What if AI could tell you which foods will spike your blood sugar?

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
[Noosheen Hashemi] (00:00):
You know.

[Jeana Anderson Cohen] (00:01):
I mean, you never know, honestly. We're recording now, but who cares?
I'm 37.

Okay,

You don't have to tell me how old you are. You can

I'm

if you want

60.

though. Stop it. Okay. I mean,

Fiber,

you've worked a lot

take

of places.

more fiber, stay out of the sun.

You're right. Drink more water. Oh my God. Okay. I'm gonna hit
record. Ryan, please cut all of that. Have you ever seen a small
round sensor on the back of someone's arm? For a long time, those
continuous glucose monitors were only used for monitoring the blood glucose
of those with diabetes. My grandfather had diabetes and he would check

(00:39):
his blood glucose twice a day using a finger prick. I distinctly remember
the sound of the little device. It was like a stapler and the curse
words that followed. So I assumed as I was putting on the freestyle
Libre on the back of my arm, that it would be as painful as the
finger prick. It was not and for two weeks I wore it and dutifully

(01:02):
trained the AI in the January AI app to help it help me Understand
and control my blood glucose. Oh, and by the way, this is a sweat
lives podcast We got goals and I'm Gina Anderson Cohen and joining
me today is Nushim Hashemi CEO and founder of January AI which uses AI
to help manage your glucose and predict the impact of key behaviors

(01:24):
on your body's unique Nushin, thanks for joining me.

Thank you for having me, Gina.

And before we jump in, we start every day at a sweat life by sharing
one good thing. So Nushim, what's good? It can be anything. Nushim, what's
good?

Well, today we got green lighted to do an exploratory work for a very
large food company where we use digital twins to understand the impact
of products they have in development on people's glycemic health. And

(02:03):
so this has the potential to completely transform food discovery using
AI. much like drug discovery has been transformed by using AI. So we've
been talking for a few years about using AI to understand the various mechanisms

(02:27):
of the body, various drugs, compounds, et cetera, and using AI in drug
discovery. And now we're thinking about using AI in food discovery,
meaning even all the possible flavors, all the possible ingredients out in
the world. what combination of ingredients could give you something delicious
that is also good for you.

Ooh, that's exciting. It also gives

Yeah.

us a little mystery to look forward to. When will we know the name
of this big food company?

Oh, maybe in a few weeks, but I think the bigger trend to think about
is what is happening in the world. These numbers just came out two
weeks ago that show that by middle of 21st century, so by 2050, we will
have 1.3 billion people with diabetes globally. And about two and a

(03:18):
half times that number will have pre-diabetes. So you're talking about...
4.5 billion out of 10 billion people having diabetes or pre-diabetes by the
middle of the century, which is less than three decades away. And so this
is a huge, huge crisis. So this isn't like COVID that took some lives.

(03:39):
This is big. This is 4.5 billion out of 10 billion people. And so we
are very passionate about solving this problem, but this problem doesn't
have one solution. It has many. solutions. One of the solutions is the
role that food takes in our lives and the role that packaged foods
take in our lives. And so restructuring packaged foods in order to have

(04:06):
a better blood sugar response is a huge promise that we are extremely excited
about. So this particular company is very progressive, very innovative.
So they want to use generative AI. to inform their product development process.
So they're just in the exploratory phase. So they're just trying to figure out

(04:27):
how might we use generative AI to create foods that are delicious but are
better for you. So we're excited about that exploratory phase and they
just gave us the green light this morning.

So exciting. I chatted you my guests, but we don't have to talk about
it. So

Oh,

my

okay.

good thing, my good thing, I would say, my good thing was my husband
and I, this is so small compared to your big potatoes, good thing,
but my small potatoes, good thing is that my husband and I did a good
job of splitting up the closing shift and the opening shift of

(05:10):
the house. this week. He has been closing it down, wiping down the
counters, doing the dishes before going to bed. I've been opening
up the house, doing the morning stuff, and it feels like a really
good division of labor. Everybody has time to work. Everybody is pulling
their weight, which I love. Shout out to Justin for all. Shout

(05:32):
out

Awesome.

to me, honestly, because he's been doing more than I have for months.
All right, should we talk about January.ai? I'm really excited to
chat about this.

Sure.

Okay, so you, Nushin, have had a storied career in tech. I spent
probably a half hour in your LinkedIn today. What's interesting
about

Yes, I've been

the

a workaholic.

biotech space for you? Yeah, I could tell. And you're on a million
boards, like you've touched everything.

Yeah, so I guess I've done a lot of things. That's what happens when you,
you know, I've lived, I'm very lucky to be very curious and very interested
in the world around me. So I have, I haven't had a government job yet,
but I will, but I've done everything else, from nonprofits to private
sector, volunteering, etc. Being a professional mother. And yeah, so in

(06:30):
terms of
In terms of January,
I mean, there's so many directions to take.
I need to install, install. This is just, can they take this out? No, yes.

Yeah, they could take this out. You want a second?

Okay. Yeah, just start over, please, with me. Sorry.

Okay, perfect. No worries,

So,

no worries.

bye.

We'll take it out. We can edit as much as you want.
Okay, so, Nushin, you've had a storied career in tech. What is interesting
about biotech to you? What pulled you in?

