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Make use of L1 wetware cache by learning how to do common things and dont make AI do them.

Start as early as possible in investing (in index funds) and otherwise being financially savvy. It is very beneficial to realise early on that growing your hard earned money and spending it wisely is way more important as it will in the future lead to some unexpected benefits. Freedom of thought and action!

Call Vanguard: 877-662-7447

An investing prof at Chicago puts this on the whiteboard at the start of semester, saying this is really all most people need to know and this class is unlikely to learn anything in his or any class that will let them, personally, do better.

That’s good advice for a layman but most high earners can do much better if they care and are motivated. Most are neither though lol.

Mostly on the tax side. Some specific examples:

- after maxing out your 401k what should you do next? IRA? Mega backdoor roth? Something else?

- If you have kids, how to best save for future education expenses? Hint: consider 529 plan.

- HSA is technically the best tax advantaged account, most high earners don’t realize it and “waste” the HSA funds to reimburse typical medical bills. HSA has triple tax benefits: contributions are tax-free, growth is tax-free, and withdrawals are also tax-free after age 65 for any reason, not just medical expenses. So basically investing without any tax obligation. You can also withdraw tax free before 65, but for medical expenses only.

i could go on…investing is great, but reducing your tax obligation is an even more powerful technique if you want to grow your net worth.

#1 Rule of Investing: you can't beat the market, but you can beat the tax man

What you have stated is almost the same as call Vanguard, all those options are the same in the sense that they all involve investing, leaving it alone for a long time. Its just the vehicle thats slightly different and tax advantages.

I wouldn’t consider those options needing much motivation or research. The key with all of them is investing early and leaving it alone.

If one is clueless with investing and taxes in general, and they call vanguard, their eyes will glaze over. It would be like me explaining software development to my 85 year old father.

I do agree people should call vanguard. But just blindly following steps they give you is unlikely to be productive if you don’t understand why you’re doing those steps. Furthermore, those people who don’t understand _why_ will freak out every time there’s a huge market correction. They get scared - because they don’t understand any of it.

I’m also curious, do they offer financial advice for your accounts outside vanguard? Genuinely curious since i’m unsure.

I’ve think the “call” part is a bit from the past, should be a setup account online with Vanguard, put it in VOO or VTSAX or the equivalent low fee market index fund and leave it alone.

Replace Vanguard with any other firm but the key is picking low fee ETFs and leaving them alone. Vanguard tends to have a reputation for the lowest fees.

At that point get someone to do it for you for x% of what they're getting you back and live blissfully unaware of arcane tax code specifics.

At least the 401k, IRA, and HSA don't require knowing anything particularly arcane. Money goes in, don't touch until 59 1/2 (401k, IRA) or 65 (HSA).

529 plans can get a bit more complicated because you'll want one from your state (if your state has an income tax) and they may offer several, but then it's less about knowing tax code specifics than about what the differences are between their offerings.

right, it’s not that arcane at all. I discovered all this over a couple weekends in my 20s. Started on reddit, then moved on to more official guides and books. I spent maybe 5 weekends in total doing this learning.

It’s really not that hard and i don’t understand why more people aren’t interested. Let’s reframe for a minute…if i said a high earner could retire a year earlier, or maybe even a few years earlier just by learning some semi-advanced tax strategies. Should they do so? Yeah. They’d be crazy not to lol.

529s are also capped based on the recipient, not donor.

My millionaire, step-father-in-law, gave this advice to my brother when graduated.

I was lucky, my physics department administrator told me the same thing when I was graduating.

The 2ND best piece of advice is to rollover your 401k when you move to a new company -> this cost me at least 500k because they effectively stagnate when your company isn't paying the maintenance cost (AIUI).

> this cost me at least 500k because they effectively stagnate when your company isn't paying the maintenance cost

Is this true? My understanding is that the fees come out of the account itself. There's other good reasons to roll over (primarily investment flexibility) but I have not heard of something like this.

Get a financial advisor that you trust.

Always have a stack of deli cups handy.

Most problems (including analytically intractible ones) can be modeled with a relatively simple monte-carlo simulation. Most simple monte-carlo simulations can be fully implemented in a spreadsheet.

