Proton Mail Wants to Organize Your Emails Automatically

Proton Mail (partner link), the service people turn to for escaping Big Tech, has rolled out "Categories" as a new inbox view that automatically sorts incoming email into six groups: Primary, Social, Promotions, Newsletters, Transactions, and Updates.

When you receive a new mail, it gets sorted automatically into one of six categories based on metadata, without Proton reading the contents of the message. This is what Gmail already introduced years ago and it does work for most parts.

How does it work?

By default, Primary houses personal and work-related messages along with any important updates; Social covers social media updates and activity notifications; Promotions covers discounts and sales offers; and Newsletters carries news content you signed up for.

The other two categories can be enabled via the Settings if you require them.

Of course, we are not claiming that this is something revolutionary. Gmail and Outlook have offered inbox tabs for years, but they achieved that by scanning the contents of emails that are hosted on their servers.

Proton's approach here is different, sorting mail by metadata instead of reading what's inside each message, since its zero-access encryption keeps that content unreadable even to itself.

Anant Vijay Singh, the Product Lead for Proton Mail, goes even further to note that:

Proton’s business model aligns our incentives with yours because we’re 100% funded by our community, not by advertisers. Enabling Categories doesn’t change any of this.

Your inbox remains protected by zero-access encryption, and emails you send with other Proton users (or using password protection) are end-to-end encrypted.

It's already live

If you haven't logged into your Proton Mail (partner link) account recently, then keep an eye out for a dialog titled "Your inbox, automatically organized." It will show you two options; go with "Yes, organize it" if you want to upgrade to the new category-focused inbox experience.

If you'd rather stay on the legacy, unified inbox system, then choose "Keep inbox as before."

Once enabled, you will see the categories all lined up at the top of your emails, with a useful blue dot appearing on the ones with unread messages.

Moving an email to a different category takes a right-click followed by "Move to category..." or a drag and drop. Going forward, Proton Mail sorts similar emails into that category automatically.

If the default category selection or the feature itself doesn't suit your preferences, then you can manage it from the Settings menu (gear button), where you could either disable it by clicking on the button near "Email categories."

Or, you could go into the "Email categories" settings page to enable or disable individual categories and toggle notifications for each one. I was content with the default selections, so I didn't bother changing anything.

You can see how Proton Mail categorized my mail. 👇

From left to right: Social, Promotions, and Newsletters.

Keep in mind that you cannot disable the "Primary" category as that one always stays on, catching anything that needs your attention along with emails from any category you've turned off.

And that's not all. Proton is also bringing full-content search to Proton Mail on mobile in the coming weeks. It'll let users search the actual contents of their emails, not just subjects and senders.

Proton says that the search will run entirely on the user's device rather than touch its own servers.

Switch to ProtonMail

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Canonical is Funding a PhD to Automate C to Rust Translation for Ubuntu

Canonical has committed funding to a three-year PhD project focused on building a system that can automatically translate large C codebases into Rust.

And they are not alone; UK Research and Innovation is matching their funding for the project, which is set to run through the University of Bristol's Programming Languages Research Group.

The PhD is aiming to build an all-encompassing platform that can take a C repository running into hundreds of thousands of lines and translate it into Rust that's "safe, behaviourally correct and maintainable Rust."

The work will be carried out by a student, Alex Wood, who will be supported by Professor Meng Wang leading the work, with Dr. Cristina David and Canonical's Jon Seager serving as co-supervisors.

How would this work?

Getting from C to Rust automatically means solving a few separate problems, and the system tackles them in sequence. First, it has to break a massive codebase into pieces small enough to work with without losing track of how those pieces depend on each other elsewhere in the code.

Only then does the actual translation happen, handled by language models that have already been trained on real C-to-Rust conversions, with the goal of writing code that looks like something a Rust developer chose to write rather than C dressed up in Rust syntax.

That's the easier half. The harder task is proving the translated code actually behaves like the original, which is where fuzzing and formal equivalence checks come in.

When something doesn't line up, a separate repair step tries to track down exactly where the translation went wrong and patch it using symbolic program-repair techniques instead of starting the whole chunk over.

Jon points out that the language model handles only one part of the job. Whatever it generates still has to clear validation before anyone can trust that it kept the original behavior intact.

The targeted test case

Both AppArmor and snap-confine already run in production on real Ubuntu systems, handling access control and sandboxing that most users never see but rely on constantly.

That's why they were picked, not because they are simple, but because Canonical wants industrial-grade test cases that offer a much better look at how the approach holds up under real production conditions.

