Curiosity is an AI education for everyone. Three courses, for the people who actually have to use this technology. One for the general public, one for developers, and one for business, with a monthly mentorship and consulting alongside them.
A powerful, innate drive characterised by an inquisitive desire to investigate, learn, and explore the unknown. It fuels human cognition and acts as a primary catalyst for scientific and personal development.
The quality most worth keeping as machines learn to answer almost anything, since the next good question is still yours to ask.
The monthly mentorship and consulting are live today, both booked with a short discovery call. The three courses follow, and you can leave your email on any of them to hear the moment it lands.
Every course, and a community to go through them with. A live call each week, a room full of people doing the same thing, and honest feedback on what you actually build. For the months you want someone in your corner.
A short call to see whether it is the right fit, then start whenever you like.
Join the communityPrefer it set up for you, or a hard problem worked through with someone who has done it before? Book a call and we will scope it together, then quote the work in plain language.
A thirty minute call to see whether it is a fit.
Pick the one that matches you. Open it to read the outline and leave your email to be notified the day it opens.
How AI actually works, what the different models do, and how to use them well without the hype.
Design, build and ship AI agents that survive contact with real users, across the Claude SDK, Vercel, Supabase, AWS Bedrock, Azure and the Microsoft add in stack.
How to apply AI properly inside a business, picking the stack, customising it for your team and rolling it out without breaking trust.
AI for Individuals settles the basics across five modules. What these models actually are, the current landscape of tools, how to use them well, where Claude fits specifically, and what it looks like to live with this technology in a working day. Two more courses follow from there.
A mental model in plain English. What neural networks do, where modern AI came from, and the things it is not. Enough to recognise hype when you hear it.
Five lessons that move from the long history of the field to the mental model you will carry for the rest of the course. By the end of the module you can hold a conversation about how these models actually work, without having to wave your hands at the difficult parts, and you can tell the difference between a paper that matters and a marketing post that is dressed up like one.
Lessons in this module
Claude, ChatGPT, Gemini, Copilot and Perplexity. What each is good at, what each is bad at, and how to choose between them for the work you actually do.
A practical tour of the assistants people actually use. Each lesson lives with one product for long enough to learn its shape, then the closing lesson brings them together with a clear rule for which assistant to reach for in which situation, written for a real working week rather than a Silicon Valley demo.
Lessons in this module
Prompting basics, getting better answers, attaching the right context, and learning to spot the moments when the model is bluffing rather than thinking.
The skills nobody really teaches. How prompts behave when the question is messy, how to bring the right context with you so the model is not guessing, the recurring mistakes that send a perfectly good answer sideways, and the early signals that the assistant has stopped thinking and started inventing.
Lessons in this module
Projects, Artefacts, Skills, and a first look at MCP. Why Claude is the one to reach for when the work runs long, and how to drive it without getting in your own way.
A close read of Claude as a tool. The features that change how you work day to day, the developer surface that quietly extends the assistant into anything else you use, and the version of Claude that lives in the terminal alongside the rest of your software so the same model can help you write and ship.
Lessons in this module
Daily workflows, ethics and bias, privacy and data residency, the jobs that change, and an honest read of what is coming next.
The lessons that sit outside the model and inside the rest of your life. Daily working patterns that hold up across a week, the questions of fairness and bias that come up the moment a real team uses these tools, the rules on where data is allowed to live, the jobs that visibly shift, and an honest read of what the next two years actually hold.
Lessons in this module
Five modules, twenty five lessons, a capstone read and graded by a human, and a printable certificate you keep for life.
Since the beginning of 2023, the length of work that an artificial intelligence can complete on its own has doubled roughly every four months.
Model Evaluation and Threat Research, 2026.