Apple dropped the Xcode 26.5 beta at the end of March 2026, bundled with updated SDKs for iOS/iPadOS 26.5, macOS Tahoe 26.5, and an unusually deep Safari update. While it's not a headline release like Xcode 26.0, it carries some genuinely useful additions — especially if your app monetizes via subscriptions.

Here's a practical rundown of what changed and what you should care about.

StoreKit Gets Serious About Subscription Billing Plans

The biggest developer-facing change in Xcode 26.5 is a set of new StoreKit APIs designed around monthly subscriptions with 12-month commitment billing plans — a billing configuration Apple introduced in App Store Connect.

New APIs at a Glance

SubscriptionInfo.pricingTerms (PricingTerms model)
You can now programmatically read the pricing terms for a subscription that uses a monthly-with-12-month-commitment plan. This means you no longer have to hardcode pricing details in your UI — you can pull them live from StoreKit.

if let terms = product.subscription?.pricingTerms {
    // Access structured pricing info for monthly commitment plans
    print(terms)
}

billingPlanType PurchaseOption
When initiating a purchase, you can now specify which billing plan type to use for monthly commitment subscriptions. This gives you precise control over the purchase flow without relying solely on App Store Connect configurations.

let options: Set<Product.PurchaseOption> = [.billingPlanType(.monthly)]
let result = try await product.purchase(options: options)

CommitmentInfo on Transaction and SubscriptionRenewalInfo
After a user subscribes, you can read their entitlement metadata via the new CommitmentInfo data model. This is attached to both Transaction and SubscriptionRenewalInfo, so you can surface commitment-related status in your app's account or subscription management screens.

preferredSubscriptionPricingTerms(_:) — SwiftUI Merchandising
If you import both StoreKit and SwiftUI, you now have access to a new built-in view modifier that lets you merchandise monthly commitment plans using Apple's built-in styles. This is the fastest path to a polished subscription paywall that automatically adapts to Apple's design language.

ProductView(id: "com.yourapp.pro.monthly") {
    // Your custom paywall content
}
.preferredSubscriptionPricingTerms(.prominent)

Why This Matters

If you're running a subscription app and want to offer yearly value at a monthly price point (the classic "monthly billed annually" model), these APIs give you the infrastructure to build a first-class experience — including transparent pricing display, correct transaction modeling, and native SwiftUI merchandising.

StoreKit Known Issue: SKTestSession in Unit Tests

There's one significant known issue to flag before you upgrade your CI pipeline.

SKTestSession cannot use the selected StoreKit configuration during unit tests, causing test actions to fail. (Feedback: FB22237318)

Workaround:

1. Build and run the app on device using the same StoreKit configuration as your test
2. Close the app
3. Run the unit test using SKTestSession without changing any configuration settings

This allows the configuration to persist on-device before the test begins. It's a clunky workaround — save yourself the confusion and add a comment in your test setup code until Apple ships a fix.

Safari 26.5: A Big Web Update

This beta includes an unusually large Safari update. If you build web views, hybrid apps, or PWAs, there's a lot to go through.

New CSS & Web Features

• :open pseudo-class — Now supported on <details>, <dialog>, <select>, and <input> elements. This unlocks native CSS-only styling for open/closed states without JavaScript.
• color-interpolation on SVG gradients — Linear RGB color space interpolation is now available for SVG gradients, giving you more accurate color blending.
• source property on ToggleEvent — Identifies which element triggered a popover toggle, making it much easier to manage complex popover hierarchies.

Notable Bug Fixes

Scroll-Driven Animations
Multiple fixes landed here: animation timelines now pause correctly when animation-play-state: paused is set dynamically, and view timeline animations near 0% and 100% thresholds report accurate progress values. If you've been battling weird scroll animation behavior, this update may resolve it without any code changes.

Layout & Rendering

• Grid and flex layouts no longer cause position shifts at certain zoom levels
• Images inside transformed containers are now properly centered
• Pinch-to-zoom no longer causes content to jump or disappear on some websites
• Absolutely positioned elements inside block-in-inline containers no longer incorrectly overlap adjacent content

Font Matching
Fixed a bug where @font-face rules with different styles could fall back to glyphs from other faces in the same family instead of moving to the next family. If you've had unexplained font rendering inconsistencies, this is likely the fix.

IndexedDB
A critical bug was fixed where IndexedDB connections could become permanently broken until the page was reloaded. Also fixed: document.hasStorageAccess() could return a Promise that never resolved.

