:42,640 --> 00:24:44,360
daily active users would go 
down. 

496
00:24:44,560 --> 00:24:47,840
Their monthly active users would
decline because of artificial 

497
00:24:47,840 --> 00:24:52,040
intelligence, because of 
ChatGPT, because of Google 

498
00:24:52,040 --> 00:24:55,720
Translate, because of the Apple 
Airpods with live translation. 

499
00:24:56,240 --> 00:24:57,960
People said the company would 
die. 

500
00:24:58,240 --> 00:25:00,000
They said that the usage would 
go down. 

501
00:25:00,000 --> 00:25:01,600
They said the churn rate would 
go up. 

502
00:25:01,760 --> 00:25:05,680
All user engagement metrics and 
numbers and usage are all going 

503
00:25:05,680 --> 00:25:07,840
up. 
And in terms of the Moat of the 

504
00:25:07,840 --> 00:25:11,680
company, many people are again 
concerned about AI learning and 

505
00:25:11,720 --> 00:25:13,960
AI translation. 
This has been one of the top 

506
00:25:13,960 --> 00:25:16,360
concerns that I've heard about 
Duolingo since the very 

507
00:25:16,360 --> 00:25:20,840
beginning, and in this call, the
CEO addresses this concern head 

508
00:25:20,840 --> 00:25:22,400
on. 
Here's what he says. 

509
00:25:23,040 --> 00:25:25,240
The two things that people say 
about the competitive landscape 

510
00:25:25,240 --> 00:25:28,720
with AI are #1 why would anybody
want to learn a language with 

511
00:25:28,720 --> 00:25:29,880
Duolingo? 
And you can just learn it with 

512
00:25:29,880 --> 00:25:33,680
ChatGPT, OK. 
I, you know, we're not 

513
00:25:33,680 --> 00:25:36,880
particularly worried about that.
You know, the, we've said it 

514
00:25:36,880 --> 00:25:42,280
before, the main thing that that
we do really well, not only do 

515
00:25:42,280 --> 00:25:44,560
we teach well, but the main 
thing that we do really well is 

516
00:25:44,560 --> 00:25:46,800
keep people engaged. 
And in order to learn a 

517
00:25:46,800 --> 00:25:49,880
language, you need to be engaged
for years. 

518
00:25:49,880 --> 00:25:52,600
Really takes years to learn a 
language coming every day. 

519
00:25:52,920 --> 00:25:55,120
And we need to keep you engaged 
actually doing it. 

520
00:25:55,120 --> 00:25:58,160
And not only that, we also need 
to have curriculum for years for

521
00:25:58,160 --> 00:26:00,640
you to do that. 
So, you know, with ChatGPT, you 

522
00:26:00,640 --> 00:26:02,720
can go there and you can ask it 
to teach you a few words here 

523
00:26:02,720 --> 00:26:05,040
and there, but you know, it's 
not like you can have really 

524
00:26:05,040 --> 00:26:08,640
curriculum for years that that, 
that teach that. 

525
00:26:08,640 --> 00:26:11,000
So we're not particularly 
worried about that aspect. 

526
00:26:11,400 --> 00:26:13,360
And then the other thing that 
people, you know, have said that

527
00:26:13,360 --> 00:26:15,800
they're worried about is, oh, 
well, nobody's going to want to 

528
00:26:15,800 --> 00:26:19,000
learn a language because, you 
know, the, we're going to have 

529
00:26:19,000 --> 00:26:24,200
simultaneous language 
translation and OK, also not 

530
00:26:24,200 --> 00:26:28,920
worried about that. 
You know, I, I believe in 100% 

531
00:26:29,000 --> 00:26:32,800
of the Google IO conferences 
over the last 10 years, they 

532
00:26:32,800 --> 00:26:36,280
have showcased simultaneous 
language translation. 

533
00:26:36,280 --> 00:26:38,440
They do it every single year and
it's good, it works. 

534
00:26:38,920 --> 00:26:41,040
But this has been happening for 
the last 10 years and we have 

535
00:26:41,040 --> 00:26:43,160
not seen the decide to learn a 
language go down at all. 

536
00:26:43,160 --> 00:26:46,320
In fact, it has come up. 
And I think the biggest reason 

537
00:26:46,320 --> 00:26:49,320
for that is because if you look 
at our users, they fall into two

538
00:26:49,320 --> 00:26:52,560
big categories. 
One big bucket is people who are

539
00:26:52,560 --> 00:26:54,920
learning a language as a hobby. 
It kind of doesn't matter 

540
00:26:54,920 --> 00:26:56,760
whether a computer can do that 
because they're the same with 

541
00:26:56,760 --> 00:26:58,680
chess. 
By the way, computers are way 

542
00:26:58,680 --> 00:27:00,960
better than humans with chess. 
But still, you know, we have 

543
00:27:00,960 --> 00:27:02,240
millions of people wanting to 
learn chess. 

544
00:27:02,240 --> 00:27:03,640
That's so it doesn't matter if 
it's a hobby. 

545
00:27:03,840 --> 00:27:06,080
The other big group of people 
that are learning a language 

546
00:27:06,080 --> 00:27:08,240
with us are people who are 
learning English and they 

547
00:27:08,240 --> 00:27:10,880
actually want to learn English 
Like that is, you know, for 

548
00:27:10,880 --> 00:27:13,160
them, you know, being able to 
have like a phone that they have

549
00:27:13,160 --> 00:27:15,240
to hold out. 
It just kind of that's not what 

550
00:27:15,240 --> 00:27:17,000
they what they want to do. 
So we just, we're not 

551
00:27:17,000 --> 00:27:20,640
particularly worried about the 
that it just so happens that 

552
00:27:21,120 --> 00:27:23,080
people like to tweet about that.
We're not worried about it. 

