One Designer + AI. Hundreds of Deliverables. — Vincent Wendy, AI Engineer

All right.

Hello everyone. Hope you guys having a

good time at the conference.

So, before we start

how many of you are actually uh

designers? Like a product designer. Hey,

one hands and another. Okay.

And how many I assume that the rest of

you are engineers? Is that correct?

Yeah, pretty much. Okay.

So, today's talk is a non-technical

talk, but more of a real-world

experience how I created the design for

AI Engineer this conference and

our other past conference as well and

how AI has helped me. And so, the talk

today is one designer plus AI, which is

me as the designer,

and hundreds of deliverables.

All right, let's start.

So, my name is Vinson Weng. I am a

senior creative designer at AI Engineer.

And at AI Engineer, it's a very small

team. So, we only have around 12 people

to 15 people at the moment. And

everyone has been doing their own thing

and

I think AI has been like has been a

really helpful way to like helping

everybody doing everything.

And

at if for if an at this scale

we have a problem, obviously, right?

And the problem is the scale problem or

I would call the challenges.

And how to overcome it?

It's basically automation and we get to

that in the later part of this talk.

So,

when I prepared this talk, we only

expected 6,000 attendees and now it's

7,000. Well,

good for us.

And then we have 140 sponsors. More.

140 plus sponsors. And then 300 plus

speakers, 600 plus sessions, and one

designer.

And everybody needs

every designs, right? Like every single

thing needs design. Sponsor needs

assets, speaker needs graphic.

You need sign it so you don't get lost.

And

this is basically what we do, what I do.

So, from stickers, do you like your

swag, your stickers?

Well, I hope you do because I create

that design, too. And

to a landing page,

speaker announcement, track mascot, all

the stuff that you see,

most of the stuff that you see

here, from a sign it to a

digital sign it, landing page,

everything is a deliverable.

And

a thousand details means a thousand way

to fail, right?

Because

I'm missing sponsor logos, going to be a

huge issue. And speakers that have a

wrong schedule, also a huge issues,

right? And it seems impossible to handle

that many kind of deliverables, but

yeah, meet my design team.

So, it's me and Devin, GPT, and Figma.

And right now we are at the stage where

tools isn't the like it's not a problem

anymore, but having a real problem is

our advantage.

So, for example,

when someone asked me, "What inspired

you when designing in AI engineer?"

I don't know the answer back then, but

after I think about it, it's actually a

problem that inspired me to like

designing in this AI engineer. And we'll

get to that in the latter part of this

talk.

So,

have you guys seen the talk by Simon

Wilson like in 2025?

>> Yeah.

>> Yeah, and it's pretty interesting,

right? He asked to

He asked every LLM to create

an a vector file, which is basically a

pelican riding a bicycle.

And it is basically to test and I tested

again and it's still doing this for the

basic model.

And it's not usable for me as a

designer. But as a designer, we have to

think outside the box.

And we could simply ask ChatGPT create a

still image like a PNG for a pelican

riding a bicycle and then I can

vectorize it on on Figma.

And we can ship that now.

So, we have to think outside the box

here

regardless the capabilities of the LLM.

And

So, how to solve this scale problem,

right?

Basically five five things. So,

foundation first, reusable designs,

automated workflows,

validated output, and also remove

frictions.

The foundation is definitely the core

part that we need to set up right. Like

the design system, typography, colors,

components, like other stuff.

And once this is set up, like for

example, when we create the website,

it's all set up within this thing.

And yeah, this is just an example. Like

we have the colors, primary, and then

also the accent colors,

the typography,

and also the tagline, all the other

stuff.

And

also, have you guys Are you guys

familiar with the atomic designs?

So, yeah, my previous background is I'm

a product designer. So, I'm pretty

familiar with the

thing where we need to create a

user-centric design and also like atomic

designs, right? Where we create the

smallest part possible and then

combining it into like basically a LEGO

pieces and then into a deliverables.

And this is pretty useful in my job desk

right now.

So, once we set up all of those

foundation, we basically need to create

for example, we use Defont a lot. In at

the office, we everybody use Defont.

Everybody like

abusing Defont for example.

Yeah. And

So, in this case, I just need hey, we

use this desktop typography and this

mobile typography because we know

Cloud or like any other LLMs love to

like throwing some random

font size, right? And if we don't define

it, it just delivering a slope like the

previous slope.

And

yeah.

Typography, color and stuff and

and then it comes to reusable design.

So, once we set up it right, like the

website is has the

the branding to it, all the other teams

on the AI engineer, like for example,

the marketing teams

can create everything basically. Like

they can create an email design based on

that. They can create a flyer, a

document

just based on the website because it's

already defined

like it defined early.

And yeah, once you get the design, you

can just rinse and repeat.

For example, the mascot, it's all has

the pretty much the same design and it's

rinse and repeat. And if you

already defining those things, you can

basically like create one design that

works for all.

And this is the part that I'm most

interesting to talk about, which is the

automated workflows.

Before, for example,

if you take a look outside the room,

there's a schedule, right? The schedule

for each and everyone.

So, we used to do it manually on Figma,

but now we use Devin for it.

And

let me show you.

Hey.

So, right now we just pull the latest

data. I just asked Devin like, "Hey,

I want this room

at these days." And then we can just

export it, download it PNG, and the data

is all accurate, and then we can just

ship it to the flash drive, and then

put it on the screen.