Yeah, so what pulled me in was this promise of prevention. I've talked
about my parents' situation, that's what I was dealing with. My father was
diagnosed with a second cancer eight years after his first cancer,
even though he'd been under the care of oncology for eight years, so they
never tested him for the second cancer. So he was told he was stage

(07:48):
four when he couldn't do anything about it. And that was, I was in the
room when he was told that. And then my mother was misdiagnosed as having
asthma where she has heart failure. And she almost died multiple times
until it was figured out that she actually had heart failure. Anyway,
I was looking, I was interested in, how can we know earlier? How can we know

(08:08):
sooner? This is so, this is so savage. This is so incredible because
my father was a raw vegetarian and he shouldn't have died at 88. I think my
dad could have lived to, you know. you know, 100 years old because he
was just, he took such great care of himself. But I was interested in prevention.
I fell into multiomics and this idea of taking a whole look at your health

(08:34):
as opposed to just one angle of your health, like, oh, I have cholesterol
or my A1C, whatever, just taking, essentially I became interested in
what's called deep multiomic. phenotyping, which is, hey, can we just grab
everything about this person? Can we take their microbiome profile? Can we
look at their genetics? Can we look at their blood tests? Can we look

(08:55):
at their wearables and how they're living? Can we look at their lifestyle?
So I became very interested in this. And then I met Mike Snyder, my co-founder,
and he has type two diabetes. And he was very switched on to the problem
of diabetes in the country. And he said, do you know one out of three people
has pre-diabetes and most of them don't know it? And we need to solve
for this problem. And he and I became partners very quickly after our

(09:20):
very first meeting. And so what's interesting here is I feel that technology
so far, you know, the promise of technology was for productivity, for letting
us to do more, to accomplish more than it was like live richer lives and
be entertained and be, you know, be closer to people, etc. But now I feel

(09:41):
like technology is entering the ultimate field, with more health than before
because health is, in my view, the ultimate wealth. And especially in
this world where I just talked about in 2050, you're going to have
half of the world population almost having prediabetes or diabetes. You're

(10:03):
going to have hundreds of millions of people that are climate refugees.
You're going to have no seafood in the ocean. You know, you're going.
So you. you're going to have a lot of water shortages. So in this world,
I feel that the thing we can do most for people is to help them be healthy

(10:26):
because that corpus of health is wealth for people. So to actually build
generational wealth for people, I feel like you need to build their
health because many people in our country are one sickness away from being
on the street. And I think... For others who have more security, I think

(10:50):
they too can have mental health problems as a result of being sick,
as a result of not living their best lives. All of us are prone to physical
or mental health problems. And I think they keep us from being able to
realize our potential to be the best we can possibly be and to live

(11:12):
our best lives. So I really feel like Of all the philanthropy I've ever
done, of all the great things I've done in the private sector, building the
software industry, I feel like working on health is the most noble goal
for me today. I can't think of another goal bigger. So if I can have an
impact on the way food is made on this planet through the food companies

(11:34):
using AI, if we can connect the dots from people's wearables to be able
to tell their state of health and understand their lifestyle and try to nudge
them to healthier states. If I can produce something like Edens, which
is a supplement, three in one supplement, that has, you know, prebiotics,

(11:56):
probiotics and polyphenols, but it's the first, first prebiotic blend of
multiple prebiotics that this is food for your gut, actually, that actually
lowers your blood sugar, that targets specifically metabolic health.
So if I can work on these things and if I can help people be healthy,

(12:16):
I can't think of anything else more invigorating. I literally, I used
to wake up just to solve sickness. Now I'm like, even though my obsession's
around prevention, but now I'm getting to work on the meta problems, which
is can we fix the food system?

Oh my gosh, that I feel is a huge, big lofty goal, which I love. And,
okay, so as an actual user of January now, I have gone through the
process of trying it, connecting, and going through that two-week
training with the AI. So my experience was I wore the freestyle Libre,

(13:02):
I connected my Auraring, and I logged and tracked my activity as well
as my food. Ooh, we're aura ring twins. And

Love aura,

I

everybody

found it

should

pretty,

have

I

one.

know, really, seriously. I also use, so I feel like this year, there's
been a ton of really great advancements that have existed before,
but they've really come to the forefront, especially with the ways
that you can use and tie in wearables too. Like, natural cycles,

(13:35):
actually getting FDA cleared and they work with Oura Ring. Even
hearing you talk about all of these custom solutions, anyway, we could
talk about this all day. But going through that process was really
interesting to me because I had no knowledge of my blood glucose because
there was no reason really for me to, except for my checkup with

(13:58):
my doctor. So why is it important to stay in range and what happens
when you come out of range?