553
00:27:23,440 --> 00:27:26,960
He highlights the distinction 
between Duolingo and a ChatGPT. 

554
00:27:27,240 --> 00:27:30,480
Although you can practice the 
language on ChatGPT, continuing 

555
00:27:30,480 --> 00:27:33,840
to be motivated for years on end
every single day is what 

556
00:27:33,840 --> 00:27:36,880
Duolingo specializes in, and 
these other companies have not 

557
00:27:36,880 --> 00:27:40,040
done nearly the user behavior 
testing to have that level of 

558
00:27:40,040 --> 00:27:41,960
engagement. 
The next thing is a live 

559
00:27:41,960 --> 00:27:45,480
translation, which he accurately
says is not a motivation for 

560
00:27:45,480 --> 00:27:47,920
people to learn languages. 
People don't learn languages 

561
00:27:47,920 --> 00:27:50,840
because of a lack of live 
translation, especially many 

562
00:27:50,840 --> 00:27:53,400
people that are learning 
languages for job opportunities 

563
00:27:53,400 --> 00:27:55,800
or for cultural reasons or for 
hobbies. 

564
00:27:56,080 --> 00:27:58,720
Just like learning chess where 
there's computers better than 

565
00:27:58,720 --> 00:28:01,720
you at chess, learning a 
language in many cases is a 

566
00:28:01,720 --> 00:28:03,760
hobby for people. 
And I agree with this 

567
00:28:03,760 --> 00:28:05,400
assessment. 
I think it's an honest 

568
00:28:05,400 --> 00:28:08,480
assessment of the differences 
between Duolingo and just some 

569
00:28:08,600 --> 00:28:10,840
AI learning app. 
Now Lewis goes on in this call, 

570
00:28:10,840 --> 00:28:12,920
outlining all the different 
things that they're doing for 

571
00:28:12,920 --> 00:28:15,880
the future, improving their 
teaching, adding more courses, 

572
00:28:15,880 --> 00:28:18,320
making it more engaging, making 
it so that they're adding more 

573
00:28:18,320 --> 00:28:20,880
content to existing courses so 
they can teach. 

574
00:28:20,880 --> 00:28:23,720
Languages to a higher level and 
so on and so forth. 

575
00:28:24,000 --> 00:28:26,360
In the chess course, for 
example, they're making it so 

576
00:28:26,360 --> 00:28:28,160
that you can now have player 
versus player. 

577
00:28:28,320 --> 00:28:31,520
Half of iOS users have that. 
They say that chess is in the 

578
00:28:31,520 --> 00:28:34,720
millions of users already. 
It has retention rates better 

579
00:28:34,720 --> 00:28:37,520
than their language learning. 
So they are growing a new pass 

580
00:28:37,520 --> 00:28:41,160
with higher levels of activity. 
But overall, the big thing that 

581
00:28:41,160 --> 00:28:44,040
I want to highlight with 
Duolingo and I think the the 

582
00:28:44,040 --> 00:28:46,720
most important thing is I 
noticed something with this 

583
00:28:46,720 --> 00:28:49,960
company in particular and that 
is an investors do what 

584
00:28:49,960 --> 00:28:53,000
investors end up doing for every
situation like this, which I 

585
00:28:53,000 --> 00:28:55,640
think is a mistake. 
They let the stock price 

586
00:28:55,640 --> 00:29:00,160
movement inform them of their 
opinion on the stock, meaning 

587
00:29:00,680 --> 00:29:02,480
they don't look at the 
fundamentals, they don't look at

588
00:29:02,480 --> 00:29:05,560
the the growth pass in the 
future, revenue expectations or 

589
00:29:05,560 --> 00:29:07,080
anything like that. 
They don't look at the 

590
00:29:07,080 --> 00:29:09,240
valuations. 
They simply look at a stock 

591
00:29:09,240 --> 00:29:13,920
price going up or going down and
they say that is what my opinion

592
00:29:13,920 --> 00:29:16,120
is. 
If the stock went down, there 

593
00:29:16,120 --> 00:29:19,240
must have been a reason why Wall
Street is pricing at lower. 

594
00:29:19,520 --> 00:29:21,600
That means that the stock is 
doing poorly. 

595
00:29:22,360 --> 00:29:25,600
That's what I see a lot on 
Twitter, on YouTube comments all

596
00:29:25,600 --> 00:29:28,400
across X. 
I see people letting the stock 

597
00:29:28,400 --> 00:29:31,440
price inform them of their 
opinion on the stock. 

598
00:29:31,640 --> 00:29:33,880
For example. 
I believe in an alternate world,

599
00:29:34,320 --> 00:29:37,360
if you had this result and the 
stock price for whatever. 

600
00:29:37,360 --> 00:29:42,120
Reason went up 10%, but nothing 
changed, not the bookings, not 

601
00:29:42,120 --> 00:29:43,880
the growth rate, none of these 
metrics. 