Testing a live component carries with it everything that's built up around it through years of real use, which makes it a far harder thing to translate without breaking something, and that's the point.

Jon also flagged an important caveat, noting that nothing generated by this project is going into either tool anytime soon. The point, he said, is that Canonical has "a vested interest in the software and are keen to see the results," not that a rewrite is coming.

Why should you care?

If the approach survives this test, Canonical will have a real answer to whether automated translation can be trusted with code that protects the system, not just the code that was easy to test on.

As a result, Ubuntu users, from regular desktop installs to enterprise deployments, could eventually see security-critical components with fewer bugs without Canonical having to gamble on a time-consuming manual rewrite of sensitive code.

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FOSS Weekly #26.34: StillOS Review, Kernel 7.2 Released, PINE Trouble, Beautifying GNOME, Terminal Multiplexers and More

LightDM 1.33.0 is out after a four-year gap, now under community maintainership rather than Canonical's. Two new maintainers, one behind Ubuntu Cinnamon Remix and the other a long-time Fedora and openSUSE contributor, have stepped up.

Nitrux has given a name to what it's been building since dropping Plasma for Hyprland last year. The Workspace Environment brings four in-house QML components together, a workspace bar, a dock, a settings app, and a lock screen.

A busy point release for Linux has just landed. AMD Radeon picks up HDMI 2.1 support, Apple M3 MacBooks can boot Linux for the first time, and Btrfs large folio support is on by default.

Canonical's VP of Engineering has said that Ubuntu's growth rate inside WSL is outpacing its growth rate on native desktops, which got picked up everywhere (including here 🤐) as "Ubuntu is growing faster on Windows than Linux." He's since clarified that the comparison was about growth rate only.

The Xen Project recently launched a Safety Committee to build the shared documentation, test evidence, and certification artifacts that companies deploying Xen in automotive, avionics, and industrial automation keep having to produce independently.

Privacy company Murena now offers Fairphone Gen 6 with its /e/OS, a private alternative to Android.

PINE64 is halting the production of its Linux-based tablets. Reason? The soaring RAM prices have made it impossible to keep the pricing reasonable for such hobbyist devices. And the RAM prices are increasing due to AI boom. Big Tech has already put their hands on the supply with bulk orders for their data centers and now the consumers are struggling as prices for disks and RAMs have gone up multiple folds.

🧠 What We’re Thinking About

Don't remember if I shared it in the newsletter or not. A few days ago, it was found that some AI companies are buying rare books to train their LLMs. And in the process, they were also cutting (read destroying) the books because it is easier to scan the books page by page that way.

404 Media (paywalled content) has tracked one such shipment to the Amazon AI training facility. So at least we have one culprit identified.

🧮 Linux Tips, Tutorials, and Learnings

Most people look no further than Tmux and Screen. But what if I told you there were terminal multiplexers that shared sessions over SSH, restored your workspace exactly as you left it, or brought tiling WM concepts straight into your terminal?

A detailed guide on apt that covers updating the package database, installing and removing packages, searching, showing package info, listing upgradable software, and cleaning up leftover dependencies.

Want your GNOME desktop to look like those Catppuccin or Nord riced screenshots without spending an afternoon in config files? Rewaita is a Flatpak app that applies color palettes to GTK and Libadwaita apps through CSS overrides.

Desktop Linux is mostly neglected by the industry but loved by the community. For the past 14 years, It's FOSS has been helping people use Linux on their personal computers. And we are now facing the existential threat from AI models stealing our content.

If you like what we do and would love to support our work, please become It's FOSS Plus member. It costs $49 a year (less than the cost of a McDonald's burger a month), and you get an ad-free reading experience with the satisfaction of helping the desktop Linux community. And there are also free Linux ebooks.

Join It's FOSS Plus

👷 AI, Homelab and Hardware Corner

Proton has come up with a tool that tells you how many secrets you have spilled over to an AI chatbot.

✨ Apps and Projects Highlights

stillOS is a new distro that's built on an AlmaLinux base with atomicity as its main selling point.

📽️ Videos for You

I show you a wonderful dock for GNOME users. See it in action in this week's video.

Subscribe to It's FOSS YouTube Channel

💡 Quick Handy Tip

On GNOME inside the Nautilus file manager (aka Files), press CTRL+F to start a search in the current directory and CTRL+SHIFT+F to search everywhere. You can also select the result and use CTRL+ALT+O to open that location in file manager.

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🎋 Fun in the FOSSverse

If you went through the apt guide earlier, why not test your knowledge with a quick quiz?

