People feel differently about AI, and here at Firefox, we think that is completely reasonable. Something else that is completely reasonable: deciding for yourself how and when you engage with AI features.

For some of you, AI is part of your everyday life, whether you are using it to summarize a large amount of information, brainstorm ideas for work, or research trips and personal purchases. Some of you interact with AI as little as possible, and prefer to keep it that way. And a lot of you are somewhere in between: curious, but exploring on your own terms and at your own pace.

Your personal use of AI is just that, personal. Firefox offers various levels of AI integration into your browser, and the choice between them is entirely yours.

Block new and current AI features in a single switch

Opting out of upcoming and current AI features on your browser should not require endless navigation through multiple Settings pages. That’s why Firefox offers an AI controls section within its General Settings panel. A single, easily located place where you can block current and future AI features and related pop-ups with the swipe of a toggle.

Not only do we want people to have the choice to remove certain AI features from their Firefox browsing experience, we make sure doing so is as easy and accessible as possible.

Choose the features that work for you

For the many people who sit in the middle of the AI usage spectrum, we made sure you can opt in and out of specific features in line with your preferences. Capabilities like AI translations, image alt text in Firefox PDF viewer, tab group suggestions, and key points in link previews can all be individually switched on and off, ensuring you can enjoy such offerings on a case by case basis as it suits your needs. 

In addition, if there is an AI chatbot provider you already trust or pay for, you can use it directly inside Firefox’s built-in desktop sidebar. This means you can use your chatbot of choice and browse side by side without ping-ponging between tabs.

While some browsers integrate a singular AI model or chatbot into their system, this can restrict flexibility and concentrate data sharing. Firefox prioritizes transparency and user control by letting you select from multiple providers, allowing you to review each option’s policies before you engage with them.

You can turn on AI chatbot providers in the AI controls section of browser settings and select one of the following: Anthropic Claude, ChatGPT, Google Gemini, and Le Chat Mistral. Once this feature is turned on, you can switch between chatbots within the sidebar itself based on your preferences and task at hand.

Smart Window, for when you want help finishing what you started

Smart Window is Firefox’s most integrated AI experience, but that doesn’t mean it compromises our commitment to choice, privacy, and transparency. Our newest window type, which we’ve been polishing and testing in beta, uses only the context you share with it to help you move work forward and across the finish line.

When permitted by you, its built-in, AI-powered assistant can work directly with your open tabs and browsing history to connect the dots. This means comparing information, generating recommendations, summarizing pages, and planning projects without having to feed every crumb of context from your previous and current browsing activity each time you enter a new prompt.

As we’ve built out Smart Window, we’ve added a few additional features to align its design with how people actually browse. These include the ability to group related tabs together – so you can make sense of what’s open without spending time organizing everything yourself – and visual history previews that help you spot a page you visited earlier when you can’t remember the exact URL or phrase searched. In addition, a new partnership with Exa enables Smart Window to not only locate current web information to include in responses, but also display the sources behind these responses so you can verify what you’re seeing, without breaking your flow.

We understand people use different Firefox windows for different reasons, and often switch between options based on the task at hand. Smart Window is the window you reach for when your browsing turns into a project. When your quick search becomes inspo for the girls’ trip you’ve been meaning to plan, or finding the perfect gift for your partner becomes a dozen tabs comparing prices and reviews, turn the window you’re already using into a Smart Window. Your tabs and progress stay in place while Smart Window helps organize the task and move it forward. Use it for one complex project, use it all the time, or switch it back when you’re done.

Smart Window remains in beta as we continue to learn and improve from our community’s feedback. At present, it’s available in English to people in the U.S. and Canada.

To try Smart Window, visit: https://www.firefox.com/smart-window

Always your call

Your opinions and preferences on AI usage are individual to you.

We don’t think there is one right answer for how and when to engage with AI, and we’re not going to pretend there is one. What we can do is make sure that whatever level of engagement is right for you, Firefox supports it well. Because the only person telling you how much AI you need should be you.

The post AI on your terms: Firefox meets you where you are appeared first on The Mozilla Blog.

Learn T-SQL With Erik: Cross Table Date Math

Chapters

• 00:00:00 – Introduction
• 00:01:48 – Slow Query Analysis
• 00:04:37 – Optimizing Cross-Table Queries
• 00:06:53 – Indexed Views Explained
• 00:09:02 – Conclusion

Full Transcript

Erik Darling here with Darling Data, enjoying a lovely LaCroix Pamplemousse seltzer. No booze in that whatsoever. Can you believe how lucky we are to enjoy a non-alcoholic beverage? Anyway, we’re going to do some more Learn T-SQL with Erik. In this video, we’re going to talk about cross-table date math, and I am going to catch myself and a funny little bit of irony in this one. Down in the video description, if you would like to purchase the full training content, there is a link with a coupon code attached to it down in the video description. Just below me here, just below this lovely fold here. There are also links for you to do other things, like hire me for consulting, become a supporting member of the channel, ask me Office Hours questions, and you can also, while you’re down there, like, subscribe, and tell all of your friends. Your beautiful, wonderful friends who would just benefit so greatly from watching these videos. If you are in the market for free SQL Server performance and availability group recently monitoring, you can get mine. There’s also links for this stuff. Totally free, totally open source, no phoning home, no weird stuff.

