Deliberate Practice

Deliberate practice with AI: feedback that makes you do the work

The fastest way to make AI-assisted practice useless is to ask for the answer before you have attempted the problem. A practice-loop workflow — subskill, rubric, attempt, feedback, retry — that keeps the effort where the learning actually happens.

9 min read

Build a skill curriculum from outcomes, not a pile of links

A method for turning a target capability into prerequisites, practice tasks, evidence, and review checkpoints — instead of a bookmark pile of courses you never finish.

Intermediate

More in this topic

8 min read

Rehearsing a presentation with AI: timing and structure, not stage presence

AI can time your pacing, flag a missing thesis statement, and count filler words from a transcript. It cannot watch your eye contact, read a live room, or verify the facts you are about to present. A rehearsal loop that keeps both jobs in the right hands.

Going back to study after years away: a return plan that keeps the thinking yours

Returning to formal study can involve subject gaps, confidence, accessibility, time, and logistics in different proportions. A syllabus-grounded plan uses AI for scheduling while keeping assessed thinking with the learner.

What deteriorates when you outsource thinking

Letting a model start every essay, email, and argument can remove opportunities to practise starting them yourself. A skill-preservation audit — baseline, unaided attempt, assisted phase, independent check — makes that trade-off visible without claiming permanent cognitive decline.

Using AI to support a neurodivergent learner, without diagnosing anyone

A cautious way to explore AI-assisted format or pacing changes with the learner, teacher, and existing support plan — without diagnosing the child or withdrawing accommodations by default.

9 min read

Read less, remember more: an AI-assisted reading loop

Asking AI to summarize a document is the fastest way to feel informed and forget everything by Friday. A reading workflow — preview, active questions, unaided recall, source-checked synthesis — that keeps you the one who understood the text.

Spaced practice, retrieval, and interleaving—with AI doing the right work

Build a practical study system around three evidence-backed learning techniques, two of them strongly supported and one more tentative. AI prepares questions and feedback; you perform the retrieval and make the distinctions.

Why AI explanations feel like learning—and often aren't

A fluent explanation can make a subject feel familiar before you can actually use it. These three tests reveal whether AI helped you learn or merely helped you follow along.

New to AI

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

A 30-day AI-supported study scaffold built around practice, retrieval, feedback, and a real project, with clear limits on curriculum and assessment claims.

8 min read

Deep Research mode: frame the question and audit the sources

Deep Research — the multi-step web research mode in ChatGPT, Gemini, Claude, Perplexity, and similar tools — can return a cited, structured report after a longer autonomous run. A practical guide to framing questions, auditing sources, and knowing when not to use it.

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.

New to AI

8 min read

NotebookLM: Build a Source-Grounded Research Notebook

Build a focused NotebookLM collection, ask source-grounded questions, and verify the cited passage before relying on an answer.