602
00:29:44,320 --> 00:29:47,520
I believe that most investors 
would look at this company and 

603
00:29:47,520 --> 00:29:51,040
say this was a great quarter. 
The stock should probably be up 

604
00:29:51,040 --> 00:29:53,680
a little bit and look, Wall 
Street is pricing it up. 

605
00:29:53,680 --> 00:29:55,280
So it must have been a great 
quarter. 

606
00:29:55,920 --> 00:29:58,800
That's the influence, the 
impression that the stock price 

607
00:29:58,800 --> 00:30:00,600
leaves on you. 
And I think that this is a 

608
00:30:00,600 --> 00:30:03,800
dangerous way to invest. 
After all, if you let the stock 

609
00:30:03,800 --> 00:30:06,800
price dictate your impressions 
of a company, if you let the 

610
00:30:06,800 --> 00:30:09,920
movements and the volatility 
tell you how to feel about a 

611
00:30:09,920 --> 00:30:13,600
company, then you would not have
bought Netflix when it fell 75%.

612
00:30:14,000 --> 00:30:15,920
You would have sold out because 
the panic. 

613
00:30:16,200 --> 00:30:20,040
It really looked bad according 
to the stock price, even though 

614
00:30:20,040 --> 00:30:22,560
at the time we can look at the 
real damage that happened to 

615
00:30:22,560 --> 00:30:24,440
Netflix. 
Let's go and take a look at how 

616
00:30:24,440 --> 00:30:28,080
bad things really were when the 
stock price dropped 75%. 

617
00:30:28,480 --> 00:30:31,400
We have Netflix here, we have 
total subscribers. 

618
00:30:31,480 --> 00:30:33,840
The stock price dropped 75% 
right there. 

619
00:30:34,520 --> 00:30:38,200
That was it because this 
quarter, right there was 

620
00:30:38,200 --> 00:30:43,400
slightly less than that 175% 
decrease in stock price, total 

621
00:30:43,400 --> 00:30:46,560
obliteration, all because of 
those two quarters. 

622
00:30:47,280 --> 00:30:50,600
Now, Wall Street said that 
Netflix was basically worth 

623
00:30:50,600 --> 00:30:53,240
nothing because the stock was 
never going to grow again. 

624
00:30:53,640 --> 00:30:55,800
They didn't listen to the 
management, they didn't listen 

625
00:30:55,800 --> 00:30:57,360
to the password crackdown 
narrative. 

626
00:30:57,800 --> 00:31:01,080
They didn't listen to any of the
the long term thesis or thought 

627
00:31:01,080 --> 00:31:03,400
process behind what the 
company's actually doing. 

628
00:31:03,840 --> 00:31:05,920
What Wall Street thought was 
that this company was highly 

629
00:31:05,920 --> 00:31:08,640
rated because of fast growth. 
The company is now not growing 

630
00:31:08,640 --> 00:31:10,400
as fast, so the stock needs to 
come down. 

631
00:31:10,800 --> 00:31:12,440
That's the mechanics of the 
market. 

632
00:31:12,840 --> 00:31:16,480
But if you let the market inform
you on how to feel about a 

633
00:31:16,480 --> 00:31:18,640
company, you'd miss out on 
Netflix. 

634
00:31:19,040 --> 00:31:21,480
And there's plenty more examples
where this came from. 

635
00:31:21,480 --> 00:31:24,960
In 2022, Amazon was trading at 
$80. 

636
00:31:24,960 --> 00:31:29,680
Per share right there, $86 per 
share now Amazon trades. 

637
00:31:30,080 --> 00:31:34,480
At $240 per share, so $80.00 to 
240. 

638
00:31:34,640 --> 00:31:37,360
What happened in 2022? 
Well, of course it was because 

639
00:31:37,360 --> 00:31:40,560
they're investing in CapEx for 
their retail growth and that was

640
00:31:40,560 --> 00:31:43,160
expensive and it caused the free
cash flow to go down a lot. 

641
00:31:43,560 --> 00:31:46,960
Investors in Wall Street looked 
at that and they said, Oh no, 

642
00:31:46,960 --> 00:31:49,120
we're not going to make as much 
money over the next year. 

643
00:31:49,280 --> 00:31:52,360
We need to abandon the stock. 
Investors that looked at this as

644
00:31:52,360 --> 00:31:54,800
an opportunity of a company 
investing in its long term 

645
00:31:54,800 --> 00:31:58,360
future that's prioritizing 
lifetime value of customers and 

646
00:31:58,360 --> 00:32:01,760
expansion over short term 
profits made immense gains in 

647
00:32:01,760 --> 00:32:04,760
that stock. 
I bought Amazon very close to 

648
00:32:04,760 --> 00:32:08,160
$80 per share. 
I bought it under $100 per share

649
00:32:08,440 --> 00:32:10,600
over and over again. 
And that's the reason why that's

650
00:32:10,600 --> 00:32:13,120
such a big winner in the 
portfolio is because I didn't 

651
00:32:13,120 --> 00:32:16,280
let them market dictate my 
thoughts on the company. 

652
00:32:16,840 --> 00:32:18,880
And again, these examples can go
on and on. 

653
00:32:18,880 --> 00:32:22,320
There's so many stocks that drop
down for short term reasons that

654
00:32:22,320 --> 00:32:24,960
if you let the stock price 
dictate how you feel about the 

655
00:32:24,960 --> 00:32:27,680
company, you're going to be 
misled and you could potentially

656
00:32:27,680 --> 00:32:30,400
miss out on huge gains. 
And on this point, I want to 

657
00:32:30,400 --> 00:32:32,080
highlight a story from Jeff 
Bezos. 