So for a person who is metabolically fit, it doesn't really matter to be in range
or not. Because if you're metabolically fit, whatever you do, let's say
you eat something that spikes your blood sugar, or you get on a bike and
you ride really hard for an hour, there is enough insulin to meet the

(14:28):
glucose that your body is producing. And there's no problem. there's
a nice balance, your metabolic fit, your body knows how to go very well from,
you know, fasting state to feeding state. It can essentially utilize
glucose very efficiently. It knows how to use it efficiently. So what

(14:50):
if your blood sugar goes way up? Because it's gonna come right down.
And so we don't really have a concern for a healthy person.
But, In the United States, 133 million people don't have that metabolic
health. So 96 million people have pre-diabetes and 37 and a half people

(15:14):
have diabetes. Now 22% of the people who have diabetes remain undiagnosed.
They don't even know they have diabetes. And 90% of the people that have
pre-diabetes remain undiagnosed. So for those people, it does matter to manage
their blood sugar because we actually know that for people that are compromised,

(15:35):
that have compromised metabolic health, glycemic dose regulation or having
hyperglycemia is a bad thing if your blood sugar keeps going up and it's
stressing your metabolic system. And basically it can cause that excess
blood sugar can cause all sorts of other diseases. It can lead not just

(15:58):
to diabetes, but it can also lead to cardiovascular disease. It can...
the two kidney, it can affect your nervous system, it can affect multiple
other organs, which is why diabetes is such a dangerous disease because
it has comorbidities. It brings on other things. So if you're healthy,

(16:21):
no problem. But if you're one of those 133 million people with prediabetes
and diabetes or diabetes, you really don't want to have spiky foods all
the time. You want to keep your blood sugar super level. You want to keep
it, so if you're if you have pre-diabetes maybe you want to keep your
blood sugar around 140. If you have diabetes keep it, don't have spikes

(16:45):
over 180. Maybe you don't have to keep it at 140 or 180. Of course that's
way too high, but you don't want to spike more than those numbers. So what
you want to do is you want to limit the assault on your body if you will
by limiting the spiking foods. So one of the things that January does
is tells you what your spiking foods are so that you can go after the problem,

(17:05):
not after all of the foods that you eat. One of the problems that we have
with what people are generally told is go on a diet, drop this weight, you
know, everything. Some people, we heard someone that went to the doctor from
an ethnic community and the doctor said everything you've been doing

(17:26):
your whole life was wrong. and you need to stop eating all those beans
and rice. I mean, it's just the most horrific thing imaginable. We don't
believe in that. We find that horrifying. We feel that we are what we
are. Most of us had no control over all the, what we've grown up with or our

(17:49):
genetics. Those are just the cards that are given to you. And not to
digress, but January is based on the month of resolutions and the month
of new beginnings is based on the Greek god Janus that has two faces,
one face forward, one face is facing forward and one is facing back. And
that's kind of how we look at life. We think that how you were raised,

(18:12):
your conditions, everything else, your genetics, those are just cards that
life gave you. But you as a person of reason, looking forward, can make
choices that are hopefully better for you. So what January tries to do
is to tell you What is the problem? Just trying to identify the problems
for you to solve as opposed to try to change your entire life. So we're

(18:34):
not trying to change your entire diet. We're just trying to look at your
high spiking foods and see what those are and try to hack those. And we
let you see alternative foods. So now that you've trained your AI,
Gina, you can go to the grocery store. You can actually scan any food.
I don't know if you've done that or not, but if you haven't.

Not yet.

Okay, you should go to the grocery store and just pick up box after box
of anything and just scan it and see how you might react to it. And it
informs you whether this is something you want to put in your body or
not. But you can have the digital twin tell you that instead of you actually
sticking in your mouth and trying to find out, you know, through your

(19:15):
body.

Oh, wow. Okay, so digital twin is something you've referenced a couple
of times, and I love that phrase. Can you kind of explain what the
digital twin means?

Sure, yeah, we basically build a biological model of your body as far
as metabolic system goes. So we try to, currently we're looking at minimal
inputs, which is food and activity. Your metabolic health has many inputs.
For example, how much stress you have, or how much you're stinking, or how

(19:50):
much you've slept, that sort of thing. But currently our model is trained
on how active you are. and exactly what you're eating, how much fibers
in your food, for example, has a lot to do with your metabolic response.
There's a lot of literature around the role of fiber or prebiotics, same
thing, fiber is prebiotics, the role of fiber in your body to stunt your

(20:14):
curves. So that's why a lot of people tell you eat fruits and vegetables,
eat fruits and vegetables, because fiber helps you feel full and is satiating.
so you don't feel as hungry and you don't wanna snack as much, but also
it lowers your blood sugar. So all of those inputs go into your blood sugar

(20:35):
response. So Digital Twin is for us to observe you for minimum of five
days. Some folks have, you know, sometimes their CGM falls off, sometimes
a few things happens, but you have a few days to train your AI and once
you... Once you train your AI, then you can go into January and then look

(20:56):
up any food and see what your response is going to be. Um, and you essentially
are having that biological model, um, try the ingredients of that food
to tell you what the response would be as opposed to you having to do it.
It enables mindful eating, which I think is really important. It's a little
bit like a weather forecast to know before you go. Um, and this is like

(21:17):
that. It's just to know before you eat, before you swallow.

I love it. So we've talked a bit about diabetes. We've talked a
bit about the importance of this tech for that population. Is it also
important for the everyday athlete, the population who's metabolically
healthy too?

