johnh-hn

There is a bug on the current openings page:

1. Click to open either the Department or Location dropdown

2. Click, and hold, with the intent to drag the scrollbar

Expected: I can scroll through the options.

Actual: It selects the item under the mouse cursor.

Browser: Latest Firefox.

I'm not sure I'd call it furniture, but are you maybe referring to the luggage?

Dapper is fantastic, and I'm happy to see it getting some love. It does exactly what I want: provides strongly-typed mapping and protects against SQL injection. It makes it easy to create domain-specific repositories without leaking anything.

In contrast, every company I've joined that used Entity Framework had enterprise products that ended up being a tightly coupled mess from IQueryable<T> being passed around like the world's favourite shotgun.

Ah, I was wondering about that. Flagging didn't seem like quite the right thing to do, but at the same time I don't see a reason to leave bots hanging around.

Thanks Gary, I'll use that next time.

This is a bot. It's even copied the typo from the top comment.

If the checkbox you're referring to is the "Use AI to suggest tabs and a name for tab groups" one, then I can't see what setting it changes. It's not the browser.ml.enable flag. I tried unchecking it, restarting the browser, and that flag was unaffected. This is in version 144.0.2.

Searching for "AI" shows one other setting: "Quickly access bookmarks, tabs from your phone, AI chatbots, and more without leaving your main view." But I'd already disabled that apparently. Despite that, there are plenty of flags that were enabled mentioned in the article.

In your address bar type: about:config

You can search for the configuration options mentioned in the article (e.g. browser.ml.enable) in there.

Just in case you never came across it, I think the second game is much better than the first one. Enjoy the nostalgia trip!

You nailed it. Well done!

It reminds me of a quote from Designing Data-Intensive Applications by Martin Kleppmann. It goes something like, "For distributed systems, we're trying to create a reliable system out of a set of unreliable components." In a similar fashion, we're trying to get reliable results from an unreliable process (i.e. prompting LLMs to do what we ask).

The difficulties of working with distributed systems are well known but it took a lot of research to get there. The uncertain part is whether research will help overcome the issues of using LLMs, or whether we're really just gambling (in the literal sense) at scale.

I think this is only half of it.

Years ago, I worked at a company where my time was split between working on a bespoke platform for an older client and a generic platform that would be used for all clients going forward. The bespoke platform was essentially being used to fund the development of the generic platform.

The contrast between the two was stark: the bespoke platform was legacy in all its weird glory, and the generic platform was considerably higher quality. Seeing that contrast up close, and flipping between working on each one, was immensely useful to me. It made it clearer why I favour certain approaches over others, and it made concepts easier to explain to others.

Since then, I'm of the opinion you should aim to work with both the good and the bad to clarify the "why" of things.

Much appreciated! I'll give this a go and see how far I get.