Using OSS models to build AI apps with millions of users — Hassan El Mghari

Channel: aiDotEngineer

Published at: 2025-07-15

YouTube video id: gcseUQJ6Gbg

Source: https://www.youtube.com/watch?v=gcseUQJ6Gbg

[Music]
Hello everybody. Thank you for uh
coming. My name is Hassan. I'm super
excited to be here today uh to talk to
you about uh how to use open source
models to build AI apps with millions of
users. Um, I've been building AI apps
for for several years now and I just
want to come tell you a little bit about
my journey, show off some of the apps,
and then tell you about uh kind of my
whole process uh of of building these
apps from idea to having the finished
app and uh how I uh market them as well,
and then some some uh advice overall.
So, I'll start off with some intros
about who I am, Together AI, the company
I work for, uh why it's one of the best
times to build right now, and then we'll
get into demos. uh I'll talk about my
tech stack and architecture and then
I'll end with uh my process for building
these apps and uh advice I have for
other people uh building these apps.
So um I lead developer relations for an
AI infra company called uh together AI
but probably the most relevant part uh
for this talk is the fact that I I build
a lot of these AI apps and I've probably
averaged one a month for the last four
years. Um, and I've been fortunate
enough that some of them have done uh
pretty well and and have gotten uh a
good amount of users and and GitHub
stars as well. Everything I do also is
open source. So, I'm going to show off
some demos uh but also you can check
those out in your own time and you can
uh dig into the code uh as well. Um like
I said, I I lead developer relations for
an AI cloud platform called Together AI.
Um we're a platform for open source
models. We give you an inference API to
be able to query uh really any open
source models probably that are out
there that that are good. Uh so we have
uh chat models like Quen 3. We have uh
reasoning models like Deepsecar1. We
have image models like the flux context
model that came out recently. Uh we have
vision models, audio models uh you know
almost all modalities. We also let you
uh run these models on dedicated
instances uh or fine-tune them on your
own data and and we have a GPU cluster
product as well uh if you want uh
training cluster.
Um, so before I get into the demos, I
just want to talk about the fact that
it's it's really a historic time right
now for building. And I think this is
because of two things. Like one, I think
the barrier for building has lowered
dramatically with a lot of these AI
tools, right? You can use cursor and
windsurf with your IDE to autocomplete
stuff. You could use uh these AI
builders like Bolt and Vzero and and
Lovable to prototype apps really
quickly. Uh you can use chat apps to
kind of brainstorm ideas or or um go
through the process of building an app.
You know, you can go to a chat app and
say, uh I'm building a Swift app for the
first time. Can you guide me through how
to do it? Right? So I think like the the
barrier has lowered on one side and on
the other side we're having these like
groundbreaking models come out every
single week that are enabling um
completely enabling builders to to build
completely new things. So it's like
these incredible AI models are coming
out that you can build with and it's
gotten a little bit easier. Um, so I I I
just think it's it's an incredible time
to to be building apps right now. Um,
I'm going to dig into a couple of demos.
These are some of the apps I I've built
that I'll I'll spend like 30 seconds on
each one demo demoing really quickly.
Uh, but one thing to to to note really
quick is the fact that some of these
apps have a couple thousand people that
have used them and then some of them
have like a million plus. And I think
like at a certain point it is a numbers
game and you kind of have to try out a
lot of different stuff and and I'll talk
about kind of how how I approach that.
Um, so we'll uh switch into some demos.
So in the beginning when I was when I
started building kind of a few years
ago, um, I wouldn't know what to build.
So I'd go on Twitter and I'd look up,
you know, people that tweeted like, "Oh,
I need an app to do this." And so here's
Sina. I said, "Uh, can someone build an
AI app to help me pick some glasses?"
And I was like, "Sure, I got you."
um and uh you know built this little um
tool that takes a bunch of different
requirements uh turns them into a query
and then actually um uses the Amazon API
to find products that you can actually
you know click on and and buy. Um, and
another one of these was, uh, one of my
friends, Theo, tweeted out like, uh, you
know, I just want an AI app that writes
my commit messages for me. And, uh, my
CTO at the time was like, I love that
idea. And, uh, so I just decided to
build it. And, um, all it does is when
you do get ad, it takes the git diff, it
sends it to an to an AI model and, uh,
it writes a commit message for you and
it and it kind of, uh, shows it to you
and you can kind of accept it. So, this
is one of my first apps that I built
that that ended up doing really well and
uh got uh I I think I got about 40,000
people that have installed it and and
downloaded it and it's also open source
and and I had a bunch of people
contribute which which is uh been great.