658
00:32:32,080 --> 00:32:35,760
This is when Amazon stock price 
crashed by around 90%. 

659
00:32:35,840 --> 00:32:42,480
Amazon's stock in a very short 
period of time went from $113 a 

660
00:32:42,480 --> 00:32:47,080
share to $6 a share was very 
concerning and shareholders were

661
00:32:47,080 --> 00:32:49,160
upset. 
Employees were nervous. 

662
00:32:50,200 --> 00:32:53,320
We had all of our employee base,
their parents were all calling 

663
00:32:53,320 --> 00:32:55,320
our employees and saying are you
OK? 

664
00:32:55,720 --> 00:32:57,840
You know, this was the 
environment of great 

665
00:32:57,840 --> 00:33:01,000
nervousness. 
But I looked at the numbers in 

666
00:33:01,000 --> 00:33:06,640
the business and every month as 
the stock price went from 113 to

667
00:33:06,640 --> 00:33:12,600
6, the a number of customers 
went up every month, our gross 

668
00:33:12,600 --> 00:33:16,840
profits went up every month, our
operating expense, we were still

669
00:33:16,840 --> 00:33:20,520
in a loss position, but our our 
losses as a percentage of sales 

670
00:33:20,520 --> 00:33:24,160
went down every month. 
Every single business metric, 

671
00:33:24,440 --> 00:33:28,560
new customers, customer repeat 
purchases, everything that we 

672
00:33:28,560 --> 00:33:31,640
were monitoring through that 
entire period kept getting 

673
00:33:31,640 --> 00:33:34,640
better. 
And so this that's one 

674
00:33:34,640 --> 00:33:39,800
observation about bubbles in 
general, the fundamentals can be

675
00:33:39,800 --> 00:33:42,280
disconnected, the fundamentals 
of the business. 

676
00:33:42,280 --> 00:33:45,320
And of course, as entrepreneurs,
you're focused on the 

677
00:33:45,320 --> 00:33:48,400
fundamentals of the business, 
the stock prices and output and 

678
00:33:48,400 --> 00:33:50,480
ultimate output. 
Did you actually have very 

679
00:33:50,480 --> 00:33:52,640
little control over Benjamin 
Graham? 

680
00:33:52,640 --> 00:33:57,040
The great investor is famous for
saying in the short term, stock 

681
00:33:57,040 --> 00:33:59,960
market is a voting machine. 
In the long term, it's a 

682
00:33:59,960 --> 00:34:03,280
weighing machine. 
And so as founders and 

683
00:34:03,280 --> 00:34:07,080
entrepreneurs and business 
people, our job is to build a 

684
00:34:07,080 --> 00:34:09,639
heavy company. 
We want to build a company that 

685
00:34:09,639 --> 00:34:13,719
when it is weighed, it is a very
heavy company. 

686
00:34:13,880 --> 00:34:18,000
The goal for entrepreneurs like 
Lewis, the CEO and founder of 

687
00:34:18,000 --> 00:34:20,600
Duolingo, is to forget about the
stock price. 

688
00:34:20,639 --> 00:34:22,920
You don't have any control over 
that, and that's the long term 

689
00:34:22,920 --> 00:34:25,239
output of what you do have 
control over, which is the 

690
00:34:25,239 --> 00:34:27,960
fundamentals making a heavy 
company. 

691
00:34:28,000 --> 00:34:30,960
Now, I'm not suggesting that 
Duolingo's the next Amazon, I 

692
00:34:30,960 --> 00:34:32,719
don't believe that. 
I'm not suggesting it. 

693
00:34:33,159 --> 00:34:35,480
But I do believe there's an 
opportunity here where Duolingo 

694
00:34:35,480 --> 00:34:38,760
could still turn out to be a 
pretty heavy company, one that 

695
00:34:38,760 --> 00:34:42,120
has a massive amount of users, a
really well liked company in a 

696
00:34:42,120 --> 00:34:45,040
very relevant industry. 
We've seen these type of similar

697
00:34:45,040 --> 00:34:48,199
companies play out, these large 
platform companies with hundreds

698
00:34:48,199 --> 00:34:51,159
of millions of users that end up
growing to large established 

699
00:34:51,159 --> 00:34:54,280
companies that in the end become
very heavy companies. 

700
00:34:54,639 --> 00:34:57,080
We've seen it with Spotify. 
That was a company that many 

701
00:34:57,080 --> 00:34:59,160
people are worried about the 
music labels and look how 

702
00:34:59,160 --> 00:35:00,800
wonderful of an investment 
that's turned out. 

703
00:35:01,040 --> 00:35:04,280
We've seen it with Netflix, 
we've seen it with DoorDash, 

704
00:35:04,280 --> 00:35:06,600
we've seen it with Uber. 
All of these companies were 

705
00:35:06,600 --> 00:35:08,880
money losing. 
All of them have very volatile 

706
00:35:08,880 --> 00:35:10,880
histories. 
All of them have time periods 

707
00:35:10,880 --> 00:35:13,880
where investors are super 
bullish or super bearish on the 

708
00:35:13,880 --> 00:35:16,640
company. 
And overtime, what matters is 

709
00:35:16,640 --> 00:35:19,720
the weight of the company. 
Is Duolingo going to become a 

710
00:35:19,760 --> 00:35:22,640
heavy company? 
Will it become a big, large, 

711
00:35:22,640 --> 00:35:24,880
established, profitable company 
or not? 