Sure, yeah. I think, I think absolutely. I think athletes want to know how
much food to eat, what to eat. Unfortunately, some of the products that
are there don't tell you that right now. They just tell you your blood
sugar is going down, eat something. I don't find that particularly valuable.
I mean, it's valuable, but it's not that valuable. What I want to see

(22:03):
is your blood sugar is going down, eat this because I know that you are
a runner and I know that your body is going to give out at this point.
And so with AI, we can, we can predict all those things. And we haven't,
uh, we ourselves have not particularly focused on athletes, but if we
were running a company that was focused on athletes alone, that's what

(22:24):
I would want to do is I would say, you know, Hey, I know that you train
on Monday, Wednesday, Friday. I know you run two hours at nine o'clock. I
suggest this drink ahead of time. I suggest these electrolytes before
you run. I suggest this protein shake after I suggest. So. If I know
your behavior, then I can interfere and intervene exactly at the right

(22:47):
moment to get you to do the right things. And if I know the context,
if I know your behavior, if I know your lifestyle, I make recommendations
based on those, you are more likely to take my recommendations than
if I just tell you random things or like motherhood and Applify things.
Like, it's a good idea before workouts to do whatever, or it's a great idea

(23:07):
for recovery to do whatever. Like, That's people are just not interested
in, in that kind of generic feedback. I think people are infinitely interested
in themselves. And I think, so we are all about personalization, but January
is all about personalization, not because of vanity. We're all about personalization

(23:28):
because of deep multi-omic phenotyping. We want to learn everything about
the person. We want to learn, you know, everything that is knowable. so that
we can connect those dots for them so that we can give them insights
that they wouldn't have on their own. And certainly things that are
not human interpretable, that's what AI does for you.

Yeah, it's super interesting to Abbot, which makes the freestyle libre.
They're working with athletes now, like the world's fastest marathoner,
Eliud Koczoky, who

Mm-hmm.

used the sensor to test his blood sugar,

Yeah.

or his blood glucose, I should say, while training. So we're seeing
this tech, or versions of this tech, being used. for

Yes.

athletic performance.

Absolutely.

So I can only imagine that, yeah, there's just gonna be a spectrum
of things happening for folks on all ends of the metabolic health

100%

spectrum.

we are big, big Abbott fans and big lingo fans. And we think that, you
know, it's such a revolutionary technology. It's been around for 20 years,
but it's getting, you know, smaller, smarter. It's going to have multiple
analytes. It's gonna be able to read more than just glucose. It's gonna
be able to give you lactate and ketones and later, hopefully other things.

(24:57):
So. We are huge, huge fans of that. Just imagine all the good things you
get from that, have an exponential effect once you add AI on top of it.

Yeah. So lingo for the listener is Abbott's everyday athlete. We'll
call it an everyday athlete, but it's really focused on the non-diabetic
population, but it's using the technology of the freestyle libre
to just like Nushin, what you were saying, to monitor ketones, blood

(25:29):
alcohol, lactic acid, as well as

That's

glucose.

the...

Blood alcohol

Yes.

will be super interesting. I would be really

Very

interested

interesting.

to see, yeah, what the AI does with that. It's not out yet, right?

No, it's

Or has

not

it come

out

out

yet.

and I just missed it.

No, no, it hasn't. So far, it only predicts glucose. And the ketone sensor
is currently in a separate sensor, but it will be reunited. It will be
united, rather not reunited, but it will be united in the future. The ketone
sensor is out there in trial. It is being used on people. Yeah, no, it is

(26:12):
super exciting. I always talk about, you know, the holy grail of continuous
monitoring will be cortisol and insulin. If anyone ever worked on continuous
insulin monitoring, it would be incredibly, it would be life altering because
now we understand the glucose side of it. We just don't know how much insulin

(26:32):
someone is producing. We can guess at it, but unless you're like in
a laboratory setting, we don't have a continuous, we don't have a continuous
sense of a person's insulin production. unless they're in a lab and they're
being monitored for a period of time, you know, with IV. So, no, I think
we will see more and more wearables come out in the future. One of the

(26:57):
wearables that we're looking at, as I always talk about this one because
I'm so, so excited about it, it will be used subcutaneously. It will
live over 900 days and it will read 20 different analytes for you, including
cortisol. So that's at least three years away. It's in animals now and it

(27:19):
will still be a bit, it's still out there, but it's gonna be phenomenal.
I will put it under my skin for sure, 100%. And then I want the AI to tell
me how I'm doing all the time. Am I coming down with something? Am I
catching a cold? Am I stressed out? Am I stressed out when I meet Gina or

(27:41):
am I just stressed out in general? So like, I

Do

wanna

I?

know,

Oh my gosh.

I wanna know which, I wanna know who gives me stress, who does not and
who actually makes me calm. And like, imagine if you could just rank the
people during the day by like the ones that put you most at ease. Wouldn't
it be wonderful? You just like basically lean into those relationships.

(28:09):
and the people that just,

Oh my god.

you know, drove your stress through the roof, you would try to, you know,
a little bit less of those folks.

certain name shows up on your phone, cortisol spikes.

This

So

exactly decide

I can.

whether you want to pick up that call or not. It's going to happen.

Yeah.

It's going to happen and not that long into the future.

Oh my God, if I could program January to automatically text someone
when they call me, um,

Ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha

that they're stressing me out.

Yeah, it will be

Gina's

possible.

cortisol has spiked.

