Learning a skill when a machine can already do it
This site is mostly about languages, and one part of it is about how learning works in general. This part is about the question that started arriving in 2023 and has not stopped: how do you learn to design, to program, to write, to analyse, when the thing you would have spent two years slowly getting good at is produced on demand, in seconds, to a standard that looks finished?
There is an answer, it is not the same answer for every skill, and almost everything written about it is either vendor copy or panic. These pages are neither. Each one sets out what actually changed about learning that skill, a staged path with an explicit rule at every stage about what the model may and may not do, the things you must still be able to do with it switched off — and the research, with what it measured and how much it can carry.
Start with design → Or with programming, where the evidence is sharpest
The one finding every page here rests on
In 2023 a research team gave nearly a thousand Turkish high-school students a GPT-4 tutor for their maths practice. While they had it, their practice performance rose 48%. Then it was taken away for the exam, and they scored 17% worse than the students who never had it at all. A second version of the same tutor, restricted to giving teacher-designed hints rather than answers, kept the gains and did no harm.
That is the shape of the whole problem, and it repeats in every discipline anyone has measured. Assistance improves what you produce while you have it. Whether it improves you depends entirely on what it was allowed to do — and the difference is invisible from the inside, because both feel like progress.
Two more numbers set the boundaries. Sixteen experienced developers, working on their own repositories, were measured taking 19% longer with AI tools while estimating afterwards that they had been made 20% faster: a forty-point gap between performance and self-assessment, among professionals. And 5,179 support agents gained 14% on average, 34% if they were novices and roughly nothing if they were experts — these tools transmit known practice downward far better than they create judgement.
Put together: the model is strongest exactly where you are weakest, and the point at which it stops being reliable is the point you are least equipped to notice. So the operating rule under every page below is the same one the hint-only tutor implemented — do the thinking first, unaided, and let the model near the work at the stage where you can already grade its answer.
Designing things people use
Where a model produces the artefact in seconds and cannot tell you whether it is the right artefact.
Building software
The skills with the most evidence behind them, and the most uncomfortable evidence: measured speedups, measured slowdowns, and a large gap between the two and how it feels.
Building with AI models
5 stagesAI engineering · LLM application development · prompt engineering
The demo takes an afternoon. Everything after it is measurement — and the people who can measure are the ones who ship.
Programming and software development
5 stagescoding · software engineering · development
The model writes code faster than you can read it. Learning to program now means learning to read, test and reject it — which nobody automated.
Working with information
Writing and analysis — the two places where the output is the thinking, so delegating the output delegates the thinking unless you are careful about the order.
Data analysis
5 stagesanalytics · data science · statistics in practice
A model will write the query and explain the result. Neither tells you whether the number means what you think — and that was always the job.
Writing
4 stagesprofessional writing · technical writing · communication
Writing is thinking made checkable. A model can produce the prose, which means the thinking is now the only part that was ever yours.
Where this sits
These pages apply the general findings rather than restating them. The mechanisms underneath — why practising retrieval beats rereading, why the methods that work feel worse than the methods that do not, why difficulty that is desirable is the point rather than the cost — are set out with the evidence in how to learn anything. Every skill page names the principles it leans on and links to them.
And if the skill you are here to learn is a language, the methods pages are the equivalent for that: the approaches people actually use, compared honestly, including where they disagree with each other.
5 skills · 48 recommended resources · 23 cited studies and reports, each with what it measured and what kind of source it is.