712
00:35:25,240 --> 00:35:27,320
If you don't believe it will, 
then don't buy the stock. 

713
00:35:27,600 --> 00:35:29,960
If you believe it might or 
there's a good chance of it, 

714
00:35:30,440 --> 00:35:31,600
then it might be worth biting 
at. 

715
00:35:31,680 --> 00:35:34,240
It might be worth 1 to consider.
And in any case, I'd never 

716
00:35:34,240 --> 00:35:36,400
recommend making it your entire 
portfolio. 

717
00:35:36,520 --> 00:35:39,400
I'm not doing that here. 
If Duolingo doesn't work out, 

718
00:35:39,440 --> 00:35:42,640
it'll be a bummer, but it's not 
going to impact my portfolio's 

719
00:35:42,640 --> 00:35:45,720
performance to a massive degree.
But I still believe there's a 

720
00:35:45,720 --> 00:35:49,120
good chance for upside because 
like Jeff Bezos says, I'm 

721
00:35:49,120 --> 00:35:51,640
looking at the fundamentals. 
I'm seeing the metrics go up and

722
00:35:51,640 --> 00:35:54,680
to the right for Duolingo. 
As long as I see that happen, 

723
00:35:55,000 --> 00:35:56,240
I'm not going to sell this 
stock. 

724
00:35:56,240 --> 00:35:59,200
And in fact, I'm a dollar cost 
average and buy a bit more. 

725
00:35:59,720 --> 00:36:00,880
Now let's go to move on to some 
news. 

726
00:36:00,920 --> 00:36:03,480
Now, amongst this big sell off, 
there are a few companies that 

727
00:36:03,480 --> 00:36:05,400
are at least holding up right 
now. 

728
00:36:05,400 --> 00:36:07,800
Google's one of them. 
It's sticking in the green, just

729
00:36:07,800 --> 00:36:11,240
barely teetering in the green, 
despite the fact that the rest 

730
00:36:11,240 --> 00:36:13,160
of the market is selling off 
heavily. 

731
00:36:13,360 --> 00:36:16,080
And the QQQ, the mega caps, are 
selling off even more. 

732
00:36:16,480 --> 00:36:19,880
Why is Google doing so well? 
Because Google has even more 

733
00:36:19,880 --> 00:36:22,120
good news. 
The company said on Tuesday that

734
00:36:22,120 --> 00:36:25,880
the 7th generation of its tensor
processing unit, the TPU is 

735
00:36:25,880 --> 00:36:29,280
called Ironwood, will hit the 
market for public use in the 

736
00:36:29,280 --> 00:36:32,280
coming weeks after it was 
initially introduced in April 

737
00:36:32,280 --> 00:36:35,760
for testing and deployment. 
The chip built in house is 

738
00:36:35,760 --> 00:36:38,840
designed to handle everything 
from training of large models to

739
00:36:38,840 --> 00:36:42,840
powering real time chat bots and
AI agents and connecting up to 

740
00:36:42,840 --> 00:36:48,000
9216 chips in a single pod. 
Google says the new Ironwood TPU

741
00:36:48,000 --> 00:36:51,080
eliminates quote data 
bottlenecks for the most 

742
00:36:51,080 --> 00:36:54,840
demanding models and gives 
customers the ability to run and

743
00:36:54,840 --> 00:36:58,400
scale the largest, most data 
intensive models in existence. 

744
00:36:58,440 --> 00:37:03,160
Now if I was blindfolded and I 
just heard this line, I would 

745
00:37:03,160 --> 00:37:05,680
think this has to come from 
NVIDIA at the very least. 

746
00:37:05,680 --> 00:37:08,040
It might come from AMD. 
They they might say something 

747
00:37:08,040 --> 00:37:11,120
like that, but that's not coming
from NVIDIA or AMD. 

748
00:37:11,400 --> 00:37:14,240
Now it's Google. 
Google is also good. 

749
00:37:14,280 --> 00:37:17,200
They're they're not just good at
YouTube, they're not good at 

750
00:37:17,360 --> 00:37:19,520
robotaxi. 
They're not just good at cloud 

751
00:37:19,520 --> 00:37:21,360
hosting. 
Now they're good at making 

752
00:37:21,360 --> 00:37:25,000
chips, really powerful ones that
in their words can run the most 

753
00:37:25,000 --> 00:37:27,160
data intensive models in 
existence. 

754
00:37:27,160 --> 00:37:29,120
How did Google get this chip so 
good? 

755
00:37:29,280 --> 00:37:31,360
How did they get it so it 
matches performance and 

756
00:37:31,360 --> 00:37:34,240
efficiency of top tier chips? 
Well, like many things that 

757
00:37:34,240 --> 00:37:36,240
Google does, they've been 
working on it for a long time. 

758
00:37:36,360 --> 00:37:39,600
They've just been investors in 
all these projects for decades. 

759
00:37:40,040 --> 00:37:42,520
The TP use have been in works 
for a decade. 

760
00:37:42,880 --> 00:37:46,160
Ironwood, according to Google, 
is more than four times faster 

761
00:37:46,160 --> 00:37:48,880
than its predecessor. 
The AI startup Anthropic plans 

762
00:37:48,880 --> 00:37:52,680
to use up to 1,000,000 of the 
new Tpus to run its clod model. 