I think we basically connect your calendar also. If that person books you
for a meeting, you could decline it nicely. Your AI could just be like,
ah, you know. Or you could delegate it to somebody else to meet with them.
Or you could just learn how to be calm when you meet with them. That
would become your challenge. How can I bring my stress

Yeah.

level down when I meet with the person? Yeah, no,

who

this

I can

is

only

all

imagine

happening.

to. Yeah,

Yeah, I don't

the

know

recommendations

if...

too. So

Yeah.

if I go ahead.

Please, go ahead.

Oh, well, I was just going to add because if I could tell January,
for example, my mind is just spinning all the things I could tell
it that I think calm me down. So I could say like, oh, I do an infrared
sauna at this time. What are my cortisol levels? Or I do meditation
at this time. What does that do? Because I think cortisol is definitely

(29:45):
something like a lot of us think about as well as all of the other
metrics we're talking about.

Right, no, AI will definitely help us dial our lifestyle way more. Like today,
we're just thinking about, oh, AI is going to help me not eat things that
are going to spike my food without me having to try that. I can know ahead
or I can figure out how much of it to eat. Like maybe I should have
half or a quarter of a portion. I don't have to deny myself. But in the future,

(30:15):
absolutely. I think the interesting thing is, you know, it knows that
you shop at the farmers market on so many days. you know, it knows
that what's seasonal in your area and it's like, it's sending you recipes
for, for those foods that, that are good for you and it's personalized
to you. And so we're also working on things that are, that are, that

(30:38):
are kind of really futuristic in terms of our predictions. But, you know,
I'll leave it to when they are out to discuss with them. But our obsession
is around democratization of metabolic health, we don't want just a few
wealthy people to wear these CGMs. We want to try to figure out how can
we give metabolic health information to people who are not wearing CGMs?

(31:03):
And what can we tell them about foods? And how can we orient them towards
thinking about blood sugar and not just calories, not just calories, because
calories and blood sugar are not the same thing. And

Oh.

You can eat, you can eat two coconuts and two avocados and never have
a blood sugar spike, but it's probably not a good idea to do that. Um,
so you, you know, and these misnomers that people have, well, it's good
for you. If that's avocado is good fats. I'll just have two or olive oil
is good for you. I'll just pour a lot of it over my food. Um, so yeah,

(31:41):
so I think we will, we'll certainly with, you know, we've used generative
AI in our glucose prediction. And now everybody's learning about generative
AI in these language models. So now everybody understands, oh, what generative
AI is. It just, it can figure out kind of the next thing. So we can figure
out, so we did that six years ago. That's how we started. So currently

(32:07):
we predict glucose, but we should be able to predict anything else
for you, like ketones, like lactate, like cortisol. We should be able to
even potentially look at how much weight you gain from eating a certain
thing. So it really can do so much.

My honestly, my mind is spinning. It's almost like you're creating
the human metabolic project, like the human genome project,

I do.

like

Yeah.

an understanding of our metabolisms.

Mm-hmm.

One thing

Yeah, absolutely.

I found super

We've been

interesting,

dedicated to it. Mm-hmm.

I can't wait to see what we come up with or what we see. But the
thing I found really interesting about my own data that I was getting
for myself was that hot and sweaty workouts like HIIT or even like
hot yoga spiked my blood glucose. And that was a new phenomenon to me,
but workouts like Pilates didn't do that. So as you were kind of trying

(33:16):
this out for yourself, what was interesting to you about blood glucose,
like what's the most fascinating thing about it?

Well, the first thing we noticed, so we started this in our office in
2017. So early days of, late days of 2017, we hired our first technical
person in November of 2017. So early 2018, we were doing experiments on
our own. So we would eat foods, we would try to eat the same foods.

(33:43):
So we gave to the world this concept that if you walk after a meal,
your blood sugar goes down. And now everyone thinks that's like, That's
like common knowledge, but that was not the case. So we would eat foods
and then walk literally just in the office, just the length of our
office. We call the prancer sizing. And so if you move at all, your blood

(34:04):
sugar comes down faster than if you just sit. So one of the first things
we learned was that, and we were like, holy cow. So if you eat this,
you know, maybe this pasta is a red food, you shouldn't have it, but.
If pasta with 20 minute walk, no problem. But you gotta eat that pasta

(34:25):
and start moving. You can't move in 20 minutes after you eat the pasta.
You have to eat it and get going because that's when it matters the most
is moving, will actually lower your blood sugar. So the first thing
we learned was the power of movement to manage your blood sugar immediately
after eating. That was one of the biggest things we learned. The other

(34:47):
thing that we learned was when we were, we learned that people's blood
sugar response was different, not just between like Gina and Yushin, but
for Gina on Tuesday versus Gina on Thursday versus Gina on Monday versus
Gina on Friday, eating the same food, doing the same thing, because of
all the other factors that I mentioned, like stress, thinking, sleep,

(35:12):
how much fiber you had in your body one day versus another day. And so
that was really interesting. So like how much we varied how much all the
examples of people Around us that said oh gosh, I spike on ice cream
the other person. I don't spike on ice cream people who You know, there

(35:33):
are definitely high glycemic foods that everybody spikes on I mean the most
famous one is orange juice, of course But people generally spike on cookies
less on ice cream because there's more fat So we were learning these
things literally experientially in 2017 when we first started researching.
And then on the supplement side, we started researching on the power of