The beginning is always simple. 😆

🗓️ Tech Trivia: On August 22, 1955, representatives from seventeen companies that had bought IBM's new 704 mainframe met at RAND Corp in Santa Monica and formed SHARE, the first computer user group, so members could trade code and documentation instead of duplicating each other's work.

🧑‍🤝‍🧑 From the Community: A long-time FOSSer has returned, kicking off a thread on how Windows enabled bitlocker without asking him, resulting in considerable wear on the attached storage disks.

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PINE64 is Halting its Linux Hardware Line, and The AI Bubble is to Blame

The open hardware manufacturer recently posted an update on its Mastodon account, and it's not great news if you were hoping to grab new Linux-powered PINE64 hardware.

The disruptions in DRAM and eMMC supply are to blame, as PINE64 says its Linux hardware production pipeline is empty for now, with nothing new planned while component costs stay high.

Whether that changes depends on component pricing after mid-2027, and they aren't promising anything before then. They expect stocks for the PineNote and PineTab2 to run out in three months.

Once that happens, there's no more new launches or restocks to cover the outgoing stock.

Not everything is affected though. PINE64's microcontroller lineup, the PineTime, PineVoice, and Pinecil, will keep shipping as usual since they don't rely on the same memory chips.

Concluding their announcement, they gave everyone a status update on the upcoming PineTime Pro:

As for the PineTime Pro, currently the demo firmware has basic drivers for the display, touch, motion, GPS, buttons, heat rate sensor (chip id only), battery charger, motor, microphone and the speaker. Though some issues do need to be ironed out first before a pilot batch begins production.

That's it for this post, all in all it's a bit bleak for the Linux devices, but in the meantime PineStore still have a great lineup of MCU powered devices which will continue to expand with more exciting devices.

The unnamed culprit

PINE64 never actually says the word "AI" in their post, choosing to keep the announcement focused on the DRAM/eMMC shortage. But you have to look further to see where that shortage is actually originating from.

Memory prices have been climbing for months, and DDR5 has taken the hardest hit of all. Companies running AI data centers have been locking up global memory supply well into next year, leaving everyone else fighting over what's left.

Executives across the memory industry aren't optimistic either. SK Hynix's CEO recently said that the worst is still ahead, with supply expected to lag behind demand for years to come.

Not the only ones

PINE64 isn't the only Linux-focused hardware provider caught in this price surge.

The Orange Pi Neo, a Linux-first handheld built with Manjaro, has been sitting on ice since earlier this year for the same reason. The project has been in development for two years and still has no launch date, all because DDR5 and SSD prices refuse to come back down.

I am sure these aren't the only projects affected; smaller ones still in the crowdfunding or conceptualization phase must be facing the same problem.

What worries me is that the AI bubble will eventually burst, but small Linux-focused projects are the ones getting choked out right now. If these component prices stay this absurd, we are going to lose the few independent hardware choices we actually have left.

---

Suggested Read 📖: Omarchy Bets Its Future on AI Agents While the Linux World Stays Cautious

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Warp Launches Factories to Let Engineering Teams Build Their Own Cloud Software Factories

▶️ Warp has introduced Factories, infrastructure for running your own cloud software factory with fleets of agents.
▶️ Agents handle triage, specs, implementation, and review; humans step in only when needed.
▶️ Works with any model or harness, and all runs are tracked via built-in metrics.
▶️ Closed beta only; apply for early access.

How software gets built at an organization has evolved a lot over the years. Long before AI agents entered the scene, engineering teams were already turning development into a series of repeatable actions that brought together shared components and defined processes while minimizing reinvention.

That approach has made teams faster and more consistent. In the age of AI, it needs to transform yet again. Warp is convinced it has figured out what's next.

The company has introduced Warp Factories as an open infrastructure offering meant to help engineering teams build and run their own cloud software factories. Here, fleets of coding agents do the work instead of an agent limited to a developer's laptop.

The short explanation is that it's Warp's attempt to turn "run an agent in the cloud" into an actual assembly line, with clear steps, real numbers to track, and humans stepping in only when it matters.

📋

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An assembly line for development

Warp Factories acts as an infrastructure layer for running fleets of coding agents across the entire software development lifecycle. In Warp's own framing, that makes it a cloud software factory, an automated loop where agents handle the work from intake through to a shipped result.

Agents handle triage, write specs, implement changes, review the work, verify it, and monitor the result, while humans only step in at decision points that actually need a person to verify what's been done.