763
00:37:52,720 --> 00:37:55,440
If the market wasn't having a 
big panic attack today and 

764
00:37:55,440 --> 00:37:59,120
selling off 2%, Google would be 
up two to 3% on this news. 

765
00:37:59,120 --> 00:38:01,480
There's no doubt about it. 
Now, moving on, we get to our 

766
00:38:01,520 --> 00:38:03,440
fail of the week. 
This is the second fail of the 

767
00:38:03,440 --> 00:38:05,040
week. 
So we're going to have a maybe. 

768
00:38:05,040 --> 00:38:07,280
We're going to have a fail of 
the week on a daily basis, a 

769
00:38:07,280 --> 00:38:10,000
daily fail of the week. 
Don't ask me how that makes 

770
00:38:10,000 --> 00:38:11,680
sense, but that's what this has 
turned into. 

771
00:38:12,000 --> 00:38:15,280
In this case, it's Chipotle. 
Now, Chipotle stock is down a 

772
00:38:15,280 --> 00:38:17,280
lot. 
That in and of itself is not the

773
00:38:17,280 --> 00:38:19,440
fail of the week. 
Many stocks go down for all 

774
00:38:19,440 --> 00:38:22,880
different reasons, but Chipotle 
is down around 50% on the year. 

775
00:38:23,240 --> 00:38:24,880
And it's not just the stock 
price. 

776
00:38:24,880 --> 00:38:28,360
The company's also struggling, 
for example, even though 

777
00:38:28,360 --> 00:38:31,160
Chipotle's opening up more 
locations and they're seeing 

778
00:38:31,160 --> 00:38:35,440
some growth that way, the 
average revenue per location is 

779
00:38:35,440 --> 00:38:38,200
declining and it's been 
declining quarter after quarter.

780
00:38:38,200 --> 00:38:40,960
One of the major problems with 
Chipotle is very clear. 

781
00:38:41,200 --> 00:38:43,680
Anyone that has gone there 
frequently knows about this 

782
00:38:43,680 --> 00:38:45,760
issue. 
It is the fact that going to 

783
00:38:45,760 --> 00:38:48,480
Chipotle to some degree is a bit
of a gamble. 

784
00:38:48,760 --> 00:38:50,720
You don't really know what 
you're going to get. 

785
00:38:50,960 --> 00:38:54,080
It's very inconsistent, and this
is an anecdote from my 

786
00:38:54,080 --> 00:38:56,880
experience, but it's also one 
that's shared amongst millions 

787
00:38:56,880 --> 00:38:59,400
of people. 
We look at viral tweets like 

788
00:38:59,400 --> 00:39:01,440
this. 
This is from Mike from Chipotle 

789
00:39:01,440 --> 00:39:04,480
Tweets. 
He's tweeted that he actually 

790
00:39:04,480 --> 00:39:07,400
did kind of like a a little bit 
of a sting operation on 

791
00:39:07,400 --> 00:39:09,680
Chipotle. 
He said that I ordered these 

792
00:39:09,680 --> 00:39:12,880
burritos 15 minutes apart from 
the same store today. 

793
00:39:13,520 --> 00:39:17,040
The one on the left I ordered in
person and it's twice the size 

794
00:39:17,040 --> 00:39:19,320
as the one on the right which 
was ordered online. 

795
00:39:19,680 --> 00:39:23,760
My order online is always 
significantly smaller every 

796
00:39:23,760 --> 00:39:25,520
time. 
Stop ripping us off. 

797
00:39:25,640 --> 00:39:28,040
Off to the. 
Left we can clearly see the 

798
00:39:28,040 --> 00:39:31,080
burrito is almost twice as big 
as the one on the right. 

799
00:39:31,440 --> 00:39:33,640
The one on the right is like a 
normal sized burrito. 

800
00:39:33,640 --> 00:39:37,160
The one on the left is gigantic.
And again, this is not just Mike

801
00:39:37,720 --> 00:39:40,600
when he tweeted this. 
Everybody said the same thing. 

802
00:39:40,920 --> 00:39:47,520
This has 10 million views, 
144,000 hearts, 7000 retweets. 

803
00:39:47,760 --> 00:39:49,360
This is one of the most viral 
tweets. 

804
00:39:49,360 --> 00:39:53,600
Across Twitter is people saying 
I know this experience. 

805
00:39:53,960 --> 00:39:57,280
I've also gone and ordered 
online and I get ripped off. 

806
00:39:57,400 --> 00:40:00,720
Now we can only speculate why 
the digital ordering and online 

807
00:40:00,720 --> 00:40:03,920
ordering has such smaller 
portion sizes than in person, 

808
00:40:04,480 --> 00:40:06,880
but if I had to guess, I believe
it's because when you go in 

809
00:40:06,880 --> 00:40:09,880
person. 
The employee feels more pressure

810
00:40:09,880 --> 00:40:11,720
to kind of deliver a good 
burrito. 

811
00:40:12,000 --> 00:40:14,520
They see you right there looking
at what they're doing. 

812
00:40:14,920 --> 00:40:17,920
So they at least see some human 
connection when it's just 

813
00:40:17,920 --> 00:40:19,400
digitally. 
They go in the back kitchen, 

814
00:40:19,400 --> 00:40:22,160
they prepare something. 
They don't even have to see you.