Forms
A readonly date <input> could still be edited via keyboard using the date picker — that's now fixed.

iOS & iPadOS 26.5: Platform Bug Fix

Beyond the StoreKit additions, iOS 26.5 includes one resolved issue worth noting:

Unity and Kaleidoscope wallpapers could fail to install or could not be removed from the Wallpaper Gallery. That's now fixed — minor, but it's the kind of polish bug that triggers App Store reviews if your app touches wallpaper features.

SDK Compatibility Reminder

Xcode 26.5 bundles the updated SDKs for:

• iOS & iPadOS 26.5
• macOS Tahoe 26.5

These are beta SDKs. As a reminder from Apple's broader Xcode 26 release cycle — starting April 28, 2026, new apps and updates uploaded to App Store Connect must be built with iOS 26 SDK or later (and equivalents for tvOS, visionOS, and watchOS). Make sure your CI/CD is already on Xcode 26.

Summary: Should You Upgrade?

Xcode 26.5 is a focused beta — not a massive feature drop, but the subscription billing APIs alone make it a worthwhile update for any monetized app. If you ship subscriptions, test against 26.5 as early as possible so you're ready when it hits stable.

*Source: Xcode 26.5 Beta Release Notes

Starting with this issue of Trends, we’ve moved from simply reporting on news that has caught our eye and instead have worked with Claude to look at the various news items we’ve collected and to reflect on what they tell us about the direction and magnitude of change. William Gibson famously wrote, “The future is here. It’s just not evenly distributed yet.” In the language of scenario planning, what we’re looking for is “news from the future” that will confirm or challenge our assumptions about the present.

AI has moved from a capability added to existing tools to an infrastructure layer present at every level of the computing stack. Models are now embedded in IDEs and tools for code review; tools that don’t embed AI directly are being reshaped to accommodate it. Agents are becoming managed infrastructure.

At the same time, two forces are reshaping the economics of AI. The cost of capable AI is falling. Laptop-class models now match last year’s cloud frontiers, and the break-even point against cloud API costs is measured in weeks. The competitive map has also fractured. What was a contest between a few Western labs is now a broad ecosystem of open source models, Chinese competitors, local deployments, and a growing set of forks and distributions. (Just look at the news that Cursor is fronting Kimi K2.5.) No single vendor or architecture is dominant, and that mix will drive both innovation and instability.

Security is a thread running through every section of this report. Each new AI capability reshapes the attack surface. AI tools can be poisoned, APIs repurposed, images forged, identities broken, and anonymous authors identified at scale. At the same time, foundational infrastructure faces threats that have nothing to do with AI: A researcher has come within striking distance of breaking SHA-256, the hashing algorithm underlying much of the web’s security. Organizations should audit both their AI-related exposures and the assumptions baked into the cryptographic infrastructure they depend on.

The technical transitions are easy to talk about. The human transitions are slower and harder to see. They include workforce restructuring, cognitive overload, and the erosion of collaborative work patterns. The job market data is beginning to clarify: Product management is up, AI roles are hot, and software engineering demand is recovering. The picture is more nuanced than either the optimists or the pessimists predicted.

AI models

The model market is moving fast enough that architectural and vendor commitments made today may not look right in six months. Capable models are now available from open source projects and a widening set of international competitors. The field is also starting to ask deeper questions. Predicting tokens may not be the only path to capable AI; the arrival of the first stable JEPA model suggests that alternative architectures are becoming real contenders. NVIDIA’s new model, which combines Mamba and Transformer layers, points in the same direction.