Um, another app I built was a like text
to app builder. There's a bunch of these
um where you can type in an app that you
want to build. Here I'm going to say
like a quiz app about American history.
And the way this works is it it takes
this prompt. It sends it to an AI model
to come up with a project plan and then
it sends it to another model to actually
uh write React code that that we can
show. So, um in in a second this should
populate, but obviously also also open
source. Um I've had about 5 million
requests go through this app and about a
million apps built um just through this.
Uh and I have uh a little over a million
people that have ended up uh using it.
So, this is an app, yeah, that that kind
of just generates images uh as as you go
through it and um also has about over a
million people and and has uh about 48
million images that were actually
generated uh with this app. I have an
app called Napkins where uh it it takes
a uh screenshot of an the idea is it
takes a screenshot of a napkin like idea
is like you draw a little web app on a
napkin, it takes a screenshot of it and
it can actually uh uh build it for you.
Um,
so yeah, that's uh that's another one of
my apps. That one has about 40,000 uh uh
users. I have another one that lets
people kind of upload a resume and then
builds them like a personal site like
this uh for for people to check out. Uh
and you know, there's there's a bunch of
others. Ones that visualize menus. Um I
built like an an AI uh chat app, like a
tutor app where you can um you know, put
in a topic that you're interested in,
like personal finance, and it can
explain it in the level of like an
elementary school. um uh uh person uh
and then some OCR stuff as well. So I'll
get back to the slides. Um
a lot of these apps have uh a very
similar architecture that I end up
using. And so this similar architecture
starts with uh a user coming in and
typing something or uploading an image
usually. So it's some sort of user
input, right? And I take that and I
generally will send it to an AI model on
on together AI. So it could be like an
image to image app where I I take an
image and I send it to an AI model to
make another image and then show that to
the user. Um so step two is I send it to
an AI model. Step three a lot of the
time is I I store that uh image or uh
that text in the database and be able to
show it to the user. And then step four
is I just show it to the user. Um so
it's a a very very simple architecture.
A lot of the time there's one single API
call happening. You know the user does
something I send one API call to an AI
model. I get the response back and I
show it to the user. Um and I think it's
this simplicity that uh is is really
really important both for moving very
quickly um but also for validating these
ideas. You know the more simple you can
drill down an idea the the the faster
you can kind of build. And then this is
my tech stack that I usually use. I use
together AI for all of my AI models. I
use Nex.js and TypeScript as my like
full stack framework uh for building
things. I use Neon as a uh as my
database. It's a like a really good
serverless Postgress host. I use clerk
for authentication. Uh I use Prisma as a
way to talk to my database and
TypeScript. Uh I use Shatzen and
Tailwind for for styling. S3 for
uploading images. Plausible for uh
website analytics. And I I kind of uh
showed you guys this in in a couple
different places. Uh so it's cool that I
can see the number of unique visitors. I
can also see where they're coming from
and what countries and what device
they're using it on. Uh and one thing I
always get very um uh surprised by is
the fact that a lot of people use most
of my apps on on mobile. So like it just
goes to show that the like mobile
experience is really really important.
Um so Plausible for website analytics,
Helone for LLM analytics so I can dig
into my LLM requests and like
troubleshoot things and then Verscell
for uh for hosting uh these apps.
Cool. So, I'm going to talk about my
process for building these apps. And a
question I get a lot is like, how do you
come up with these ideas? Uh, and I
think like the the biggest thing I did
for ideas that that helped me out was
just to keep a a list of running ideas.
Um, I think we all get great ideas at
random times and most of us don't write
them down. And I think like uh that
makes a lot of the difference. And so I
think keeping this list of ideas uh
trying to write down anytime you see an
interesting idea or see an interesting
product and you say, "Oh wow, that's
actually really cool. Maybe I can use uh
a similar methodology to and apply it to
something else." Um, so ideation is like
uh a big thing. And uh the list of ideas
I have, I usually always have this short
list of like the top five. And so I like
I know right now kind of the top five
apps I want to build next. Um and then
if anything kind of drops in between,
then I'll I'll build it. You know, if a
new image model comes out next week
that's like really really incredible and
open source, um I'm probably going to be
scrambling to build an app with with
that. Uh naming is another big one. You
know, you want a short memorable name.