(35:56):
various fibers. And I've been taking some kind of fiber every day for
six years, but we started with like really, really hard things like guar
gum. And that really, really sticks to your teeth. And it's just like, it's,
it's gruesome. It's just really hard to, it's not something you can

(36:19):
really eat, but man, it stops. It stops, like it, it's incredible.
Like we would, we would experiment on ourselves and look at gastric
emptying. We would look at just like how food is moving through your
body, how it's clearing all your organs. So we were, we were obsessed
with building a mathematical model of your, all your organs actually. and

(36:42):
figuring out, okay, if this works this way, then how does this other work?
So if you have so much fiber, so much water, you drink so many glasses of
water and you move this much, then what's gonna happen to your blood
sugar response? So a lot of those things we learned, a personal anecdote,
like I've been a foodie since I was a child, since I was like five
years old, a fact, and...

(37:10):
You know, I once ate three kilograms of cream puffs. I think I was nine.
It was for a big party. I just went and had it by myself. And then
when it was time for dessert, there was no cream puffs. But anyway, I have
many stories like that. But

(37:30):
I think this idea of, you know,
not making people... completely, you know, deprived and not sort of taking this
approach that you shouldn't you shouldn't eat any foods because you know
Everything's dangerous for you is kind of not a great mental model. I

(37:50):
don't think so. Yeah, this is all super exciting and you know, I Science
is infinitely interesting infinitely interesting and when you put science
and medicine and AI together then it's even more so

All of that was honestly, the prancer sizing post meal is, I think my
perfect day.

Truly.

I wanna come to your office, machine, and hang out with you,

I do.

have a spaghetti dinner, and then prancer size. I'll

And

be right

run.

there. Yeah. I also have, I have a pretty similar story. My mom
baked a cheesecake for, I think it was my aunt's baby shower. And she
froze it because I loved, I love sweets. She froze it to keep me away
from it. And when she went to the freezer to take it out, I had like

(38:50):
bit by bit taken pieces of that cheesecake and scratched off the frosting
with my tiny kid fingernails to the point where she could not serve it.
And she was

Hahaha!

so mad at me. I think she's still mad at me honestly about that cake.
Sorry, mom. So I understand the cream puffs. I really do.
But I digress. I would be remiss, Nushin, if I didn't bring up Ozempic.
So we're talking a lot about technology that was created for measuring

(39:25):
blood glucose, which was largely invented for the diabetic population.
Same is true for Ozempic. Obviously, it's apples and oranges, but I'd
love to hear sort of your take on that, the trend of it. The good,
the bad, the ugly.

Yeah, no, we are, so I think we are given, so first of all, let's remember
that obesity is going up in every country in the world. There's no exception.
So all those Northern European countries that we admire and we say, why can't
the US be like the Netherlands, like Sweden, I'm saying jokingly, because it's

(40:03):
ridiculous when people make that analogy. But obesity is going up in every
country, so it's a very serious problem. And I think the new class
of drugs are, you know, are doing something really interesting and
really different because by essentially going through multiple mechanisms,

(40:24):
you know, not just one mechanism, which before was giving you like 5% weight
loss or whatever, they're going through multiple mechanisms. They're
able to achieve things that are just unthinkable, like 24% body weight
is coming off. So, do we think this is great? So I do think this is
great. for people that need a kickstarter to try to, they need an adjustment,

(40:49):
they need to kickstart their health journey and they want to have some help.
I think it is a great idea. Some people have really tried everything and
it hasn't worked for them. And so I do think it's a good idea. I do worry
about what happens when they are off these drugs. Now, some people,

(41:11):
not worried about that because when I interview them they say I'm not worried
I'm going to take it for the rest of my life. But I think others that
maybe are not able to spend a thousand dollars a year for the next 17 years
until these drugs come off patents and they become very inexpensive and
cheap, those people if they stop taking that drug they will and they have

(41:36):
not changed their lifestyle at that point they will regain the weight and
it's not like the best way to gain weight rapidly and to lose weight rapidly.
That is literally very, very bad for your body. So we know that when
rapid weight loss happens, your microbiome changes, it has many, many

(42:01):
angles that people are not necessarily looking at. So the question is,
what's the ideal scenario? And we think the ideal scenario is that you...
Try to change your lifestyle at the same time as you're on the drug. That
could be an oxymoron because some people, if they could have changed their
lifestyle, they would not have been led to the drug in the first place.

(42:22):
They have maybe tried that and it didn't work out and that's why they
are on the drug. But to the extent it's possible, for example, to practice
intermittent fasting, what if you eat two times a day, just in general?
What if... you're able to increase fiber in your diet in a big way. What

(42:44):
if as a matter of practice, you don't eat right before you sleep? What
if as a matter of practice, you move after you eat? Maybe not when you're
socializing, but maybe all the other meals where you're not socializing.
And so I think using six or seven hacks in your life and really nailing
those, like personally, I've always been a workaholic. I've always...