And

it was like impossible before because

the friction is just too much between

the designers and the developers.

We [snorts] cannot make things like

pixel perfect because

once we tell the designer, "Hey, this is

the design." And then

Sorry, the the engineers that created

the design, for example. "Hey, I need

this to be delivered." And then they

don't create it pixel perfect, it's a

lot of

feedback loop, right? But with Devin, we

just say, "Hey,

can you make this more accurate?"

We can just connect it to MCP, and then

if it doesn't work, we can just always

like

give a spec sheet or something that

can be defined like what's the spacing,

what's the

font size, etc. And

this is what we do to for the speaker

announcement. So,

we have 300 plus speakers, and it's

impossible for me to like handle one by

one, right? So, we create this thing,

which is called which you can also

access to speaker announcement, and you

can also try

it yourself.

Like this one, for example.

You can select it right here.

And then you can also change your name.

Well, that

Yeah. For example, this you can change

the name to whatever you want. And we

also have the landscape mode

which can be also loaded. If the speaker

also have the headshot and all the

details, it will automatically export.

And we also have the trading cards

which is surprisingly pretty popular.

And we have a different team. And this

is all pixel perfect.

All right. For example, this one.

This is inspired by TBPN, so

Yeah. And how do I deliver this in pixel

perfect? Let's jump into it.

So,

the process here is

before

when I start my career as a product

designer, it used to be just

okay, we need to research, we need to

build product like design thinking in

general, right? And then feedback loop

and stuff like that. But right now, it's

it's just outdated for me. Like in my

case,

we just go to Slack,

Figma, and then send it back to Slack

because Devin or Devin live in Slack,

and then ship all the things that he

need.

>> [snorts]

>> Like for example, if we can connect the

MCP or also the

spec document, which is for example the

spec sheet like this,

which is

uh plugin in Figma if you interested.

It's free and it's basically give an

annotation to the PDF.

And

yeah, all designers don't name their

layers, so yeah, this is just like

some random frame three, frame four, but

the LLM will get it.

And it's basically defining all this

spacing, all this

font size, and then all the

colors and stuff. It's definitely going

to help you develop a pixel-perfect

product.

And

we also have just recently like today

have uh photos which we have to create

the thumbnail for its

speaker, right? And then we ask Devin

like, "Hey, who is this person?" And

yeah, it kind of did. Like I make a

Tinder kind of

you know, detection

if this is the same person or not. And I

think it's pretty accurate.

It's Jason Liu. Yes.

And then we can use this to like

for context. Like before, when we create

the thumbnail, we have to search all the

codes that photographer have and search

it one by one and maybe by time

if possible. But now we can just like,

"Oh, this is Jason Liu. Download that

photo." And then we can paste it into

the thumbnail, right? And it's pretty

amazing. I mean, the world that we live

in right now is actually like the state

for me as a designer is already at the

peak because

what what else can you ask for, right? I

mean, we already have things to

automate, we already have things to

create the design fast.

Basically, all you need is a problem

because once you have a problem that

worth solving, you can

basically solve anything.

And back to my talk, I got sidetracked

right there.

Yeah.

And then yeah. And this is also the

amazing thing that we test.

So, as you know, we have like hundreds

of sponsors, right? Like 140 plus. And

as you can see on the at the lobby, we

have the banner with all the sponsors.

And

I basically tell Devin like

"Hi, could you compare

could you check if there are any missing

logos in this graphic?" And the accuracy

is 100% based on the test that I

do. So,

which is pretty well. And we use the

same thing for the

T-shirt that you got for your swag.

And yeah, surprisingly, Devin knows how

to like visualize things, right? Like

how to detect things visually.

And that is very surprising because

as a human, we can like give errors. Oh,

turns out there's one small something

that is missing. But with this kind of

thing, we can like double-check. So,

human plus AI, combine it,

well, you got your own QA team.

And then remove fiction.

So, this is just uh the way of thinking.

So, as a designer, we have to think

as a user, not as a designer, all right?

Because every user has its needs.

You can walk through the for example,

the map plan here. So, basically,

I'm imagining myself as an attendee to

go to the registration, go to the

see the wayfinding and the QR code and

then all the stuff. Basically,

everything needs to be connected so you

guys don't get lost and knows how to

find your rooms and

other stuff.

And

the real job is handling exceptions.

So, for example, oh, I have Yeah.

>> [snorts]

>> For example,

um

there is a schedule update, all right?

And

when we create this thing, it doesn't

has an edit button. And then one

morning, it just "Hey,

this schedule needs to be updated and we

don't have those edit buttons." I could

just ask Devin, "Hey, can you add me an

edit button?" And then it did. So, we

can change everything now and then ship

it to PNG and replug it to the screen,

which is pretty convenient, right? And

those exceptions, right? It

it's not possible before

when we have to do it manually and

stuff.

But now it's just get easier. And

so, the takeaway here is that to solve

the scale problem, you have to actually

think small. Think all the smallest

thing possible. Think everything that

can go wrong and will go wrong and then

try to solve it before. And also, like

yeah, right now basically you can

automate everything.

And

at this moment, having a problem is

actually going to benefit you because

that's going to help you ship

a better product, going to ship uh

things that are

good. And yeah, I think that's all that

I can share. Hope my talk has some

benefits to you and

yeah.

That's all. Thanks, guys.

>> [applause]

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