Write prompts that work
Structured, repeatable prompts for real tasks — not lucky one-offs that break next time.
What you'll build
Real skills, real projects — not another slide deck.
Master advanced techniques
Context engineering, token optimisation, structured JSON outputs and reliable multi-step prompting.
Build custom GPTs
Turn prompts into reusable custom GPTs and AI assistants tailored to a job or business.
Run models your way
Understand model selection across ChatGPT, Claude and Gemini, and run local LLMs with Ollama.
- A reusable prompt library for real business and content tasks
- A custom GPT / AI assistant tuned to a specific use case
- Structured JSON-output prompts for automation-ready results
- A context-engineered workflow that stays reliable at scale
- A local LLM setup you control end to end
Who it's for
The skill under every AI workflow
Prompt engineering is the foundational skill behind every serious AI workflow — agents, automations, RAG systems and content engines all depend on prompts that are structured and reliable. This course goes well past 'write a good prompt' into context engineering, structured outputs and building reusable assistants, so your AI work is repeatable instead of hit-or-miss.
It suits anyone who uses AI at work — professionals, marketers, founders, students — and it's the natural first step before automation and agents. ONROL is project-first, so you finish with a prompt library, custom GPTs and assistants in a portfolio you keep and reuse.
The ONROL method
Build the evidence. Keep the proof.
ONROL is an execution school, not a lecture hall. Every session you ship something real — an automation, an agent, an app — and you keep it. You don't leave with a certificate alone; you leave with a portfolio of working AI products that proves what you can do.
Questions
Straight answers.
Is prompt engineering still a useful skill?
Yes — more than ever. As AI moves into automations, agents and RAG systems, the ability to write structured, reliable prompts and engineer context is the foundation everything else is built on.
Do I need to code?
No. Prompt engineering is done in natural language. The course is built for non-coders — professionals, marketers, founders and students who want dependable results from AI.
What will I build?
A reusable prompt library, custom GPTs and AI assistants, structured JSON workflows, and a local LLM setup — all kept in a portfolio you can reuse in your work or freelance projects.
Which AI models does it cover?
ChatGPT, Claude and Gemini for model selection, plus running local models with Ollama — so you understand strengths and trade-offs rather than relying on one tool.
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