Learn AI Capital Group — Own the stack. Bill the client.

01

The thesis

Most people are renting a commodity at a markup and calling it a business. The margin is in owning the compute, owning the distribution, and shipping before the window closes. That is what the group does, and it is the only thing we teach.

01

Ownership beats access

An API key is rent. Weights on a drive you control are an asset. Once the model runs on your machine, your marginal cost is electricity and your rate limit is your own patience.

02

Distribution is the moat

The model is not the product. Nobody pays for a model. They pay for the narrow, annoying problem it solves, delivered somewhere they already are.

03

We ship before we teach

Every method in the curriculum came out of a product that is live and taking payments. Nothing is repackaged from a thread you already scrolled past.

04

Speed is the strategy

The advantage is a matter of months, not years. Build small, launch ugly, charge early, and let the market correct you instead of a planning document.

02

Portfolio

Learn AI Capital Group holds and operates the companies below. Each one exists to find out what people will actually pay for, and each one feeds the curriculum.

Operating companies · last updated August 2026
Company	Sector	What it does	Status
TabDaddy	Consumer fintech	Receipt OCR and group bill-splitting. Scans a tab, assigns line items to people, writes the reminder you were too polite to send, and hands back a pre-filled Venmo link.	Live
Undisclosed	Consumer AI	In build. Local-first tooling. Details released at launch.	In incubation
Undisclosed	Vertical SaaS	In build. Details released at launch.	In incubation
Undisclosed	Education	In build. Details released at launch.	In incubation

03

Programs

Two courses. Take one, or take the bundle and get the group. Everything is self-paced, everything is lifetime access, and everything is delivered and billed through Whop.

Program I

The Local Stack

Run serious models on hardware you already own — and never pay per token again.

$149one time

Pick hardware honestly: what a 3060, a 4090, and a Mac actually run
Ollama, llama.cpp and vLLM — when each one is the right answer
Quantization without the hand-waving: GGUF, sizing, quality loss
Open WebUI, a private endpoint, and access from your phone
RAG over your own documents, without a vendor in the middle
LoRA fine-tunes on a single consumer GPU
Serving it to other people safely, and what that costs in watts

Enroll — $149 → Lifetime access · Updates included

Program II

The Cash System

Turn the stack into invoices. Offers, delivery, pricing, and the boring parts nobody posts about.

$199one time

Find a problem worth money before you write a line of code
Four offer shapes that sell: tool, service, automation, teaching
Ship a paid product in a weekend — the exact stack we use
Pricing: what to charge, when to raise it, when to refuse work
Selling on Whop end to end: storefront, checkout, delivery, retention
Cold outreach that gets answered, with the scripts
Reading your numbers so you keep the ones that work and kill the rest

Enroll — $199 → Lifetime access · Updates included

Best value

Full Access

Both programs, the private group, and everything the group ships next. If you intend to do this seriously, start here.

The Local Stack — in full
The Cash System — in full
Private group chat with direct access
Teardowns of what the portfolio companies ship, as they ship
Every future program added at no extra cost

$297 $348

One payment · Lifetime · Save $51 Get full access → Cohort 01 pricing. It goes up when it fills.

04

Curriculum

Nine modules. Every one ends with something running on your machine or something live and taking money. No module ends with a summary.

Stack · 01

Hardware, honestly

What your machine can actually hold. VRAM math, model sizes, and the point at which the answer is “rent a GPU for an hour.”

Stack · 02

First model running

Ollama end to end. Pulling weights, swapping models, context windows, and a local endpoint your other apps can call.

Stack · 03

Quantization

GGUF, the quant ladder, and how much quality you give up at each rung. Measuring it instead of guessing.

Stack · 04

Your own documents

Chunking, embeddings, a vector store, and retrieval that returns the right passage. Built locally, no vendor.

Stack · 05

Fine-tuning

LoRA on one consumer GPU. Building the dataset, running the train, and knowing when a fine-tune was the wrong tool.

Stack · 06

Serving it

vLLM for throughput, a reverse proxy, auth, and reaching it from your phone without opening your machine to the internet.

Cash · 07

The offer

Choosing a problem with a budget behind it. Four offer shapes, and how to test one before building anything.

Cash · 08

Ship and charge

A paid product live in a weekend: the build, the Whop storefront, checkout, delivery, and the first customer.

Cash · 09

Make it repeat

Pricing, outreach that gets replies, retention, and reading the numbers so you scale the thing that works.

05

Who is teaching

Cartoon portrait of the founder of Learn AI Capital Group — The Chairman LACG

The Chairman

Founder — Learn AI Capital Group

Computer science student. Builder first, teacher second. I spend most of my time shipping consumer software and the rest of it running models on machines in my own room, because paying rent to an API for something I can host myself stopped making sense a while ago.

TabDaddy came out of that. So does everything else the group is building. I teach the exact stack I use — the hardware decisions, the quantization trade-offs, the serving setup, and then the unglamorous half: what to charge, how to get the first customer, and how to keep them.

I am not going to tell you this is passive. It is work. But it is work that compounds, and almost nobody is doing it properly yet.

01CS student — building and shipping, not lecturing from theory
02Operator of TabDaddy, live and taking payments
03Local-first by default: own the weights, own the margin
04Everything taught is something already in production

06

Questions

Do I need an expensive GPU to start?

No. Module one covers what runs on modest hardware, including Apple Silicon and 8 GB cards, and is honest about where the ceiling is. You will also learn when renting a GPU by the hour is the correct answer instead of buying one.

How much programming do I need?

Enough to be comfortable in a terminal and read a Python file. You do not need a degree. If you have never opened a command line, start with The Local Stack and go slowly — the setup work is walked through command by command.

Is this another “AI side hustle” course?

No, and I would rather you not buy it if that is what you want. There is no promise of income here. It is a technical course on self-hosting models, followed by a commercial course on packaging and selling what you build. The work is real and so is the time it takes.

Why is it sold on Whop?

Whop handles checkout, access, and the community in one place, so I spend my time on the material instead of on billing infrastructure. Your purchase, access, and refunds are handled through Whop.

Do I get updates after I buy?

Yes. This field moves monthly and the material moves with it. Buying once gets you the course as it grows. Full Access also gets you every new program the group releases.

What is Learn AI Capital Group, exactly?

A holding company. It owns and operates the software products listed in the portfolio, and it publishes the programs on this page. The products fund and inform the teaching; the teaching is not a separate business dressed up as one.

Can I get a refund?

Refunds are handled under the policy shown at checkout on Whop. Read it before you buy — if the material is not what you expected, use it.

Own the stack.
Bill the client.

Cohort 01 is open. Enrollment runs through Whop — the storefront goes live shortly. Leave an email and you get the link the moment it opens, at cohort 01 pricing.

Review the programs See what we ship