How to pivot into AI (for non-technical people)

So, I don't have a technical background,

but I was able to pivot into the AI

field two years ago. Many of my

non-technical friends want to

participate in the AI revolution, but

don't know how. So much of the AI hype

has been around engineers and coding

that non-technical people often feel

left out. Today, I'll talk about how

nontechnical people can pivot into the

AI field. First of all, I believe that

in the age of AI, the definition of

being technical itself is changing. We

used to think of technical as equivalent

to being able to code. But now that AI

can code faster than humans, I think we

should revisit this dichotomy. If you

don't code, I personally think that

instead of trying to learn coding from

scratch or trying to get technical, you

should try to become technically

literate. What do I mean by that? Here's

what I think you actually need to know

to become technically literate. You

should understand what the

state-of-the-art AI models can do. What

are their limitations and potential? You

should understand the direction and

speed of the development. So follow

industry news and understand what it

will be able to do in three to six

months. Third, you should understand how

to turn technology into an actually

useful product that can solve real world

problems. You should know about and

become a power user of the top AI

products and also learn how to prototype

or design products through vibe coding.

Fourth, you should be able to convey the

benefits of AI products to end users. In

some I don't think you need to become a

coder to ride the AI wave and I believe

the line between technical and

nontechnical is blurring. Note that what

you choose not to learn is as important

as what you choose to learn because our

time and energy is limited. So I believe

that instead of signing up for coding

boot camp, you should just tinkle with

VIP coding tools to build little

projects. Instead of spending hours

pouring over academic papers about how

the models are trained, you should be

using these products hands-on and

watching podcast interviews with their

builders and founders. Next, how to

position yourself in the market. If you

want to actually join AI company, you

need to understand these two charts. The

first one is the tech stack of the AI

industry which I borrowed from Andrew.

At the bottom layer, you have chip

companies like Nvidia. Then you have

cloud. Then you have foundation models

like OpenAI or Anthropic. At the very

top is the application layer. This is

the layer that I believe nontechnical

people can contribute the most to and

also the layer that I think has the

biggest potential going forward. These

are things like the AI coding tools,

perplexity, granola, AI browsers, etc.

In other words, this is where the rubber

meets the road where the technology is

actually turned into a useful product in

the hands of end users. Let's look at

the second chart. This is roughly the

value chain of the AI industry. It

starts with researchers who find out

that AI has these new capabilities. Then

the engineers and the product team turn

it into actual product. Then it goes

through the go to market team which

consists of things like sales and

marketing. Then it finally reaches the

end user. I believe that if you're

non-technical, you would contribute the

most value at this last mile stage that

is between product go to market and the

end user. This could go both ways. For

example, you can work in the top

tobottom direction, which means helping

an AI product go to market, translating

a product into benefits that users can

understand and distributing it to more

users. Or you can work in the opposite

direction, which means you can take your

deep understanding of the end user and

translate that into product

specifications using these insights to

decide what to build as a product

manager or a founder. Next, I want to

talk about why you don't need AI related

experience. A lot of my friends complain

that they want to pivot into AI but they

don't have any AI related experience on

their resume. I think first of all you

need to understand that almost nobody

has AI related experience because this

field is so new. The technology itself

is only a few years old only 0.01% of

people can say that they actually have

AI related experience. But I think that

whatever field you were working in

before should become your asset not your

liability. This chart is what I mean.

You might think the pivot to AI will

look something like the top chart where

you're joining a completely unrelated

field that has nothing to do with what

you were working on before, but actually

it's going to look more like the bottom

one. AI is going to have an overlap

between whatever you were working on

before. And this is where you'll shine.

If you were working in education, then

look at companies that are trying to

disrupt education with AI. If you were a

lawyer, then look at companies working

on disrupting the legal field with AI.

The point is the biggest value tends to

be created at the intersection of

different fields or skill sets. If you

want to become irreplaceable, be at the

intersection. In order to realize AI's

full benefit, we need both technical

expertise and domain expertise because

technology is only useful if it's

applied to real world problems.

Engineers may understand the solution,

but you understand the problem. Your

past experience in these unrelated

fields should become your unique assets.

So, how do you actually land a job in

AI? I prefer to reframe this question

into how to get discovered because I

don't believe the traditional job

seeeking methods are relevant anymore.

You shouldn't be sending your resumes

into hundreds of job postings and hoping

someone picks it up. Most likely they'll

just pass on it because on the surface

you don't have any AI related

experience. Instead, you should spend

your time working on becoming

discoverable. Luck is mathematics. Luck

equals surface area times probability.

So, we should work on increasing our

luck surface area. To become

discoverable, you need to show, not

tell. You need to build something. You

have two options. Either you build a

product or you build an audience. These

two correspond nicely with what Naval

Ravikan said. He said, "Code and media

are permissionless leverage." So don't

wait for other people to give you

permission. You don't need anyone's

permission in order to build your

product or your own audience online. And

AI has made both of these a lot more

accessible. In the past, you needed an

army of engineers to build a product.

Now you can just vibe code it yourself.

You can just do things. It's no longer

about credentials like which school you

went to or what big tech company you've

worked at. It's about getting your hands

dirty and showing what you can actually

build. Your demo and your content will

speak louder than your resume. So to sum

it up, these are my tips for pivoting

into AI for nontechnical people. Work on

becoming technically literate. Become a

power user of AI products yourself.

Identify your place in the market. Your

past experience is your strength, not

your liability. Become discoverable by

building a product or audience. I deeply

believe that the AI industry has a place

for everyone. And as we're seeing more

and more technology translated into

actual products, the role for

nontechnical people will become more and

more important.