Guides
How to master AI, subject by subject
Vincoria teaches six subjects. Each guide below is the whole of what we would tell someone starting one of them: what it actually is, how long it honestly takes, the order to learn it in, the tools worth your time, and the mistakes that cost people weeks. Free to read, no address required, and edited whenever the tools move.
Develop with AIBuilding with AI means describing what you want in ordinary language and having a model write, run and correct the code, while you remain the person who decides what is correct. You still read the result, run it, and deploy it. That judgement is the skill being learned, and it is the part no tool replaces.Read the guide →Prompt engineeringPrompt engineering is the practice of getting reliable output from a language model on purpose rather than by luck. It covers choosing the right model, giving it the context it needs, structuring the request so the answer can be checked, and testing whether a change made things better or only different.Read the guide →Search & fact-checkAI search answers a question in prose and cites pages it retrieved while answering. It fails in a specific way: the sentence can be wrong while the citation next to it is real, because the model wrote the sentence and attached the source afterwards. Checking means opening the source and finding the claim in it.Read the guide →MCP & tool useThe Model Context Protocol is an open standard for connecting AI assistants to outside systems: files, databases, APIs and applications. Anthropic published it in November 2024, and it has since been adopted well beyond them. It replaces one custom integration per tool per assistant with one server any client can speak to.Read the guide →Image, video & audioGenerative media tools produce images, video, speech and music from a description or a reference. Producing one impressive result is easy and is not the skill. The skill is producing a set that belongs together: same character, same style, same voice, across twenty assets, on a deadline.Read the guide →AI for researchersAI genuinely accelerates research at four points: finding literature, pressure-testing a method, exploring data, and drafting prose. It cannot be the authority on any factual claim, and it fabricates citations in a form that looks correct. Used with a verification step attached, it is the largest practical gain research workflows have had in years.Read the guide →
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