DeepSeek + REA Is INSANE

DeepSeek can now look inside apps and

rebuild them. I plugged a tool called

REA, short for [music] reverse engineer

anything, into DeepSeek harness. Then I

pointed it at three apps on my [music]

Mac. It opened each one up, showed me

the evidence of how it works, and

rebuilt the idea as a beautiful business

tool, an agent control deck, a lead flow

reactor, and my own website rebuilt

[music] from scratch. I'll show you

every build, every prompt, and the exact

setup step by step.

So what is REA? It's an open source tool

on GitHub from Morluto. It has over

438,000

stars and it's MIT licensed. It gives

your AI agent one set of tools for

reverse engineering, native programs,

JavaScript and Electron desktop apps,

.NET apps, Android apps, and websites.

Everything runs on your own machine. And

the part I love, every answer comes with

the evidence behind it plus what it

could not prove.

Now the brain. DeepSeek harness is

DeepSeek's own agent app. It's open

source too, MIT licensed with over

275,000

stars. Everything inside it is a plugin,

so REA just slots in. I'm running

DeepSeek V4.1 Flash. It's fast and it

can look at screenshots which matters

when it checks its own work. Here's the

setup. Open your terminal and run npx

REA-agents setup -- client dsh. That

registers REA inside DeepSeek harness

and installs the reverse engineering

skill. One thing caught me out. REA

needs node 24. If setup stops and asks

for node, install node 24 next to your

current one and run it again. Then run

npx rea agents doctor. You want the

DeepSeek harness line marked healthy.

Restart harness, open a new session,

pick your folder, and pick your model.

One more

If DeepSeek tells you your account quota

is used up, go to settings, then models,

add OpenRouter with your key and pick

DeepSeek v4.1 Flash from that list.

That's exactly what I did for these

builds. That's it. Three commands and

DeepSeek can now look inside software.

Quick one. If you want my best setups

for DeepSeek and REA, like the three

prompts from this video, the evidence

checklist, and the design brief that

made these builds look this good,

they're all inside the AI Profit

Boardroom. You also get the faceless

video skill I used to make this video,

plus a community of people building with

AI every day, and a new tutorial almost

every day. The link is in the comments

and the description, or go to

aiprofitboardroom.com.

Build one. The agent control deck. Ion

UI is an open-source desktop app that

runs several AI agents side by side. I

asked DeepSeek to use REA to find out

how it does that, then build my own

version for a dental practice. Here's my

prompt. Use REA to reverse engineer how

Ion UI runs several AI agents side by

side. Write the evidence to evidence.md.

Then build my own version, an elegant

agent control deck with six live agents,

light trails, and a command box. Watch

what happens. It loads the reverse

engineering skill, unpacks the app, and

maps it. 38,000 pieces inside one app

file. 548 source files checked. Then it

hit a limit. Two bundles were too big to

pass, so it raised its own memory limit,

narrowed the search to the app's own

code, and kept going. And here's the

honest part. Its report says exactly

which conclusions came from the code and

which parts it could not read. It found

the agent manager at the heart of the

app, one adapter for each kind of agent,

and how each conversation tracks its

status. Then it built this. Six live

agents for Bright Smile Dental. Lead

finder, inbox, SEO writer, booking,

support and reports. Each card streams

what it's doing. Light trails flow from

the DeepSeek lead to every agent. And

when I type a new task, it flies to the

right agent, and that agent picks it up.

Build two, the lead flow reactor. Agent

is another open source app. You give it

a job, and it splits that job across a

team of worker agents. I asked DeepSeek

how the splitting works. My prompt, use

REA to find out how Agent breaks a

request into tasks and hands them to

worker agents. Write the evidence. Then

build a lead flow reactor for my dental

practice. This is where REA earned its

place. The desktop app turned out to be

just the front. The real task splitting

lives in a Python backend shipped inside

the app. DeepSeek would never have

guessed that. REA found it. So it

rebuilt that pattern for leads. New

leads fly into the reactor. Each one

gets split into tasks, qualify, reply,

book, and follow up. The tasks shoot out

to four worker lanes. And when an

appointment gets booked, the whole

screen celebrates. I can add a lead by

hand, and it goes straight through the

same flow. Build three, my own website

rebuilt. My prompt, use REA's website

analysis on juliangoldie.com,

which I own. Map the sections, fonts,

scripts, and buttons. Then rebuild it as

an elegant premium version. This time,

REA did something different. It launched

a real browser, loaded juliangoldie.com,

and captured the page structure, the

fonts, the scripts, and where every

button leads. 15 sections mapped. Then

DeepSeek rebuilt it with my real

sections and words. Big serif headlines

that fade in as you scroll. Soft, warm

light. Every service, every result, and

real reviews laid out cleanly. The first

version copied a banner I didn't want.

So I asked for a revision right in in

same chat, and it fixed it in one pass.

Here's what I learned from these three

builds. One, always ask for an evidence

file. It keeps deep seek honest, and you

can check every claim. Two, on big apps,

tell it to focus on the app's own code,

not the bundled libraries. Three, only

look inside software you own or open

source software you're allowed to study.

Then build your own version with your

own name and design. Four, ask for the

look in detail, colors, fonts, motion.

That's the difference between a plain

dashboard and something people actually

want to use. If you want the exact

prompts for all three builds, the setup

checklist, and the design brief, they're

inside the AI Profit Boardroom along

with [clears throat] the faceless video

skill that made this video. The link is

in the comments and the description, or

go to aiprofitboardroom.com.

Thanks for watching, and I'll see you in

the next one.