(43:08):
struggled with that because I just rather work than you know, it's I just
love working. So I have perfected sleep now. I've been working on it
for two or three years and I really know I have dialed my sleep. I know
what I have to do to sleep well. I know it very well. I also know how
to eat very well, extremely well. Like right now as I'm speaking with you,

(43:33):
I've been doing
And I also during the week, I try at least three days a week. I don't eat
any added sugar whatsoever. So anything that has added sugar in it, I don't
eat any carbs for like three days a week. So whatever hack that is simple

(43:57):
and it's a heuristic that you can use, my suggestion is, yeah, sure,
take the Ozempic. But can you, when you have assistance from Ozempic
while you're on Ozempic, Can you incorporate a few important hacks that
you could keep for the rest of your life, Ozempic or not? And if we can

(44:18):
do that, I think that's phenomenal. But if you just tell me, Ozempic,
eat whatever I want, lose weight, off Ozempic, gain weight, is that very
healthy? I would tell you no. I can't imagine that could be good for
you.

We froze.
Can you hear me, Nusheen?
Can you hear me or no?

Gina, are you there?

I'm here, can you hear me?

I can't see you or hear you. I hope, I wonder if it's...

I'm here, I'm here.

you

try something.

(46:15):
I'm in low data mode, so you should be able to hear me now. Can you
hear me?
New Sheen?

Gina, should I hang

Thanks

up

for watching!

and come back again?

I think, can you hear me?

Um.

I'm

for this thing

sorry.

I've ever seen.
So let me type. Wow, just let me type to her please.

(48:10):
Do you want me to log off and log in again?
You can hear me?

I can hear you. I'll email you.

Should I log off and log in again?
If you can hear me, tell me by chat.
This won't let me, oh.

Can you see me?
Can you hear me and see me?

Gina,

Yes?

I just went out and came back in and I still can't see you or hear you.

Oof. Oh my god. Oh my god. Wild.
Can you hear me now?

(50:10):
Goodness.
Nushing, can you hear me on your phone?
New sheen.

Hello? Hi.

Hello.

Oh,

Huh,

I'm just hearing

you can

myself.

hear me?

(51:19):
Can you hear

Hello,

me now?

yes I can. I just can't

Okay,

see you.

oh my

Oh

God.

my god. I just can't see you.

Okay,

Okay,

I

I

enabled

enabled

low

low

data

data

mode. Let's

mode.

turn

Okay,

it off.

sure.

Okay, can

No

you

problem.

see me now?

Great. Can you hear me now? Yes.

Oh my God, the universe does not want us to succeed. Okay, we're so
close to being done. Let's close it down and walk

down,

away from our computers

walk

for like

away

10

from

minutes.

our computers.

Take everybody, take a breath.
And now it's time for show and tell.

Show and tell. We'll share

Let's

a

share

tip. So,

a tip,

we're going

a resource,

to start with

or

a little

an

bit

article

of a

you referenced. Nushin, do you wanna go first

you

or second?

want to go first or second? First or second you go first. Yeah, love that.

Okay, great. So I am actually going to share

to

in the

share.

show notes a scholarly article

scholarly

about

artifice.

how to measure blood glucose that was written in 2014, which just
really

which

shows how

just

much has

really

happened

shows how much has

from

happened

then to now.

from then to now.

So it references

So it references

pricking your fingers

breaking your fingers

and the test strips.

and the test strips.

And it's really just

And it's really

a challenge

just a

that

challenge

a lot

that a

of

lot of

people

people

in...

in

America

America

and just across

and

the

just

world

across the

have

world

had

have

to go through.

had to go through.

I think it's

I think

so

it's

interesting

so interesting

all of the advancements

all the advancements

that have been made

that have

in blood

made

glucose

in blood

monitoring,

glucose monitoring,

especially with constant

especially

blood

with

glucose

constant blood

monitors.

glucose monitors.

So

So

take a gander

take

at

a

that

gander at that.

because wow, the things that

the

have happened

things that

in the past

have happened

14

in the past

years,

14 years or

or I'm sorry, seven

I'm

years,

sorry, seven

eight

years,

years,

eight years

it's

has

been

been

incredible.

incredible. Indeed.

Anoushi, what about

What

you?

about you? Well, I would, I would, I will share with you an article about
what happens to your microbiome after rapid weight loss and how to mitigate
sort of rapid weight gain after that. and I will give you the punchline

(53:28):
away. And one of the factors that mitigates rapid weight gain is eating
protein. But I will send the article so that you can share it with your
audience. There are many interesting articles that we write ourselves
at January. So check out the January Journal, which is on our website.

(53:50):
And it has, you know, we are a very nerdy bunch.

Hehehehehehe

So there's a lot of science that we share there from both on the metabolic
health side, but also around health in general.

of it. Okay, let's finish it off with one thing we are loving this week.
I don't think

I

for

don't

either

think

of us

for

it will

either

be

of

technology

us it will be technology

because we've had

because we've had

quite the time

quite the time

getting this podcast episode recorded. We are both troopers for
still being here. But what is one thing you're loving this week?

this week

It will fall under

it will

food,

fall under

friendship,

food,

fitness,

friendship,

or

fitness,

fun. Usheen,

or fun.

would you

Usheen,

like me

would

to go

you like

first

me to go

or

first?

second?

Go ahead.

Okay, here's

Okay,

what I'm

here's

loving

what

this

I'm loving

week.

this week.

I am

I

loving

am

this

loving

week

this

my

week my

own little creation

own little creation

of a

of

turmeric

a

latte.

turmeric latte. Ooh, love. So I'm

So I've been doing

having

coffee.

coffee.