A brand new sort of version of the monitoring tool is available. Let’s go to Postgres and Timescale backend, and it has a headless Windows service, and it can monitor up to 500 servers, again, totally for free. It doesn’t cost you. It doesn’t cost you more if you want to monitor more than 500 servers. I would just maybe start a second install to monitor the other 500, because concurrency for that many servers, even in the wonderful world of Postgres, is maybe not so much fun. But, but let’s talk T-SQL here. That is, that is the turkey that we care about.

So, so we’re going to use this query, which, if I remember its provenance correctly, came from the Stack Data Explorer site. I can just never find it when I go look there again. But it’s, it’s, it’s, it’s the intent of the query is to find posts that had a lot of very early upvotes, and this query was always very slow, and to me, the interesting part of the query was that the where clause was looking for a date diff in columns on two tables. Now, under normal circumstances, if you had both of these columns in the same table, right, you could, you could, if you were denormalized a bit, but this would be a terrible denormalization.

You could create a computed column, but them being cross table, you don’t get that. SQL Server 2005 or so had this feature called the date correlation optimization, which could help in cases like this, but it required a lot of stuff, like, like a unique index on one of them. Which you can’t always get, and a foreign key between the two of them, which you can’t always get, because your data is filthy and cackadoodoo dirty because of your, all your nolak hints and whatever.

I don’t know, whatever. Let’s just go, go along with it. It’s funny.

So, it would be very hard to get that set up, but you, nothing is stopping you from creating an indexed view that can do the same or a similar thing. Now, this query runs for about, oh, five, six seconds or so. Oh, we got, we got a big five and a half second thing there.

And, you know, like one, like, this is not the thing I wanted to look at. It was being very silly. But, sort of, like, the important thing here is that, like, you know, you can, like, there’s only so much you can filter until the tables kind of get joined together, and you can finally apply, like, some of those filters, like the date diff one here, right?

The date diff in hours is less than or equal to 168, which is seven days, right? So, you have to, like, get all the rows from both tables and then do the join, and then you can start doing other things. And then you can start filtering your results to where they’re greater than or equal to 50.

And that’s fine, but, you know, if you want this type of query to be much faster, there are some things you have to do, right? So, you know, like, you might not find it very useful to seek to 40 million rows. I know I sure wouldn’t, but this is the way the votes table kind of breaks down.

So, you know, like, anything in here is going to not be fun. Like, nothing about this is going to be enjoyable. So, what I would recommend here is, especially if you are not in a situation where you can get the date correlation stuff working naturally out of the box, one thing I just want to point out about the original query, I’m going to make you sit through about five and a half more seconds of runtime here, is that, like, the majority, if not the total of these operators, aside from gather streams, are all happening in batch mode already, right?

Like, this is a nearly entirely batch mode query, and so, like, you’re already getting a lot of, like, the oomph that you would get out of this. You know, like, I guess if you want to add a non-clustered columnstore index there, you could, but we’re going to look at a slightly different way of handling it.

So, let’s come on down here, and what we’re going to do is we’re going to take a portion of the query that makes for a good indexed view. It’s not the full query, because I’ve talked about in other videos where we talk about indexed views. Making overly specified, overly specific indexed views will largely lead to those indexed views not being used by queries that could potentially benefit from them.

So, looking at all the, like, this is just, like, the base query that I would start with in here, and the idea behind it is just to get this part sort of squared away, right? So, we’ll create our unique clustered index as required in order to create other indexes.

And then there’s a neat trick with indexed views. Now, the indexed view documentation has some stuff about columnstore indexes. You can obviously not create a clustered columnstore index on an indexed view, because you can’t create a unique one, and the indexed view needs that.

But you can create a non-clustered columnstore index over an indexed view, and that can sometimes get you a very, very good mix of both the pre-aggregate and the batch mode that you would want. Did I actually run that?

It just happened very quickly. So, this all happened, it all happened in the blink of an eye. And now we can sort of, we can run this query, right, where we can get our sort of pre-aggregated list of stuff from the indexed view that has a count big of greater than or equal to 50, just like our original query.

And then we can join to our, just those rows to our query, and we can get ourselves a wonderful result that goes a lot faster. This all finishes in, well, because this is all happening in batch mode, we have to, and there’s no parallelism, we have to go look over here, and that the query time stats, and we’ll see this finished in 500 milliseconds of wall clock time with 460 milliseconds, 462 milliseconds of CPU time.

So, if you’re in an environment where these types of queries really have to be front and center fast, indexed views can go a long way to making them much, much faster. There are, of course, many caveats and drawbacks to indexed views.

Maintaining them on modification can be somewhat painful. And for this one specifically, which is something I’ve talked about many times in many other videos, when you have a cross-table index, when you have an index view with a join in it between one or more tables, not lock escalation, but isolation-level escalation can get pretty out of control.