• Yann LeCun and his team have created LeWorldModel, the first model using his Joint Embedding Predictive Architecture (JEPA) that trains stably. Their goal is to produce models that do more than predict words; they understand the world and how it works.
• NVIDIA has released Nemotron 3 Super, its latest open weights model. It’s a mixture of experts model with 120B parameters, 12B parameters of which active at any time. What’s more interesting is its design: It combines both Mamba and Transformer layers.
• Gemini 3.1 Flash Live is a new speech model that’s designed to support real-time conversation. When generating output, it avoids gaps and uses human-like cadences.
• Cursor has released Composer 2, the next generation version of its IDE. Composer 2 apparently incorporates the Kimi K2.5 model. It reportedly beats Anthropic’s Opus 4.6 on some major coding benchmarks and is significantly less expensive.
• Mistral has released Forge, a system that enables organizations to build “frontier-grade” models based on their proprietary data. Forge supports pretraining, posttraining, and reinforcement learning.
• Mistral has also released Mistral Small 4, its new flagship multimodal model. Small 4 is a 119B mixture of experts model that uses 6B parameters for each token. It’s fully open source, has a 256K context window, and is optimized to minimize latency and maximize throughput.
• NVIDIA announced its own OpenClaw distribution, NemoClaw, which integrates OpenClaw into NVIDIA’s stack. Of course it claims to have improved security. And of course it does inference in the NVIDIA cloud.
• It’s not just OpenClaw; there’s also NanoClaw, Klaus, PiClaw, Kimi Claw and others. Some of these are clones, some of these are OpenClaw distros, and some are cloud services that run OpenClaw. Almost all of them claim improved security.
• Anthropic has announced that 1-million token context windows have reached general availability in Claude Opus 4.6 and Sonnet 4.6. There’s no additional charge for using a large window.
• Microsoft has released Phi-4-reasoning-vision-15B. It is a small open-weight model that combines reasoning with multimodal capabilities. They believe that the industry is trending toward smaller and faster models that can run locally.
• Tomasz Tunguz writes that Qwen3.5-9B can run on a laptop and has benchmark results comparable to December 2025’s frontier models. Compared to the cost of running frontier models in the cloud, a laptop running models locally will pay for itself in under a month.
• OpenAI has released GPT 5.4, which merges the Codex augmented coding model back into the product’s mainstream. It also incorporates a 1M token context window, computer use, and the ability to publish a plan that can be altered midcourse before taking action.
• TweetyBERT is a language model for birds. It breaks bird songs (they use canaries) into syllables without human annotation. They may be able to use this technique to understand how humans learn language.
• Vera is a new programming language that’s designed for AI to write. Unlike languages that are designed to be easy for humans, Vera is designed to help AI with aspects of programming that AIs find hard. Everything is explicit, state changes are declared, and every function has a contract.
• The Potato Prompt is a technique for getting GPT models to act as critics rather than yes-things. The idea is to create a custom instruction that tells GPT to be harshly critical when the word “potato” appears in the prompt. The technique would probably work with other models.

Software development

The tools arriving in early 2026 point toward a deep reorganization of the role of software developers. Writing code is becoming less important, while reviewing, directing, and taking accountability for AI-generated code is becoming more so. How to write good specifications, how to evaluate AI output, and how to preserve the context of a coding session for later audit are all skills teams will need. The ecosystem around the development toolchain is also shifting: OpenAI’s acquisition of Astral, the company behind the Python package manager uv, signals that AI labs are moving to control developer infrastructure, not just models.

• OpenAI has added Plugins to its coding agent Codex. Plugins “bundle skills, app integrations, and MCP servers into reusable workflows”; conceptually, they’re similar to Claude Skills.
• Stripe Projects gives you the ability to build and manage an AI stack from the command line. This includes setting up accounts, billing, managing keys, and many other details.
• Fyn is a fork of the widely used Python manager uv. It no doubt exists as a reaction to OpenAI’s acquisition of Astral, the company that developed and supports uv.
• Anthropic has announced Claude Code Channels, an experimental feature that allows users to communicate with Claude using Telegram or Discord. Channels is seen as a way to compete with OpenClaw.
• Claude Cowork Dispatch allows you to control Cowork from your phone. Claude runs on your computer, but you can assign it tasks from anywhere and receive notification via text when it’s done.
• Opencode is an open source AI coding agent. It can make use of most models, including free and local models; it can be used in a terminal, as a desktop application, or an extension to an IDE; it can run multiple agents in parallel; and it can be used in privacy-sensitive environments.
• Testing is changing, and for the better. AI can automate the repetitive parts, and humans can spend more time thinking about what quality really means. Read both parts of this two-part series.
• Claude Review does a code review on every pull request that Claude Code makes. Review is currently in research preview for Claude Teams and Claude Enterprise.
• Andrej Karpathy’s Autoresearch “automates the scientific method with AI agents.” He’s used it to run hundreds of machine learning experiments per night: running an experiment, getting the results, and modifying the code to create another experiment in a loop.
• Plumb is a new tool for keeping specifications, tests, and code in sync. It’s in its very early stages; it could be one of the most important tools in the spec-driven development tool chest.
• “How I Use AI Before the First Line of Code“: Prior to code generation, use AI to suggest and test ideas. It’s a tremendous help in the planning stage.
• Git has been around for 10 years. Is it the final word on version control, or are there better ways to think about software repositories? Manyana is an attempt to rethink version control, based on CRDTs (conflict-free replicated data types).
• Just committing code isn’t enough. When using AI, the session used to generate code should be part of the commit. git-memento is a Git extension that saves coding sessions as Markdown and commits them.
• sem is a set of tools for semantic versioning that integrates with Git. When you are doing a diff, you don’t really want to which lines changed; you want to know what functions changed, and how.
• Claude can now create interactive charts and diagrams.
• Clearance is an open source Markdown editor for macOS. Given the importance of Markdown files for working with Claude and other language models, a good editor is a welcome tool.
• The Google Workspace CLI provides a single command line interface for working with Google Workspace applications (including Google Docs, Sheets, Gmail, and of course Gemini). It’s currently experimental and unsupported.
• At the end of February, Anthropic announced a program that grants open source developers six months of Claude Max usage. Not to be left out, OpenAI has launched a program that gives open source developers six months of API credits for ChatGPT Pro with Codex.
• Here’s a Claude Code cheatsheet!
• Claude’s “import memory” feature allows you to move easily between different language models: You can pack up another model’s memory and import it into Claude.

