1,910 karma · joined March 15, 2016
Spotify on Android got an order of magnitude slower recently.
These are just the examples that come to mind that I've dealt with from the last 48 hours.
Learn to use Anki to leverage spaced repetition to intentionally put things into your long term memory. This step comes after understanding though.
Don't rely on AI to do anything you don't know how to do yourself. (You can use it to learn, but then make sure you independently verify and internalize the information.)
Use Math Academy to learn math ahead of time. Then take as much math as you can.
Use pen and paper to do your thinking and problem solving before writing a line of code.
By review, I mean attempting to solve them like you're seeing the problem statement for the first time.
The issue wasn't the flashcards but their own failure to use them effectively.
AI amplifies what you are.
If you take shortcuts in your education, you will remain mediocre.
If you dive deep in your understanding, building a broad and deep foundation, then you will be exponentially more powerful.
Hillel Wayne's writing is a good starting place to learn more: https://www.hillelwayne.com/formally-specifying-uis/
Types are also documentation!
They also decrease the degrees of freedom LLMs have to make mistakes [1].
[0] https://kevinmahoney.co.uk/articles/tests-vs-types/
[1] https://john.regehr.org/writing/zero_dof_programming.html
Like:
[0] https://csci1710.github.io/2026/ and https://forge-fm.github.io/book/2026/
Anyone claiming LLMs are an a higher level of abstraction are not using it in the way used by programmers and computer scientists.
They're usually conflating "delegation" and "abstraction", as if a junior developer is an abstraction.
It can take you from knowing your multiplication tables all the way to all the math you need for an engineering and/or CS degree.
You could take Harvard's CS50 and then tackle it.