Think of it like a car assembly line. One station welds, another paints, another does final inspection, and the vehicle doesn't move forward until the station before it signs off. Warp's version applies that same logic to code.

One agent triages an incoming ticket, another drafts a spec if the change is complex enough to need one, another implements the fix, and another reviews it before a human approves the merge.

Warp is leaning hard on the idea of AI sovereignty to explain why this needs to exist as infrastructure. Teams can bring their own hosting, and every agent conversation, evaluation, and memory record can be kept on infrastructure the company controls instead of Warp's.

Data can also be kept out of any training pipeline entirely through zero-data-retention options.

The founder and CEO of Warp, Zach Lloyd, further points out that:

Our vision is providing you all with the core components to get to this point as quickly as possible. In an age where time to ship is arguably your most important competitive advantage, you should be standing up and operating a factory today, not six months from now.

More of its capabilities

Factories also ships with a dashboard the company calls the "factory app," basically a control room where you can watch live and past agent runs, check what's pending, and review every automation in one place.

You're not locked into Warp's own models or its own agent either. Factories works with any model, open-weight ones too, and any harness, so Claude Code or Codex can sit in the implementation seat instead of Warp's native agent.

All of that activity gets measured automatically, with cost, throughput, and code quality metrics feeding into evaluation and benchmark tools that track how a factory's performance shifts over time.

Get started

Warp Factories isn't available for everyone right now. If you or your organization wants to try it out, then you will need to request access through Warp Factories' early access portal.

Qualifying organizations can get up to $10,000 in factory usage credits.

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Book Review: The Ultimate AI Guide for Linux Engineers

Even Linus Torvalds is fine with AI being used in Linux kernel development these days, and it's everywhere else in the Linux and tech world too. The time has come to stop ignoring AI and start using it as a tool and to use it well, especially if you are a professional sysadmin or DevOps.

That's why seasoned Linux professionals, Ezequiel Lanza and Eduardo Spotti wrote the book The Ultimate AI Guide for Linux Engineers that I am reviewing here. The book is published by Packt and you can find it on Packt, O'Reilly and Amazon.

Note that the book is written for people who already know and use Linux professionally. That means sysadmins, devops, SREs, system engineers, network engineers. The book collectively calls them "Linux engineers" and I like that term.

Basically, it is for the people who are more used to doing things the old way and unsure where and how to fit AI into their regular workflow.

A book for seasoned Linux professionals

The book opens with "Linux engineers have always been expected to do more with less," and that's the core idea of the book: using AI effectively to improve efficienncy.

The examples are good, and if you've managed servers and infrastructure before, you'll relate to them. That's what makes the book interesting: it's written from a sysadmin/DevOps perspective.

To reduce the risk of letting AI agents loose on your systems, the authors suggest best practices like role-based access, limiting operations to read-only wherever possible, and logging all AI actions for auditing.

There are also examples and sample code you can adapt for your own workflow with some modification, like an anomaly detector you could plug into your Linux observability stack.

Although the book has 12 chapters and runs over 300 pages, I find that the book is divided into four core sectors:

1. Foundational knowledge

The book starts by explaining AI, machine learning (ML), and large language models (LLMs) specifically in Linux contexts, covering the practical differences between training, fine-tuning, and inference.

This sets up the technical foundation for building an AI-ready Linux environment, with an emphasis on Python as the primary language and virtual environments and containerization for safe, reproducible workflows.

2. Intelligent automation and LinuxOps agents

A major focus of the book is the shift from static automation to intelligent automation. AI-assisted automation shows how to combine AI with traditional tools like Ansible, Bash, and systemd to generate safe, validated commands from natural language intent.

The book also teaches how to build autonomous agents that can perceive system problems, reason through multi-step plans, and execute tasks while following least-privilege principles and safeguards.

3. Intelligent observability and RAG

The authors push for moving from passive monitoring to a "dialogue model" of observability, through log dialogue pipelines. So, instead of manually grepping through logs, you build pipelines that compress and correlate multi-source logs into actionable knowledge.

The book also covers building RAG systems that index system logs, internal runbooks, documentation, and past incident reports to give you context-aware answers instead of hallucinated ones. This is where AI actually shines. When it has context, its analysis is far more accurate.

4. Production deployment and security

To move these concepts into real-world use, the book covers scaling and securing AI workloads on Kubernetes: managing GPU resources, implementing autoscaling based on inference-specific metrics, and optimizing performance through techniques like quantization.