I, you know, you can use AI tools like
domains GPT to kind of uh check names
that also have the domain name available
uh to to use them. Uh number three is
design. you know, thinking through how
the app will work. Like, you know, I'm
going to have a landing page and a user
is going to click like enter and then
enter get this page where they upload
something and then they see an image,
you know, and so it's like these two
screens and uh you can either kind of
sketch it out on a piece of paper, you
can use Figma uh or you can use a lot of
these prototyping tools uh to to try to
help you think through uh what what the
app is. Uh and then I go about building
the actual app. So, trying to make the
simplest possible working version of a
specific app. Um, and like I said, I I
always try to shoot for like one API
endpoint, you know, like one like just
very very simple. Um, step five is like,
you know, I have a working prototype
now. I I start to think through uh
authentication and limits of like, okay,
like how expensive uh is this? Like how
many um how many uses do I want to give
each person per day? Do I want to want
to add authentication? Do I want to add
bring your own API key? Uh so it really
just depends on on the app and the AI
model that I'm using. Uh, and then step
six is usually kind of prepping for the
launch, getting a nice OG image, getting
a domain, adding analytics, uh, writing
a nice readme because like I said,
everything I kind of do is open source.
So, I also want to make sure the code is
is really easy to use and and really
easy to uh to clone.
Um, and then the last step is actually
launching. And so, I usually use
LinkedIn or X to to launch and uh, you
know, kind of uh, just see what people
say at that point.
Cool. final section uh and then I think
we'll get into some Q&A. We have a
little bit more time because the demos
didn't work. Um so advice for building
apps. I have these like seven tips that
I'm going to go through. Uh one is
thinking of an idea that excites you but
is very very simple. Uh that you should
be able to describe to anyone in five
words, right? Like blinkshot generate
real-time images. Llama coder go from
some text to an app, right? Like, and I
think this is one of the biggest
mistakes people use is they try to they
try to think like, okay, you know what?
I like I want to build this like
personal CRM software that has this
dashboard that will email me every week
and do this and that and you know, they
come up with this like grandiose version
and spend like six months building it
and then they realize, oh wow, it's like
it's it's um this isn't this wasn't the
right thing to build or um this is just
like really hard and nobody cares about
it now. And so it it's all about uh
thinking of an idea that excites you but
is also uh really really simple. Number
two, and this is very underrated, is
making sure the UI looks good. A lot of
the apps I showed you are AI apps, but I
actually spend 80% of the time on the UI
for most of my apps. Um, and that should
tell you like how how important this
thing is. I I've like the first few apps
I've built kind of looked really really
bad and that was a big part of why
nobody kind of used them. And I've
started learning that even if you take a
really simple idea or something that's
like so simple like summarizing a PDF,
right, you can go to Chadb and summarize
a PDF right now. But I I built a PDF
summary app and I spent a lot of time
making it look really really really good
and and then I had tens of thousands of
people that that ended up using it. Um
so it's all about making it look really
good, making it really easy to use. Uh
and making it really really
straightforward.
Um the third tip is just keeping the app
simple. I talked about this a bunch, but
uh most of my apps have only one or two
API calls. Um tip number four is trying
to incorporate the latest AI models. A
lot of these apps um that that I showed
you have like used some of the latest AI
models like Blinkshot real-time image
generation app um that used uh a model
called Flux Chanel and I and I launched
this app I think 2 days after this model
came out. Um and so it was one of the
first apps that leveraged kind of this
new technology or this new really really
fast model that was good. Um and so
doing that kind of increases uh the
potential for uh virality.
Uh tip five is launching early and then
iterating. Um, for a lot of these apps,
like still to this day, you know, like
40 apps later, I still have no idea what
will do really, really well versus what
won't. Um, and the only way to de-risk
this is to simplify your project to
launch early and then if nobody really
cares about it or not a lot of people
use it, then at least you know, you
didn't spend 6 months building, you
spent a week building and you can kind
of move on to another idea.
Cool. Uh, another tip that I that I've
kind of done is trying to make it free
and open source. um so folks can kind of
learn from you and are also very
incentivized to share it. Um and so uh
this is something that that's worked
well uh for me. And then the last tip I
have is uh just keep shipping. Um a lot
of AI apps like I said don't do very
well. It's a numbers game. You have to
kind of keep building and building and
building and the more you build the more
you realize you know kind of what
resonates and what doesn't. The faster
you get at building uh and the better
you get at like picking picking ideas.
