Topic

Learning With AI

Use AI as a tutor, quiz partner, research aide, and source-based learning companion.

15 stories (5 articles · 10 videos)

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A few good first pieces before you browse the full feed.

Learning anything faster with AI: from "explain like I'm 12" to practice quizzes

A four-prompt loop that turns any AI into a private tutor — explainer, examples, practice, and feedback. Works for any topic, any background.

Understand the idea well enough to try it safely in a low-risk setting.

AI for learning a new skill: a 30-day self-study plan

A structured 30-day approach to using AI as a personal tutor and curriculum designer. Four weeks, four phases, with the exact prompts and the habits that make learning stick.

Turn the workflow into a small practical experiment with a clear quality check.

NotebookLM: turn any source into a personal knowledge base

Google's NotebookLM is the easiest way to chat with your own documents — books, papers, meeting notes, research files. A practical tour of what it does, where it shines, and the four use cases worth setting up this week.

Turn the workflow into a small practical experiment with a clear quality check.

More in this topic

MCP for the non-engineer: connect Claude or Cursor to your tools

MCP is the new standard for connecting AI to your tools. You don't need to write one to benefit. A non-engineer's guide to what MCP is, which servers to install, and what becomes possible once your AI can actually act.

Evaluate the implementation pattern, failure modes, and guardrails before building.

Deep Research mode: a 20-page report without reading 50 tabs

Deep Research — the autonomous research feature in ChatGPT, Gemini, Claude, and Perplexity — produces in fifteen minutes what used to take you a day. A practical guide to using it well.

Turn the workflow into a small practical experiment with a clear quality check.

The Model Context Protocol (MCP)

Anthropic. The protocol's designers — Theo Chu, David Soria Parra and Alex Albert — walking through why MCP exists, the components (server, client, transport), the reception since the November 2024 release, and which servers they actually use day-to-day. Useful as the canonical source after the Nate Herk overview.

How MCPs Make Agents Smarter (for non-techies)

Nate Herk | AI Automation. A 16-minute, no-jargon explanation of what an MCP server is, how clients like Claude and n8n use them, and what you actually do differently once you have one. Lines up almost exactly with the article's "connect Claude or Cursor to your tools" framing.

How to Become a Speed Learner (with ChatGPT)

Tina Huang. Walks through the structured self-study system Huang used to learn SQL in 11 days for a Meta interview — active recall, spaced repetition, and using ChatGPT to generate practice problems and explain mistakes. Useful as the "how do I actually execute my plan" follow-up to the primary pick.

How to learn to code FAST using ChatGPT (it's a game changer seriously)

Tina Huang. Hands you a study-plan prompt template ("Act as a coding tutor that creates study plans…") that takes the student's goal, time commitment, and resource preferences, then generates a structured plan. The framing is coding, but the prompt pattern is exactly what the article applies to any 30-day learning sprint.

AI For Data Analysis In 21 Minutes

Tina Huang. Tina puts Perplexity's Deep Research and ChatGPT/Claude analysis modes in the context of a working analyst's day — pulling together market signals, exploratory data analysis, and structured outputs. Useful as the "what else is this good for besides academic literature reviews" companion to the primary pick.

How to Use ChatGPT's Deep Research to Save HOURS on Research

Andy Stapleton. Stapleton runs Deep Research against the exact use case it shines at — a literature review with a clear scope, time frame, and structure — and shows the clarifying-questions handshake, the 10-minute wait, the 40-source output, and where the citations and tone still need a human pass. Calls out the limits honestly (no BibTeX export, occasionally too generous in source choice).

35+ INSANE Ways To Use NotebookLM (For FREE)

Matt Wolfe. Once you understand the basics, this is the right second video. Matt runs through a long list of less obvious uses — turning a book into a study guide, briefing yourself on a competitor from their content, generating mind maps from a folder of PDFs — that help you see how flexible the "grounded notebook" frame actually is.

How To Master NotebookLM in 2026 (Free Course)

Paul J Lipsky. A clean three-step framing — curate sources, ask the right questions, produce final outputs — that maps almost one-to-one onto how the article tells you to think about NotebookLM. Recent enough (early 2026) to match the current UI, including Studio, audio overviews, and mind maps.

How To Learn Anything 10x Faster Than Anyone With AI

Dan Koe. A different angle on the same problem: pick a real project, then let the AI surface only what you need to know to finish it. Useful counterweight to the Mike and Matty video if you learn better by building than by studying, and it pushes back gently on the "consume more courses" reflex.

How to learn anything fast using ChatGPT | Full guide to studying with AI

Mike and Matty. A 10-minute framework — Construct, Connect, Challenge — applied with specific ChatGPT prompts for each phase: ask for a syllabus, ask for analogies, ask for a practice test, ask for feedback on your explanation. These prompts work on essentially any subject from physiology to programming, and the tone is exactly the article's: AI as a tutor, not a substitute for thinking.