Your users don't need another dang chatbot.
Learn how to fine-tune models that automate actual human processes, while capturing your users' individuality to build stickier AI products.
Go from this...
To this...
Learn how to fine-tune models that automate actual human processes, while capturing your users' individuality to build stickier AI products.
Too many SaaS companies pour resources into AI—only to end up with superficial chatbots or data-driven features that look good in demos but don't actually save time or create a defensible advantage.
When your AI simply provides information instead of completing critical processes, it becomes just another feature any competitor can replicate with a handful of API calls.
Y Combinator and other accelerators are overflowing with startups that bolt the same flagship LLM API's onto their products. VC partners indicate that many pitch decks rely on the same large language model APIs—pointing to a lack of technical differentiation. Even Sequoia Capital and Andreessen Horowitz now explicitly advise founders to focus on creating genuine moats through custom data.
Investors and customers alike are shifting their focus from clever prompts to methodical dataset development. Teams that can capture expert judgment, turn it into structured data, and feed it into purpose‑built models create advantages competitors simply can't copy‑and‑paste.
Instead of starting with raw data, we begin with how your product's top experts actually get work done. By mapping those nuanced decisions, creative insights, and domain-specific rules, we can replicate them in AI systems that truly automate tasks and preserve your unique "secret sauce."
The Emulate Framework systematically reverse-engineers your organization's expert workflows. We discover what makes your SaaS platform special—the very process your best users and internal experts follow—and turn that into an AI system that:
Expect 60-80% time savings on core tasks, freeing users to focus on higher-level work.
Preserve the decision-making elements and best practices that only you can provide.
Rather than a chatbot that suggests, Emulate automates entire processes, saving your users time and creating a defensible advantage.
By defining success metrics (time savings, improved output quality, lower costs) upfront, we ensure every AI project ties directly to business value.
LinkedQwen is a more accessible version of my GrowGlad model for LinkedIn post generation, which paved the wayfor the Emulate Framework. LinkedQwen is also freely available at Hugging Face here.
It powered a content marketing SaaS to help users consistently publish high-engagement poosts in their unique voice—without spending hours each week writing or editing drafts.
I was the guinea pig in the first tests, and the results speak for themselves:
To learn the Emulate Framework with hands-on experience, I've put together a course where you build the LinkedQwen model from scratch.
Get 40+ in-depth video tutorials and 27 python scripts that walk you through each Emulate phase using a LinkedIn post generation example.
From theory to implementation, you'll learn how to systematically encode the "special sauce" of a product and user workflows into features that standard AI APIs can't replicate.
Follow along with a small dataset to build your own LinkedIn post generation model that truly mimics a user's unique writing style and brand voice.
We cover AI practices for implementing your custom LLM in real SaaS environments—complete with documentation, performance monitoring, and more.
Gain a competitive edge that drives user retention and product-market differentiation
Learn a systematic, business-algined approach to customizing LLMs
Automate manual processes and clearly measure the impact of your AI initiatives
Learn how to build AI models that emulate your strongest users and give your SaaS a defensible advantage.
No preview lessons available yet.