815
00:40:22,160 --> 00:40:23,880
They never see you through the 
drive through really. 

816
00:40:24,200 --> 00:40:26,000
So there's not that human 
connection. 

817
00:40:26,160 --> 00:40:28,720
Now, the previous CEO of 
Chipotle noticed that this is a 

818
00:40:28,720 --> 00:40:31,280
problem. 
He even suggested going in 

819
00:40:31,280 --> 00:40:33,520
person. 
And then if you get a smaller 

820
00:40:33,520 --> 00:40:36,240
portion size than what you 
believe you should have, if it's

821
00:40:36,240 --> 00:40:39,360
a kind of a smaller portion size
and what you want, you give the 

822
00:40:39,360 --> 00:40:41,920
employee the nod. 
You give them a nod to get the 

823
00:40:41,920 --> 00:40:44,760
portion size you deserve. 
Here he is talking about that. 

824
00:40:45,360 --> 00:40:47,160
One of these, I think it's great
about Chipotle's. 

825
00:40:47,160 --> 00:40:49,800
If you come into the restaurant 
and you want a little more rice 

826
00:40:49,800 --> 00:40:52,200
or you want a little more 
people, all you got to do is 

827
00:40:52,200 --> 00:40:56,120
kind of like, and usually our 
guys and women give them a 

828
00:40:56,120 --> 00:40:59,080
little more scoop. 
Now, I don't know about you and 

829
00:40:59,160 --> 00:41:02,920
you may think I'm crazy here, 
but I don't believe that the 

830
00:41:02,920 --> 00:41:06,320
customer should be the one 
responsible for making sure 

831
00:41:06,320 --> 00:41:09,680
their burrito is made with the 
proportions that they're paying 

832
00:41:09,680 --> 00:41:11,640
for. 
I think if you just ask for 

833
00:41:11,640 --> 00:41:15,520
something, if you say I want a 
burrito with chicken, then it 

834
00:41:15,520 --> 00:41:17,440
should come with the right 
amount of chicken. 

835
00:41:17,440 --> 00:41:20,360
You shouldn't have to give them 
a nod to say, hey, I really want

836
00:41:20,360 --> 00:41:22,080
the the full amount that I'm 
paying for. 

837
00:41:22,400 --> 00:41:25,160
I don't think that should be the
case and it seems like I'm again

838
00:41:25,160 --> 00:41:27,160
not the only one that feels this
way. 

839
00:41:27,160 --> 00:41:31,360
There are massive amounts of 
posts on this subject with 10s 

840
00:41:31,360 --> 00:41:34,120
of thousands of people, hundreds
of comments all saying the same 

841
00:41:34,120 --> 00:41:37,520
thing, that this company has a 
problem with inconsistent 

842
00:41:37,520 --> 00:41:40,560
portions. 
Chipotle has even been sued for 

843
00:41:40,560 --> 00:41:44,280
inconsistent portion sizes. 
The inconsistent portion sizes 

844
00:41:44,280 --> 00:41:47,520
of Chipotle's food is such a big
deal that one Wells Fargo 

845
00:41:47,520 --> 00:41:50,520
analyst took it upon himself to 
do an in depth study on the 

846
00:41:50,520 --> 00:41:52,960
subject. 
He ordered 100 burritos from all

847
00:41:52,960 --> 00:41:54,920
different locations at all 
different times. 

848
00:41:55,160 --> 00:41:57,960
He had the exact same order 
every single time. 

849
00:41:58,120 --> 00:42:01,880
The bowl weight varied widely. 
The lightest bowl was 3 standard

850
00:42:01,880 --> 00:42:04,760
deviations below the median. 
Meaning that this is not just an

851
00:42:04,760 --> 00:42:07,520
anecdotal experience, this is a 
mathematical certainty. 

852
00:42:07,880 --> 00:42:11,040
Chipotle has wildly varying 
portion sizes with the food that

853
00:42:11,040 --> 00:42:13,880
they give to their customers. 
Management of Chipotle don't 

854
00:42:13,880 --> 00:42:15,480
seem to know how to solve this 
problem. 

855
00:42:15,880 --> 00:42:18,400
They've tried to tell their 
employees, hey, do better, they 

856
00:42:18,400 --> 00:42:21,280
tried to train them better, but 
so far they don't have an 

857
00:42:21,280 --> 00:42:23,400
answer. 
And Chipotle has taken to 

858
00:42:23,400 --> 00:42:26,880
blaming the economy and their 
most recent earnings, saying our

859
00:42:26,880 --> 00:42:29,840
third quarter performance fell 
short of our expectations due to

860
00:42:29,840 --> 00:42:32,080
persistent macroeconomic 
pressures. 

861
00:42:32,120 --> 00:42:35,240
And that certainly is a factor, 
I'll admit, that it plays into 

862
00:42:35,240 --> 00:42:37,960
any restaurant. 
But there's also a big factor 

863
00:42:37,960 --> 00:42:40,600
that you do have control over. 
Even though the CEO does not 

864
00:42:40,600 --> 00:42:43,800
have control over the economy, 
they do have control over how 

865
00:42:43,800 --> 00:42:46,640
they run their restaurant. 
And they could get rid of this 

866
00:42:46,640 --> 00:42:48,800
frustration that many customers 
deal with. 

867
00:42:49,160 --> 00:42:52,400
And luckily for the Chipotle 
management, I have the answer. 

