Category: Tutorials
You are in the right place if you want a lesson you can follow, not a glossary and not a product homepage. This shelf holds most of the articles on Analytics Made Simple. Two paths sit inside it on purpose. SQL is the database path: you have rows, and you need to ask a question without exporting another spreadsheet. AI is the tool path: chat products, open-weight models, and the jobs those tools are actually good at. Other tutorials land here when they teach a skill that does not belong on a narrower shelf.
A category page is the pile. A series page is the path, with a place to start and an order. If you open a tag or page 2 of this list, you are in a filing cabinet. The lesson is the article, or the series hub that lines the articles up.
Where to start: if the pain is a table, open the SQL series and use the first part on that page. If the pain is a model name or a chat tool, open the AI category and pick the product you already have on screen. If you are not sure which job you have, open Learn and choose the track that matches the work, not the logo.
How to turn a chart into a short video with Claude Motion, and when a dashboard is better
Claude Motion turns a chart or report into a short animated video built from code, so you can fix any word or number and export an MP4. Here…
How to give an AI coding assistant the right files and context
Pack agent context on purpose: search, AST skeletons, tiered budgets, and pruned tool output. More tokens are not more understanding.
How to keep an AI agent from touching your real files and passwords
Run everyday AI agents behind privacy defaults, sandboxes, and permission tiers. Keep secrets out of the prompt path, isolate filesystem and network, and approve only mutating actions.
How to measure whether AI really saves your team time, without trusting a survey
People feel faster with AI tools, but the clock often disagrees. Here is a five-week test with a spreadsheet and a coin flip that measures the real time…
How to combine meaning search and keyword search for better AI document search
Use dense vectors for semantic match, sparse for exact terms, and hybrid fusion when both matter. Consider Matryoshka dims to cut storage. Test on your queries.