I know it's been really

I know

good.

it's

So

been

coffee,

really good. So coffee,

coconut

coconut

oil,

oil,

oat milk

oat milk,

and turmeric.

and

And then

turmeric.

I just

And then I just

whisk, whisk.

whisk,

And it's so delicious.

and it's so delicious.

For some reason coffee

For some

lately

reason coffee

has been

lately

too acidic

has been too

for

acidic.

me. And that has been

And that has

really

been really...

delicious. What about

Fantastic.

you?

Well, mine, so my daughter was traveling. She was working, but traveling
remotely. Sorry, she was traveling, working remotely for the last month.
So she just came home. And so the funnest thing for me is to have to practice

(55:29):
discipline around her because she's a big foodie and she has a Instagram
account called strictly the good stuff. and she is just trying every
food imaginable around the world. And my discipline is not to eat whatever
she wants. So when I'm around her, and this has taken quite a while for me

(55:52):
to get to this point, because she's always like a butterfly. She's just very
happy. And she's like, how about right now, we just make our own acai
balls. Let's just get some fresh coconut, take the gelatin coconut flesh
out. I'll make some acai and then we'll just have mango and with cashews
and we'll just, she's always talking about something super luscious at any

(56:13):
hour. So it's actually a great show of discipline for me to be around
her back in the house of not just running out and eating whatever a
25 year old can eat. Cause she's also working out all the time. So that's
my fun thing, family and discipline around food. But taking that as

(56:36):
a really fun challenge.

I am ever since you mentioned her Instagram handle, I have been
on her Instagram.

Hahaha.

And I want at least five things she's posted here. Okay, okay.
She's living

The

a

girl,

good

well,

life.

I took her, yeah, I took her to, I took my kids to 105 countries and
I homeschooled

Oh my

them

god.

in addition to sending them to school. So if you have another podcast,
call me and talk, let's talk about kids and let's talk about parenting
and how to homeschool your kids. So, not how to, I'm sure a lot of people
don't wanna take their kids from, you know, Mecca to Pyongyang. North Korea,

(57:24):
but I did and it was amazing. It was amazing.

Oh my God, it sounds

Yeah,

incredible.

Mike, Mike. Yeah. No, they've become they've

My husband.

I think I think travel, I think world. I think travel is a life skill
that kids should learn early and just be, you know, be fall in love with
discovering other cultures and, you know, making connections with other
people. And it's something that is great when you learn it early.

Ooh, are you interested in adopting? No, I'm just

So

kidding.

many people

Me? No.

over the years have told me that. So many years. Because I did such
an unconventional, I took such an unconventional path. People thought
I was crazy to take my kids to the countries that I did. And in a lot of
cases, in multiple, took them multiple times. Because you take like

(58:26):
the United States is a huge country. So You can't really quote unquote
see the US in like a few, like

See it all.

it's kind of hard to see, you know, Washington DC on one trip or it's
hard to see China on one trip. So I took them over and over and over
again and layered, you know, age appropriately layered. And you know, my
daughter by the age 16 was a world expert in genocide. You know, it's

(58:55):
so, yeah, so. She has been to a lot of, you know, the common genocides
that people think of now, of course, in human history, we've been killing
each other, like, throughout history. So you can never name all the genocides

(59:16):
that have happened. But of the ones that happened in the last

Yeah.

two centuries, the ones that happened in the last two centuries, she's
been to those sites and she's seen those and she studied those. So...
Yeah, I'm very, very proud of my job as a mother and all the years that
I gave to it.

Ooh, if my husband and I pull the trigger and decide to have kids,
you will be my first email.

Call me,

My very

call

first call.

me.

Yeah.

I would love to,

Help

I'm

me, Nushin.

passionate.

How

Yes,

do I do

I'm

it

passionate.

my own way?

Absolutely,

Oh my

I

gosh.

would

That

love

actually,

to.

okay, great. I will actually take you up on that. I've got goosebumps,
so it's meant to be. Oh my gosh, we do need to do another

[Noosheen Hashemi] (01:00:04):
You

[Jeana Anderson Cohen] (01:00:04):
episode.

need to do another

Okay,

episode.

well this has been

Okay,

an

well

episode

this has

of

been

We

an episode

Got Goals, which

of We

is

Got...

in a sweatlife.com production, and another thing that's

And

better

another

with

thing

friends.

that's better with

Thank

friends.

you so much

Thank

to

you

Nushin

so much

Hashemi

to Nushi and Hashemi

for joining me

for

today,

joining me today. This

the CEO

is

and founder

the founder

of January.ai.

of jwly.com.

You are a delight. Thank you to

Thank you

our listeners

to our listeners

for subscribing,

for subscribing,

rating, and reviewing

rating, and

wherever

reviewing,

you

and watching

get your podcasts.

your podcast.

Thank you,

Thank

Ryan

you to

Duffett,

Ryan

for

Duffin

editing.

for editing.

You've got a big

You've

job

got a

this

big

week,

job

but

this

you

week,

can do

but you

it.

can do it. Thank

Thanks, sushi, bye!

you, bye. Thank you, bye, Gina.

Oh my God, we did it. Ha ha.

So much.

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What if AI could tell you which foods will spike your blood sugar?

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