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For most of their lives, most people have a rate of 0 learning because they aren't even trying to learn it.

And yet still unknown to more than 99.9% of the population (a conservative estimate).

Have you read this post on incorporating spaced repetition into teaching linear algebra?

https://bentilly.blogspot.com/2009/09/teaching-linear-algebr...

This isn't really an answer.

How are you checking the accuracy of the content? Especially if you plan to scale this to hundreds of courses, it doesn't seem like you actually have humans checking.

Fiber intake has a dose-dependent effect on cholesterol levels.

Obviously some people still need medication if they have particularly unfortunate genetics.

There isn't a conflict between cholesterol having a useful role in the body and too much being harmful.

There are mountains of evidence establishing a causal relationship between elevated cholesterol levels and heart disease.

I agree with the goals of the policy but I don't understand how it's enforced.

How do you determine if something is enhanced by AI versus just Photoshop or something else? Apart from being physically impossible, I suppose.

I think gstatic.com was down yesterday or something because a ton of websites just stopped working.

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.

Read Cal Newport's books on study habits.

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.

OCaml is such an obvious solution to their problem that I'm shocked it wasn't even mentioned. You get fast compile times without sacrificing type safety.

You can take advantage of spaced repetition just for scheduling the review of proofs and problems you've solved before.

By review, I mean attempting to solve them like you're seeing the problem statement for the first time.

You were actually using spaced repetition implicitly whereas they were using flashcards to cram.

The issue wasn't the flashcards but their own failure to use them effectively.

"Active recall" specifically (aka the testing effect [0]), as opposed to passive recall like rereading.

[0] https://en.wikipedia.org/wiki/Testing_effect

The thing about Scheme is that learning the syntax takes 10 minutes and then you can just focus on computation.

To the extent that you use AI at all, it should be to accelerate your own understanding in ways that are independently verifiable/falsifiable.

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.

Most UIs in practice boil down to state machines which are extremely amenable to formal verification.

Hillel Wayne's writing is a good starting place to learn more: https://www.hillelwayne.com/formally-specifying-uis/

Types replace entire classes of tests that coverage metrics wouldn't detect [0].

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

Ask (tell!) Jose to release the manga reader!

Talk to your doctor about getting evaluated for sleep apnea.

You have to actually practice the skill of communicating while solving a problem.

A land value tax makes way more sense.

Have you considered incorporating formal modelling?

Like:

[0] https://csci1710.github.io/2026/ and https://forge-fm.github.io/book/2026/

[1] https://elliotswart.github.io/pragmaticformalmodeling/

[2] https://quint.sh/

Everyone should Jimmy Koppel's post on what abstractions are and aren't: https://www.pathsensitive.com/2022/03/abstraction-not-what-y...

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.

The post explicitly makes the case for the filtering playing a role. Ctrl-F "Python".

To disambiguate search results in the future, I've had great luck appending "lang" like so: "roadmap 2026 rust lang".

But the point is that taking bad pictures doesn't help.

How to Design Programs: https://htdp.org/2026-2-25//Book/index.html

I don't have a dog and it would be very weird to get a dog for the sole purpose of having one for dating profile pics to meet women.

I don't have a dog and it would be very weird to get a dog for the sole purpose of having one for dating profile pics to meet women.

Notably none of these matter on dating apps where profile pics actually help you get matches so you can actually talk to a person.