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?
- 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?
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.
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.
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.
vouaobrasil•2h ago
juliansimioni•8m ago
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.