Using timing coincidences in particle physics experiments is incredibly powerful. If multiple products from the same reaction can be measured at once, it's usually worth looking into.

Circular saws using wood cutting blades with carbide teeth can cut aluminum plates.

You can handle and attach atomically thin metal foils to things by floating them on water.

Use library search tools and academic databases. They are entirely superior to web search and AI.

I feel like the Monte-Carlo simulation modeling trick is one I picked up intuitively but only recently heard formalized. Do you (or anyone else) have a list of example problems that are solved in this way? Like a compendium of case studies on how to apply this trick to real world problems?

_How to Measure Anything_ by Douglas Hubbard includes a chapter on Monte Carlo simulations and comes with downloadable Excel examples: https://www.howtomeasureanything.com/3rd-edition/ (scroll down to Ch. 6)

The main example is, you're considering leasing new equipment that might save you money. What's the risk that it will actually cost more, considering various ranges of potential numbers (and distributions)?

I think it's harder to apply to software since there are more unknowns (or the unknowns are fatter-tailed) but I still liked the book just for the philosophical framing at the beginning: you want to the measure things because they help you make decisions; you don't need perfect measurements since reducing the range of uncertainty is often enough to make the decision.

A simple example that highlights the strength of this method: a 137Cs point source is at the origin. A detector consisting of a right cylinder at arbitrary distance and orientation is nearby. What is the solid angle?

There may exist an analytical solution for this, but I wouldn't trust myself to derive it correctly. It would certainly be a huge mess.

If we add that the source is also a right cylinder instead of point source, and we want to add first order attenuation of emitted gammas by the source itself, the spreadsheet becomes only a bit more complex, but there will not be a pen and paper equation solution.

In this example every row of the spreadsheet would represent a hypothetical ray. One could randomly choose a location in the source, a random trajectory, and check if the photon intersects the detector. An alternative approach would be randomly choosing points in both target and detector, then doing additional math.

The results are recovered by making histograms and computing stats on the outputs of all the rows. You probably need a few thousand for most things at least. Remember roughly speaking 10k hits gets you ~1% statistics.

not sure if it counts as a list of case studies, but a relevant and recent video nonetheless https://www.youtube.com/watch?v=KZeIEiBrT_w

also in general bayesian statistics

random medium article: https://medium.com/pythoneers/monte-carlo-simulation-ideas-a...

The big one, for keeping my focus on the power of repeated, consistent action, and prioritizing my "future selves":

What is likely to happen if I do (or don't do) this thing one thousand days (or times) in a row?

Examples:

- exercising 2h per day and eating right --> I'm going to look and feel great and my health will be far better than that of my peers

- Should I buy these cookies along with the rest of my groceries? If I do that 1,000 grocery trips in a row …

- spending 30+ minutes per day reading the highest quality material I can find; taking notes; and figuring out ways to implement the knowledge and ideas I gain --> …

I like your approach to relating your daily choices to your broader life goals.

I think you'd like Atomic Habits [1] if you haven't read it already.

[1] https://www.amazon.com/Atomic-Habits-Proven-Build-Break/dp/0...

I only learned this in the last five years: do less, automate less, do more by hand, and use the limited capability of the manual method to really choose projects that are worthwile, rather than aim for maximum efficiency.

Similar to this: if you want to optimize your productivity*, do so on a timescale of at least weeks if not months or years.

Simple example: Can you get more done working 12 hours a day than 8? Sure, for the first day. Second day maybe. But after weeks, you're worse off in one way or another.

It's easy to chase imaginary gains like automating repetitive tasks that don't actually materialize, but some basics like sleep, nutrition, happiness, etc are 100% going to affect you going forward.

* I actually hate that word, and prefer saying "effectiveness". Productivity implies the only objective is more, more, more, endlessly. Effectiveness opens up the possibility that you achieve better results with less.

> What Trick of the Trade took you too long to learn?

"Everything worth doing is worth doing badly"

And as a corollary, every complex system that works came from a simple system that works.

I learned this in programming, but now I apply it on everything from motorcycle maintenance, home appliance repair to parenting.

--

Often the easier way to fix a complex system is to pretend that it could be simpler and then reintroduce the complexity-inducing requirements.

