https://docs.renovatebot.com/

Warp is the only closed source terminal product I know of. Most other popular terminal emulators are open source already.

I feel like their funding is drying up and this is their last ditch effort to have the "community" build their product for them.

They claim agents will run the show, with inputs from community in the form of ideas/specs/direction. I wonder how long that will be sustainable for given the subsidized model prices are collapsing as we speak.

Is this an attempt to pivot to something else while the "community" keeps their first product alive? Maybe I'm being too cynical here, but I don't see this as an act of good faith, especially given their roots in VC funding.

I know... all content has to be served via a "server" but in case of OVH it's a full-blown hosting solution isn't it?

Besides, I'm sure GitHub wouldn't mind supporting Pandas documentation. They do it for a million other projects for free (even though they're not popular among the HN crowd these days)

His books are more plot driven and the characters are pretty flat, but it's so damn fun to read through!

Morgan Freeman has been trying to get the movie adaptation made since early 2000s and wants to play Commander Norton. I had read that Denis Villenueve (the same director from the new Dune movies) was attached to direct the adaptation, but it seems like his schedule is really busy. He recently finished filming Dune Messiah and then he's got the next James Bond movie to deliver.

Obviously, if this is true, the team at GitHub is failing to scale their infra to meet the workload demands.

Especially since everyone harps on about it but never provides concrete evidence. If your thinking has sharpened, surely you can find a way to demonstrate how.

I suspect it's one of those things where the user thinks they have improved but the reality is different.

It's called "The science of cycology: Failures to understand how everyday objects work" by Rebecca Lawson.

https://link.springer.com/content/pdf/10.3758/bf03195929.pdf

LLMs can barely remember the coding style I keep asking it to stick to despite numerous prompts, stuffing that guideline into my (whatever is the newest flavour of product-specific markdown file). They keep expanding the context window to work around that problem.

If they have something for long-term learning and growth that can help AI agents, they should be leveraging it for competitive advantage.

Debugging/profiling why it's gotten slow has mostly been an uphill battle for me. I tried using zprof which pointed that compdef and compinit were culprits. I tried changing my config to calculate compinit only once a day since most people reported it to work, but it never worked. This kind of stuff pokes and stabs at you endlessly.

OMZ being shell, and being a maze of a codebase, I couldn't track down if and where compinit was being called from even after the config change above, because all profilers pointed to the possibility of compinit being called twice.

I gave up and started using barebones zsh + starship because I do need a good prompt. Yet the issues persisted.

I recently started using fish + starship on my local machine so that I could evaluate it before committing to it at work. It's the fastest shell so far (maybe because its new, I intend to find out).

My only painpoint now is I have a bunch of utility functions I've maintained in bash that I need to port to fish because of the posix incompatibility.

OMZ is absolutely bloat.

Especially if it's a multi tenant architecture, it helps to have the cityHash64 caclulated as a combination of tenant ID and another column, so the overall amount of data scanned is lowered too.

We have tons of Confluence wikis, updated frequently.

People boast about the gains with LLMs all the damn time and I'm sceptical of it all unless I see their inputs.

I once ended up on the frontpage because of something I wrote: https://news.ycombinator.com/item?id=41689159

When I was in high school, I needed to automate downloading torrents (I was downloading tons). So I plugged together a bunch of tools including:

1. QBittorrent to run a FileBot script once the file was finished downloading.

2. FileBot script was a Groovy script that renamed and rearranged the contents into proper folders and

3. A small Python script that called the Telegram API to send me a notification that the download was complete.

Then I got into college and learnt they had a web portal which showed metrics like attendance (which turned out to be important) and test scores. So I wrote a Telegram Bot that would scrape these figures and save it into a database and run some calculations such as

1. Tell me how many lectures I needed to sit through to get to a required threshold.

2. If I decided to bunk college on certain days, how much attendance I'd end up losing.

Then I opened up this bot to allow my friends to register. Near the end of the first semester, the test scores were only available on the website but there was no direct link to that page from the public portal. I had found it out playing around on it and noticed they had directory listing enabled on some endpoints which led me to those "unlinked" but functional pages.

I wrote a neat feature which would allow querying this page and send a screenshot of it via my bot. I was running this entire thing on a Raspberry Pi 3B at my home and one morning I woke up to see logs from students I didn't know trying to use the bot (and ended up crashing it haha). Word had gotten around that test scores are accessible only through my bot.

It was one of the best projects I ever worked on. At its peak, I had 300 DAUs and I would hear from my friends in other departments that their entire batch is using Telegram solely for my program. I was also able to monetize it towards the end which felt nice.

These projects served as a learning tool for a lot of stuff for me. I learnt how to manage VMs, containerization, async I/O, DB and ORM integration, how to write good docs.

I still miss it.