So, um, a lot of it just comes down to,
you know, putting in the hours, building
a lot of stuff, and then, uh, seeing
what happens.
And that's all I have. We actually have
5 minutes for Q&A if anybody has any
questions. Um, and yeah, I think you can
line up at these uh, podiums and we can
uh, take a few questions. But just uh,
before that, uh, you can find me on
Twitter at nutlope or uh my email,
hassanto together.ai. Uh we also have a
together AI booth here at S25. Um I'll
be there uh for a few hours after after
the talk. So uh come and talk to us.
Yes.
Thanks for sharing.
Yeah, I just y Oh, it's on. Okay. Uh
thanks for sharing. This is great. I'm
just curious. Uh you have a lot of
traction success more than many most YC
startups. Why don't why don't you just
start a company? It seems like the
perfect formula. I'm just really
curious.
Yeah. Um that's a good question. I mean,
part of it is I I really enjoy um I
really enjoy teaching and a lot of these
apps like I can a lot of these apps,
first of all, do well because they're
free and open source, right? And so
because I'm I'm strictly not trying to
monetize them. I'm I'm strictly like
trying to make them free and I get
companies to kind of sponsor it and and
uh and and keep it open source. Um so I
just kind of enjoy doing that and
launching these apps and I I will also
like make videos and blog posts about
different things. Uh but yeah, maybe
eventually I'll I'll come out with an
idea that I really really love working
on and uh and and do that. But um for
now it's just been really fun getting to
build a lot of the stuff and experience.
If you ever do start a startup, let me
know. I I'll Andrew invest.
Thank you.
Yes.
So what are some common trends with
ideas that maybe you thought were good
but didn't resonate with people and the
reverse? Where have the surprises been?
Yeah, that's a really good question. Um,
where have the surprises been? It's It's
been a little bit random, honestly. Um,
I think
I I think one insight I got is like
building apps where people can very
easily share what they create tend to do
way way better. Um, and so now I try to
think about that like building in that
viral loop into my apps on like if you
can generate an image, I want to make it
really easy to share that image or and
share it with like a really nice OG
image. Um, and so that's one insight
I've had is like, you know, apps that
have that viral loop of of like, oh,
this is really cool and I can share this
with a friend and then they can go on it
and try it out and they can go on it.
Um, and so that that's something that
I've incorporated a little bit more.
Yeah.
Yes.
I love that you're making all of this
like, you know, it's all free so far.
It's not monetized, but how are you
paying for like all the compute and the
model calls yourself? Like, are you
funding this?
Yeah. Great question. So, um, first off,
you know, I work at Together AI. We
sponsor all of the compute in terms of
the AI models, but then I'll also
partner with other AI companies like
Neon gives me a free database to use
their database and and like you know
like Clark gives me a free account for
authentication and uh uh and the reason
for that is because it's it's it's all
open source. So it's it's in their best
interest to be in that open source
project and and to for people to use it.
Um, and so that that's also uh like a
good piece of feedback I have for people
is like if you want to just tinker with
apps and build them, a lot of people are
like, "Oh, but I I can't launch an app
because AI models are too expensive or
this thing's too expensive." Um, more
often than not, if you launch something
and you reach out to these companies and
you say, "Hey, like I'm building this
this open source app. Can you please
give me some credits?" More often than
not, they will. Uh, and so that's
generally how I do it.
Awesome. Thank you.
Yeah. Yes.
Yeah. Um, I mean, thank you for this
talk. It was it was really great. Um, I
just had a question because you talked
about how frequently you build these
apps like every every week you said for
for a decent amount of time. Um, and you
also talked about, you know, using the
latest and greatest in AI models with
them changing so quick and with you
having so many apps out there. Do you
ever struggle with like going back
through and and like changing the models
that you've used for some of these apps
and and how do you deal with that?
Yeah, it's a great question. Um I I I
think like a really cool um a really
cool thing is the fact that you can do
that. You can just build an app with an
AI model and then a better AI model
comes out 3 months later and you can go
and a lot of the time it's like a
oneline change of like let me update
this model and the app just gets way
better or it just unlocks new things. Uh
and so that's something I do frequently
where I'll go back and I'll like even
like relaunch an existing app with a new
AI model or add a tiny feature to it.
Um, and so, um, yeah, I think that's
kind of the superpower of like building
with AI is the fact that you can just
kind of replace these AI models.
Thank you.
Yeah.
All right. Awesome. Thank you all so
much for coming. I appreciate it.
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