Ask HN: What trick of the trade took you too long to learn?
Every week for the last 3 months I’ve learned a new trick when it comes to getting whatever LLM I’m using at the time to produce better output. That’s my trade, but lots of HNers have more interesting trades than that.
In my case, only recently I learned the value of getting an LLM to write and refine a plan.md architecture doc first, and for it to break that doc down into testable phases, and then to implement phase by phase.
Seems obvious in hindsight. But it took too long to learn that that should be my approach. I had been going phase by phase myself- no overarching plan.md for the LLM.
What Trick of the Trade took you too long to learn?
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[ 2.7 ms ] story [ 127 ms ] threadSimple 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.
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.
Never let tests depend on implementation details.
https://www.youtube.com/watch?v=NyiMOmCqu00
In tests in a web application/api, your tests can actually be real use cases quite easily and design your api around real use cases.
How would you do that in a game? Check a frame looks a certain way?
I have done proper testing a puzzle game where the game can be represented by abstract state. But modern 3d rending is hard to test well.
Where you are going to run into difficulty in testing is if your APIs are so complex that it's all but impossible to exercise all code paths by testing with different parameters, or if functions have global side effects (bad practice).
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.
This is a fantastic course. It covers a lot of ground.
If you want to actively invest, this will help you learn the mechanics. But in the end, what you really learn, is that you can't beat the market.
https://ocw.mit.edu/courses/15-401-finance-theory-i-fall-200...
[1]: https://github.com/tmux/tmux/wiki
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.
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 --> …
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.
"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.
journal before you start your day
buy some sort of electric kettle