Stop Renting AI.Start Owning It.

No. This is the opposite. We don't teach you to call APIs—we teach you to build the systems behind them. In "Build Your Own LLM," you'll start with a blank Python file and build every component of a transformer: tokenization, embeddings, attention mechanisms, the decoder. By the end, you'll have built something that actually generates coherent text.

This is first-principles learning. It's hard. It's demanding. But it's the only way to truly understand AI.

These masterclasses are specifically designed for technical founders and senior engineers who need to make architectural decisions—not become full-time ML researchers. We start every concept with a TED Talk-style explanation of the "why" before diving into implementation.

The goal is to give you enough depth to architect AI systems, evaluate technical hires, and make defensible technology decisions for your startup. You'll understand trade-offs that API-only founders never grasp.

Search for "Build your own LLM from scratch" or "Reasoning models course"— you won't find much. Sebastian Raschka's book exists, but there's no live course teaching this systematically. Reasoning models (like OpenAI's o1) are cutting-edge—the technology was just released. Mixture of Experts architecture? That's how Mistral competes with OpenAI at 1/10th the cost.

We're teaching frontier AI that most courses won't cover for years.

You have lifetime access to all materials regardless of your tier. The cohort provides live instruction and accountability, but you can always revisit content at your own pace. Many students go through materials twice—first with the cohort for structure, then again independently for deeper understanding.

We also offer office hours specifically for students who want extra help on challenging concepts.

If you're building an AI startup, the 1:1 architecture sessions alone are worth the premium. You get direct access to review your specific system design, discuss trade-offs for your use case, and get guidance on technical decisions that could cost you months of wrong turns.

Compare to hiring an ML consultant at $300-500/hour or making expensive architecture mistakes. For serious founders, it's a fraction of the alternative cost.

Yes. Most tech companies have professional development budgets of $2,000-$5,000 that rarely get used. Our pricing is designed to fit within these thresholds. We provide invoices and certificates of completion that satisfy most L&D requirements.

We've had students from Google, Meta, Stripe, and numerous startups get full reimbursement.