used to be one of the “sharers,” maintaining a fairly popular blog, writing tutorials on platforms like DZone and CodeProject, answering questions on StackOverflow, and creating open-source projects that collectively amassed millions of downloads.
At one point, I decided to monetize one of my open-source projects by creating a commercial fork. That’s when a group of people, none of whom had contributed to the project in any way, started a witch hunt over a few super trivial lines of code they accused me of “stealing” from contributors. Despite having the full support of all actual contributors, the backlash from these outsiders left me drained and disillusioned. So I stopped sharing my work and contributing to open source altogether—and honestly, I’m happier for it.
To all the Jimmy Millers who genuinely appreciate the goodwill of creators: be aware that there are people who will leech off it or even destroy it.
This series got me into coding languages for work and fun. I wish more books about complex topics were written this way... For anyone who's interested, Jack Crenshaw did an interview in 2009 and touched upon how he wrote this series. [1]
Okay, maybe I shouldn't have mentioned the worst possible outcome. Let's use the words of Sam Altman, the risk here is "light out for all of us", and let's just assume it meant we would still live, just in darkness. Or whatever plausible bad case outcome you could imagine. Do you see any negative outcome is possible at all? If you do, would you at least be cautious so that we could avoid such an outcome? That would be the behavior I expect to see in leading AI scientists and yet...
You disagreed with me, but at least you acknowledged there was risk, even though we could disagree about the odd or potential impact. Yet, folks like Yann LeCun ridiculed anyone who thought there was a risk AI could endanger us or harm our way of life. What do we know about experts who are always confident (usually on TV) about things that haven't happened yet?
What I found disheartening was many of those scientists, especially those on the "nothing to worry about" camp, seemed not to entertain the thought that they could be wrong, considering the scale of the matter, i.e. human extinction. If there's a chance AI poses an existential threat to us, even if it is 0.00000001% (I made that up), should they be at least a bit more humble? This is uncharted domain and I find it incredible that many talk like they already have all the answers.
They lost their money on the short position because the price went up, instead of going down. Had other people noticed about the hack as early as they had assumed and the price went down as they had assumed, they would have made a lot of money.
I used to maintain several popular open-source projects and contribute to even more popular ones. It was always fun at the beginning, especially because I built them for my own needs. But I kept getting asked to fix bugs or improve things even long after my needs had expired. I tried the donation route for a little while but it didn't go anywhere - I received maybe a few hours worth of money (versus hundreds if not thousands of hours I had spent working on those projects). I also tried releasing a paid version for one of the projects and got buried with hate mails and, unfortunately, online abuse. That was when I stopped working on open-source and I'm happier than ever.
I'm very happy for people who make it from doing serious open-source work. I think they deserve it. But at the same time I feel bad for those who build or maintain no less serious or popular work and yet couldn't make enough to worth even a portion of the time they'd spend.
Start by adding breakpoints for some key actions of the app. Then step through the flows with the debugger. First pass you can just step over functions to get the high-level idea. In subsequent passes, you can step into functions that seem important. Rinse and repeat until you understand those actions well. Then move on to other areas in the app.
This works because you can see the actual end-to-end execution flow (not always clear from reading code), inspect runtime data (impossible by reading code) and even change the runtime data (variables, DOM) to validate assumptions about how the code works.
> what relevant software have they actually written
I think Fitnesse [1] is quite relevant. That said, not a lot of FOSS work from someone like him, to put the things he preaches in large and complex projects that we can look at the source and learn from.
Thanks. I do prefer an all-in-one option so this looks promising. The website says v3 is beta and not ready for "production use". Have you encountered major issues with it?
Thanks. What do you think about SvelteKit? I looked at Svelte, liked it a bit and went on to explore SvelteKit to see how the API/SSR/route was handled but I couldn't get through their docs. Maybe I should find a better tutorial to evaluate it.
At one point, I decided to monetize one of my open-source projects by creating a commercial fork. That’s when a group of people, none of whom had contributed to the project in any way, started a witch hunt over a few super trivial lines of code they accused me of “stealing” from contributors. Despite having the full support of all actual contributors, the backlash from these outsiders left me drained and disillusioned. So I stopped sharing my work and contributing to open source altogether—and honestly, I’m happier for it.
To all the Jimmy Millers who genuinely appreciate the goodwill of creators: be aware that there are people who will leech off it or even destroy it.