It also lays out a full security stack, including threat modeling for AI, PII (personally identifiable information) redaction, prompt injection defenses, and using Open Policy Agent (OPA) to enforce strict guardrails on agent actions. This part matters more than people think; it's usually the part companies skip, right up until they end up trending on social media over a security incident.

The book ends by looking at the future of AI-driven Linux workflows, and the need to balance autonomy with human oversight.

💡

Each chapter comes with practice exercises and additional external resources. There is an accompanied GitHub repo that has the codes and pipelines discussed in the book.

Verdict

Overall, The Ultimate AI Guide for Linux Engineers is a practical, Linux-first handbook designed to help system administrators, SREs, and DevOps professionals fold AI into their daily workflows. Instead of focusing on theory, it lays out a roadmap for evolving from traditional shell scripts to intelligent, autonomous systems.

This book isn't for you if you're completely new to Linux or just a casual desktop user. You may still learn something, but unless you're managing servers, containers, and infrastructure, you probably won't find it as engaging or useful.

I think every Linux professional should start looking for ways to use AI in their workflow. The book gives you ideas, it gives you scenarios and guides you through them. If you ever wanted to start using AI but was unsure because of all the noise around it and didn't know where to begin, the book is definitely worth a read.

The best engineers will not be replaced by AI but will be the ones who know how to use it effectively.

Still unsure? To determine whether the book is for you, I advise checking it on the O'Reilly website. It has chapters of the books and you can expand those chapters to see the sections of those chapters.

This will give a clearer picture if you are still indecisive if you should get the book.

Get it from Amazon

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Murena Just Made The Fairphone (Gen. 6) Better!

We are used to seeing Murena roll out new devices every now and then. Their whole sales pitch revolves around a de-Googled, privacy-focused Android experience. Not everyone is sold on that approach, sure, but the company has managed to stick around for quite a few years now, which says something.

The latest addition to their lineup is the Fairphone (Gen. 6+) with /e/OS. It sits right next to the standard Gen. 6 model, which is still on sale. The new variant packs better hardware and carries a higher price tag to match.

The new device

The three colorways: Horizon Black, Cobalt Blue, and Forest Green.

The most significant change is the Snapdragon 7s Gen 4 processor, paired with 12GB of RAM. The base model makes do with the older Gen 3 chip and 8GB of RAM. Though storage stays at 256GB across both, expandable via microSD up to 2TB.

Everything else on the hardware carries over from the base model, including the 6.31-inch 120Hz LTPO OLED display, the 50MP main camera with a 13MP secondary and 32MP selfie shooter, the 4,415mAh removable battery with 30W charging, IP55 water resistance, and Gorilla Glass 7i to protect the display.

There's also a new Cobalt Blue colorway that ties into Fairphone's fair-mined cobalt supply chain efforts. It joins the existing Forest Green and Horizon Black options. The modular design is unchanged, so you can still swap out 12 key components with a regular screwdriver.

The software itself has not changed for this launch. It is still the same privacy-first build Murena has been refining for a while now.

That means no Google tracking baked into the OS, an Advanced Privacy widget that lets you control what data individual apps can see, and a running Wall of Shame that calls out installed apps leaking the most personal information.

The founder and CEO of Murena, Gaël Duval, spoke about the device, saying that:

With devices like Fairphone (Gen. 6+) with /e/OS, users can have a truly ethical device both in terms of hardware and software.

When I developed Mandriva Linux back in the 90s, it was my mission to make the operating system usable for the everyday, non-techie user. This is my goal with Murena – to give the average user access to smartphones that do not hold their privacy to ransom.

Get yours

Pricing depends on which region you order a Murena Fairphone (Gen. 6+) from. For EU, it costs €699, more than the €649 Murena charges for the standard Gen. 6. In the US, the Fairphone (Gen. 6+) is priced at $699, which is more than the standard Gen. 6's $649 price tag.

People who order during the limited-time launch window of 18 August-1 September 2026 get a few extras. In the EU, that's two free accessories of your choice, where you get to pick from a case, screen protector, finger loop, card holder, or lanyard. US buyers get a case and screen protector bundle.

Everyone gets a year of 1TB Murena Workspace and a year of Murena MDM.

Availability differs by region too. The device is shipping now in Europe, with the US listed as a backorder.

Buy Now

Closing thoughts

The ethical smartphone market is still tiny, and it mostly survives on partnerships like this one. Fairphone builds the hardware, Murena handles the software, and together they keep proving that a privacy-first phone does not have to mean a phone stuck in the dark ages.

Whether that is enough to pull people away from Google remains the same open question it was the last time Murena updated their lineup.

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