AI Literacy
Stop treating every AI feature like the same magic trick. Learn what models can do, when they need your documents, and when a simple prompt beats building an agent. Free, with a lab and a quiz.
Start hereNew to AI? Start with the free AI Literacy course. Learn when to use a prompt, bring in documents, or reach for an agent, then try the lab and quiz. Ready to build? Create a small agent, add a tool, and test whether it runs only when it should. The architect course is independent prep for a real $125 exam: 120 original questions and a two-hour mock. Pro is listed at $19/mo and is not for sale yet.
Stop treating every AI feature like the same magic trick. Learn what models can do, when they need your documents, and when a simple prompt beats building an agent. Free, with a lab and a quiz.
Start hereIndependent prep for Claude Certified Architect – Foundations. Knowing the terms is one thing. Choosing what an agent should do when a refund, a missing fact, or a bad tool call is on the line is another. Practice with domain lessons, worked examples, 120 original questions, and a two-hour mock.
Open the courseBuild a small agent that can call a tool, save a note, and delete it again. Start with the included mock, so no API key is needed, then optionally connect a real model. Ten test cases help you check what happened.
Open the courseNext on the roadmap: prompts for the job you already have, with the boring constraints still in the prompt.
Next on the roadmap: how to read a vendor bill without inventing a usage number the invoice does not show.
Next on the roadmap: the gap between a demo and a feature a coworker can open on Monday.
Step counts and minutes are the pages in each course, using the minute field on each page. Question counts are the questions in the bank. The comparison still shows the separate seat-time method, including the two-hour mock. The sample certificate is a learning milestone, not an accredited credential. The glossary has 54 terms.
Diagrams, exercises, sources. They are not the courses above.
Start with what a language model does →Start here if the acronyms are piling up.
Understand the difference between producing plausible language and knowing that a claim is true.
Read the explainer →02 · 4 min readDecode the units behind model limits without pretending a token is always a word.
Read the explainer →Pick a model for the job in front of you. The leaderboard can wait in the other tab.
A practical scorecard for comparing capability, latency, data rules and cost.
Read the explainer →02 · 4 min readSeparate access to model files from licenses, hosting costs and operational ownership.
Read the explainer →How agents use tools and repeat steps, and what to check before you give one access.
Know when a fixed workflow beats a model choosing its own next action.
Read the explainer →02 · 4 min readUnderstand tool interoperability without mistaking a connection for a safety guarantee.
Read the explainer →How a demo becomes something your coworker can open without calling you.
How retrieval-augmented generation connects evidence to an answer—and where it can still fail.
Read the explainer →02 · 4 min readEvaluate quality and total cost per acceptable outcome instead of celebrating one lucky output.
Read the explainer →Use AI to cut busywork while you keep making the calls.
A reusable prompt structure built around task, context, constraints and an inspectable output.
Read the explainer →02 · 4 min readChoose low-risk workflows, protect data and measure real effort saved without outsourcing accountability.
Read the explainer →The source comes with the story.
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