LLM engineering. The discipline, not the demo.
Moonlabs is the operator-led AI Academy in Derby. We run three live companies — Homemove, home.co.uk and homedata.co.uk — and we teach twelve students per cohort to ship a real AI product, sell it to a real customer, and raise on it. Three pillars: Coding, Commercials, Investment. Twelve weeks. £6,000.
Moonlabs is what we are. Two operators — James Freestone and Louis O’Connell-Bristow — who run Homemove, home.co.uk and homedata.co.uk. Every customer surface and internal tool at all three is built on the LLM engineering disciplines this page covers — we ship these patterns ourselves, every working day.
The Academy is what we do. A twelve-week, in-person, twelve-student cohort in Derby. You build a real AI product. You sign a paid pilot on it. You write a deck and a financial model. You leave with a deployed system, a paying customer reference and a live investor pipeline. Coding, Commercials, Investment — the three pillars taught in equal weight every week.
Why this page exists. “LLM engineer” is one of the fastest-growing technical job titles in the country and almost no course teaches it properly. Most resources online stop at calling an API and pretty-printing the result; the production discipline — evals, structured outputs, retries, observability, cost ceilings, agent orchestration, retrieval, regression catches — is folklore passed around inside a handful of teams. You leave the Academy as one of those handful — or as the founder of the LLM-engineering-shaped product you used to wish existed.
Coding · the full LLM engineering stack, end to end
Claude, OpenAI and open-weight models. Structured outputs, tool use, evals gated in CI, retries that do not loop, observability with token-level cost reporting, provider-portable architecture that swaps in an afternoon when the leaderboards reshuffle. A deployed LLM system by week twelve — what a real LLM engineering portfolio piece actually looks like.
Commercials · the AI-engineer salary band
AI-native employers (Anthropic, Cohere, ElevenLabs, Mistral, Wayve, Faculty AI, Sierra, Glean, Hebbia) pay senior LLM engineers 3-4x conventional senior-eng rates — if you can show shipping evidence. Pricing your own work, the discovery call, a one-page pilot agreement. A paid pilot or a credible senior-LLM offer by week six.
Investment · raising on an LLM-engineered product
Investors back LLM engineers who can also ship customer-facing product. Sierra ($4.5bn), Glean ($4.6bn), Perplexity ($14bn), Cursor ($2.5bn), v0/Vercel, Cognition (Devin), Lovable ($200m+), Inflection, Reka, Anyscale — the founder shape investors are loudest about wanting is exactly what the Academy produces. Cap table, ten-slide deck, financial model. A live investor pipeline by demo day.
Common questions.
How is this different from a prompt engineering course?
Prompt engineering is one component. LLM engineering is the broader discipline that contains it — evals, agents, retrieval, observability, cost discipline, regression management, deployment. The prompt engineering page is the sister framing for the prompt-specific entry point.
What providers do you cover?
Anthropic (Claude), OpenAI, and open-weight models where they fit. The course is deliberately provider-agnostic — the durable skills transfer.
Will I learn fine-tuning?
Lightly, where it earns its place. Almost no useful LLM engineering in 2026 trains models from scratch, but fine-tuning small open-weight models for narrow tasks is a real tool. We cover it pragmatically.
Will I learn agents and RAG alongside?
Yes — both are core to the syllabus. The agents course and RAG course pages are sister framings.
Is this for engineers or for non-engineers?
Mostly engineers and engineering-adjacent operators. The on-ramp for non-coders is real (see that page), but if “LLM engineering” is the phrase that brought you here, you already have the appetite for the technical depth.
More Academy entry points.
The Academy is one course with many doors. Each of these pages is a different entry point into the same twelve weeks.
Build it. Sell it. Raise on it. In twelve weeks.
Tell us where you are starting from and what LLM-shaped product you would build first. James and Louis read every application personally and reply inside the week.
© 2026 Moonlabs Incubator. All rights reserved.