868
00:42:52,760 --> 00:42:56,560
I have the solution. 
This is a a really easy problem 

869
00:42:56,560 --> 00:42:59,400
to solve and I'm going to lay 
out the answer today. 

870
00:42:59,720 --> 00:43:01,840
This will change Chipotle for 
the better. 

871
00:43:02,040 --> 00:43:04,840
When we see this implemented, 
you're going to have a better 

872
00:43:04,840 --> 00:43:07,800
product because your product 
will be completely consistent 

873
00:43:07,840 --> 00:43:09,960
every single time. 
We can take the example of a 

874
00:43:09,960 --> 00:43:12,640
restaurant called Mobetus. 
It's a Hawaiian style 

875
00:43:12,640 --> 00:43:14,680
restaurant. 
It's a really good 1. 

876
00:43:14,680 --> 00:43:16,880
I actually love this place. 
So if you've ever, if you've 

877
00:43:16,880 --> 00:43:18,640
ever been around on Mobetus, go 
try it out. 

878
00:43:18,640 --> 00:43:20,000
If you haven't, I think you'll 
like it. 

879
00:43:20,440 --> 00:43:23,720
We have a guy here, He's doing a
food review like Chipotle. 

880
00:43:23,720 --> 00:43:26,120
This is a restaurant where you 
have all the pictures of the 

881
00:43:26,120 --> 00:43:28,840
food, you have all these 
different orders, and you go up 

882
00:43:28,840 --> 00:43:31,840
in A and you go up and you 
assemble your food in the line. 

883
00:43:31,840 --> 00:43:33,520
So we get to where they prepare 
the food. 

884
00:43:33,520 --> 00:43:36,040
Again, you go down the line, 
they prepare it exactly like 

885
00:43:36,040 --> 00:43:38,880
Chipotle's. 
But there is one notable 

886
00:43:38,880 --> 00:43:42,320
difference, one thing that is 
just different than what 

887
00:43:42,320 --> 00:43:45,480
Chipotle does that makes it so 
at this restaurant, you get 

888
00:43:45,480 --> 00:43:49,880
perfectly consistent portions of
the protein every single time 

889
00:43:49,880 --> 00:43:52,360
you go in. 
Let's look at exhibit one. 

890
00:43:52,560 --> 00:43:57,080
We have it right here. 
I'll outline it in red right 

891
00:43:57,080 --> 00:43:58,280
there. 
We have exhibit one. 

892
00:43:58,400 --> 00:44:01,040
That is a scale. 
That's a food scale. 

893
00:44:01,040 --> 00:44:05,120
What Movedas does is they take 
your plate of food before they 

894
00:44:05,120 --> 00:44:07,760
put any protein in it. 
They put it on the scale. 

895
00:44:07,960 --> 00:44:11,320
They hit a button that zeroes 
out the scale, then they put 

896
00:44:11,320 --> 00:44:15,040
food on to where you have the 
amount of food in weight. 

897
00:44:15,120 --> 00:44:16,960
That is the amount you're paying
for. 

898
00:44:17,400 --> 00:44:19,560
So as a. 
Customer, you see them pick up 

899
00:44:19,560 --> 00:44:22,760
the food, put it in the plate on
the scale, and then they have a 

900
00:44:22,760 --> 00:44:25,520
nice little margin, right? 
It has to be very close, but 

901
00:44:25,520 --> 00:44:27,840
they have a nice little margin 
of the amount of food you paid 

902
00:44:27,840 --> 00:44:30,080
for. 
It doesn't take hardly any 

903
00:44:30,080 --> 00:44:31,800
additional time. 
In fact, it takes probably about

904
00:44:31,800 --> 00:44:34,720
two to three seconds longer. 
But that two to three seconds 

905
00:44:34,720 --> 00:44:37,680
longer ensures that you get the 
correct proportion of food. 

906
00:44:37,920 --> 00:44:40,080
All Chipotle needs to do is add 
the scales. 

907
00:44:40,400 --> 00:44:42,200
That's it. 
They add the scales and they 

908
00:44:42,200 --> 00:44:44,640
figure out one massive problem 
for the business. 

909
00:44:44,680 --> 00:44:47,680
Food scales are cheap, they're 
easy to implement, they're easy 

910
00:44:47,680 --> 00:44:49,760
to train. 
It fixes a massive complaint for

911
00:44:49,760 --> 00:44:51,800
the company. 
It doesn't cost the company much

912
00:44:51,800 --> 00:44:55,400
in CapEx, and their throughput 
or the rate that they can get 

913
00:44:55,400 --> 00:44:57,800
people through the line really 
isn't slowed down that much. 

914
00:44:57,800 --> 00:45:00,760
Maybe 3 to 4 seconds to ensure 
you get a better experience. 

915
00:45:01,280 --> 00:45:04,320
So even though this is the fail 
of the week, it's also ending on

916
00:45:04,320 --> 00:45:07,240
a positive note. 
I'm glad together we could fix 

917
00:45:07,240 --> 00:45:10,200
Chipotle, we could make it a 
better company, and overall, we 

918
00:45:10,200 --> 00:45:13,200
can make that unit volume grow 
again because if you know what 

919
00:45:13,200 --> 00:45:14,960
you're getting, you're going to 
go there more often. 

920
00:45:14,960 --> 00:45:16,480
That's going to be it for this 
episode. 

921
00:45:16,520 --> 00:45:18,240
Hope you enjoyed. 
See you in the next one.