I had a professor who taught debugging as a whole another skill from programming and used to say "Most of programming is starting from an empty editor and debugging until your code works".

The debugging "lab" in Java course (in the year 2000) was one of my transformational after-school classes - where I got a java program which fits within 2-3 pages of print code with a bug and was told to go find it in print for ~20 minutes, then given 40 minutes with a debugger instead.

> And as a corollary, every complex system that works came from a simple system that works.

"Do the simplest thing that works" is one of the few core architecture principles I stick my neck out for time and time again. Why write a simple function when you can spend a week accounting for every imagined corner case and implement modular expansion capabilities! Please... stop...

I empathize with the debugger story. If you're super deep in a language it makes sense to know the debugger inside and out. But stdout is universal and I've never been a specific language developer rather than being able to jump into whatever is needed.

Writing tests first is a good way to end up with testable code. If you skip that, retrofitting tests is incredibly difficult.

While it can be a useful forcing function, I find it also just fits into a higher velocity workflow in general, one I would describe like so:

1. Make PRs small, but not as small as you can possibly make them.

2. Intend to write at least one nice-ish test suite that tests like 50-80% of the LOC in the PR. Don't try to unit test the entire thing, that's not a unit test. And if something is intrinsically hard to test - requires extensive mocking etc - let it go instead of writing a really brittle test.

3. Tests only do two things: help you make the code correct right now, or help the company keep the code right long term. If your test doesn't do either, don't write it.

4. Ok - now code. And just keep in mind you're the poor sod who's gonna have to test it, so try to factor most of the interesting stuff to not require extensive mocking or shit tons of state.

I've found this workflow works almost anywhere and on almost any project or code. It doesn't require any dogmatic beliefs in PR sizes or test coverages. And it helps prevent the evils that dogmatic beliefs often lead you into. It just asks you to keep your eyes open and don't paint yourself into a corner, short term or long term.

One more piece - if the test would be hard to write, use that to drive you to clean up the architecture of that piece of code.

Even if you aren't going to do the complete test code just writing down the expected checks for each test makes things so much easier

Git bisect. For certain classes of software regressions, it makes life easier. Many people (me) don’t know this feature exists and end up reinventing the wheel on their own. https://git-scm.com/docs/git-bisect

Technical skills will only take you so far in most orgs. Learn to play the soft game.

How do you maintain tests, in order for LLM edits to not keep breaking things?

  - As a formal test suite in the program's own language?
  - Or using a .md natural language "tests" collection that must pass, which an LLM can understand?

Observe as much mastery as possible at what you would like to do.

Apprentice, journeyman, master: worked for millennia, will work for millennia more.

When I realized that a) `screen` exists and b) what it does, I felt like an utter fool for having gone for years—YEARS—without benefiting from it.

Measure everything. There are two benefits to this.

1. Discarding the bullshit. A consistent practice of weighting assumptions and conclusions on evidence/numbers helps identify biases and motives from other people.

2. Measures allow for value identification and performance. Most people just guess at this. Guessing is wrong more than 80% of the time and often wrong by multiple orders of magnitude.

Most people don’t think like this and find this line of thinking completely foreign, so I often just keep my conclusions to myself. To see a movie about this watch Money Ball.

This is interesting. I’ve often thought about building a dashboard for my personal life, comparable to the dashboards I build for growth teams.

And then iterating on it over time, and I find what’s valuable and what’s not.

Drum cards

That macros ruin everything they touch. I used them extensively for maybe 15 years, stopped adding them, and then a bit later removed them all from my code. My C/C++ code was a lot nicer without them.

My early C code would have been awfully slow without them. We needed enums and good inlining before we could ditch (most) macros. When did Zorland/Zortech C become good enough?

There are still a few special cases where macros are useful, such as the multiple #include trick where a macro #defined before the #include determines what the macro invocations in the include file does -- really helpful for building certain kinds of tables.

Zortech had an inliner even before it was Zortech.

The #include trick is called the "X Macro". I used it extensively, and eventually just removed it.

Was it reliable enough?

(I have never played with it -- I saw the ads in Byte but I never met anybody who had tried it. It seemed so ridiculously cheap that I felt it had to be a scam ;) )

It was frequently better and faster than the others. Mine was the first (for the PC) to add data flow analysis.