You’ll also end up seeing a lot of serializable stuff that you didn’t ask for. SQL Server just does it automatically. So, you do have to be pretty careful and, you know, pretty conservative with how many indexed views you’re using and all that stuff.

But under the right circumstances, and especially if you start getting real crazy and creating non-clustered columnstore indexes on your indexed views, you can do a lot of really, really neat tuning stuff if the workload demands it.

Anyway, thank you for watching. I hope you enjoyed yourselves. I hope you learned something. I hope you’ll purchase the full course that this was just a tiny, itty-bitty little taste of and, yeah, all that stuff.

All right, cool. Thank you for watching.

Going Further

If this is the kind of SQL Server stuff you love learning about, you’ll love my training. Blog readers get 25% off the Everything Bundle — over 100 hours of performance tuning content. Need hands-on help? I offer consulting engagements from targeted investigations to ongoing retainers. Want a quick sanity check before committing to a full engagement? Schedule a call — no commitment required.

The post Learn T-SQL With Erik: Cross Table Date Math appeared first on Darling Data.

A user asked for per-solution color themes. It already ships, and it goes further than they asked.

You run several instances of Visual Studio side by side, one per solution, and they all look identical. Same taskbar icon, same alt-tab thumbnail, same chrome. So, you land in the wrong one, start typing, and realize thirty seconds later you just edited the wrong repo. Could each solution get its own color theme?

It can. It already does. And the way it works turns out to be more useful than a personal color preference.

How to do it

1. Open Tools > Options.
2. At the top of the window, find the Applies to dropdown and switch it from your user profile to the current solution.
3. Change the color theme.

This uses the new settings experience introduced in Visual Studio 2026.

That’s the whole thing. From that point on, every setting you change applies only to the solution that’s open. Close it, reopen it tomorrow, and the theme comes back with it. Open a different solution and you get its color instead.

No restart, no Apply button, no dialog to dismiss. Most setting changes take effect immediately, and the theme is one of them. The window changes color while you’re still looking at it.

Pick colors with real contrast between the solutions you keep open together. Dark for the service, Blue for the client, Light for the sandbox. The goal is telling them apart from your peripheral vision, not having to read the title bar.

Why this works now

The Applies to dropdown isn’t a color feature. It’s the scoping model behind the new settings experience, and the theme just happens to be the most visible thing you can point at it.

In the old Tools > Options, every page owned its own UI, and settings were a flat, global, machine-wide pile. The new experience puts them all in one consistent, searchable surface backed by JSON, and once settings have a real schema, they can have a real scope. “This value, for this solution” becomes something the IDE can express.

So, the color theme is the demo, not the feature. The feature is that settings now have a scope and a file, and a file is something you can put in source control.

The JSON underneath, and why your team cares

Per-solution settings live in a file called settings.VisualStudio.json, in the solution root folder, right next to your .sln or .slnx. That location is the point.

Commit it, and everyone who clones the repo gets the same setup. A new teammate opens the solution on day one and the IDE already looks and behaves the way the team agreed it should, with no onboarding doc that starts with “first, go to Tools > Options and change these nine things.”

Don’t want to impose your taste on everyone? Add it to .gitignore and it stays yours alone. Same feature, same file. One line decides whether it’s a team convention or a personal preference, and you decide it per repo, after the fact, by whether you commit.

If you’d rather work in the raw values than UI, select Edit user settings as JSON from the toolbar. The file opens showing only what you’ve changed from the defaults, not thousands of lines of untouched values. Edit them there directly or copy a single setting to the clipboard to hand to someone else, which beats screenshotting a checkbox into a Teams chat.

One thing to know

Per-solution settings are stored separately from your user settings, so changing the scope doesn’t overwrite the setup you use everywhere else. Switch the Applies to dropdown back to your user profile whenever you want to change the default for all solutions.

That separation also makes experimentation low risk. Give one solution a distinctive theme, see whether it helps, and remove the solution-level value if it doesn’t. Visual Studio falls back to your user setting without requiring you to reconstruct it.

If you want to go further

Long before this shipped, an extension called Solution Colors solved the same problem from a different angle. It’s color only, and it’s more granular: instead of switching the whole theme, it tints specific parts of the IDE per solution, and it can pick a color automatically, so you don’t have to decide anything.

If per-solution themes are enough, use the built-in feature. It’s supported, it syncs, and it’s checkable into source control. If you want finer control over exactly which pixels change color, the extension is still there and still worth a look.

Try it

Open your two most-confusable solutions and give them different themes. Fifteen seconds each, and it pays you back every time you switch windows.

Then, if it’s useful to more than just you, commit settings.VisualStudio.json. Your team gets the same visual cue for free, and the next person who joins never opens the wrong window at all.

If there’s another setting you want scoped per solution, tell us in the comments. The plumbing is there now.

The post Stop alt-tabbing into the wrong Visual Studio appeared first on Visual Studio Blog.

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Giles Edwards-Alexander reports that during an experiment to see how productive a team could be using fully agentic engineering practices, the team accidentally prompted the agents into creating a blackboard coordination system inside the git repository.

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