Infrastructure and operations

Organizations should be thinking about agent governance now, before deployments reach a scale where the lack of governance becomes a problem. The AI landscape is moving from “Can we build this?” to “How do we run this reliably and safely?” The questions that defined the last year (Which model? Which framework?) are giving way to operational ones: How do we contain agents that behave unexpectedly? Where do we store their memory? How do we coordinate agents from multiple vendors? And when does it make sense to run them locally rather than in the cloud? Agents are also acquiring the ability to operate desktop applications directly, blurring the line between automation and user.

• Anthropic has extended its “computer use” feature so that it can control applications on users’ desktops (currently macOS only). It can open applications, use the mouse and keyboard, and complete partially done tasks.
• OpenAI has released Frontier, a platform for managing agents. Agents can come from any vendor. The goal is to allow business to organize and coordinate their AI efforts without siloing them by vendor.
• Most agents assume that memory looks like a filesystem. Mikiko Bazeley argues that filesystems aren’t the best option; they lack the indexes that databases have, which can be a performance penalty.
• Qwen-3-coder, Ollama, and Goose could replace agentic orchestration tools that use cloud-based models (Claude, GPT, Gemini) with a stack that runs locally.
• KubeVirt packages virtual machines as Kubernetes objects so that they can be managed together with containers.
• db9 is a command line-oriented Postgres that’s designed for talking to agents. In addition to working with database tables, it has features for job scheduling and using regular files.
• NanoClaw can now be installed inside Docker sandboxes with a single command. Running NanoClaw inside a container with its own VM makes it harder for the agent to escape and run malicious commands.

Security

This issue has an unusually heavy security section, and not only because AI keeps expanding the attack surface. A researcher has come close to breaking SHA-256, the hashing algorithm that underpins SSL, Bitcoin, and much of the web’s security infrastructure. If hash collisions become possible in the coming months as predicted, the implications will reach every organization that relies on the internet. At the same time, AI systems are now capable of gaming their own benchmarks, and the pace of new attack techniques is outrunning the pace of security review.

• A researcher has come close to breaking the SHA-256 hashing algorithm. While it’s not yet possible to generate hash collisions, he expects that capability is only a few months away. SHA-256 is critical to web security (SSL), cryptocurrency (Bitcoin), and many other applications.
• When running the BrowseComp benchmark, Claude hypothesized that it was being tested, found the benchmark’s encrypted answer key on GitHub, decrypted the answers, and used them.
• Anthropic has added auto mode to Claude, a safer alternative to the “dangerously skip permissions” option. Auto mode uses a classifier to determine whether actions are safe before executing them and allows the user to switch between different sets of permissions.
• In an interview, Linux kernel maintainer Greg Kroah-Hartman said that the quality of bug and security reports for the Linux kernel has suddenly improved. It’s likely that improved AI tools for analyzing code are responsible.
• A new kind of supply chain attack is infecting GitHub repositories and others. It uses Unicode characters that don’t have a visual representation but are still meaningful to compilers and interpreters.
• AirSnitch is a new attack against WiFi. It uses layers 1 and 2 of the protocol stack to bypass encryption rather than breaking it.
• Anthropic’s red team worked with Mozilla to discover and fix 22 security-related bugs and 90 other bugs in Firefox.
• Microsoft has coined the term “AI recommendation poisoning” to refer to a common attack in which a “Summarize with AI” button attempts to add commands to the model’s persistent memory. Those commands will cause it to recommend the company’s products in the future.
• Deepfakes are now being used to attack identity systems.
• LLMs can do an excellent job of de-anonymization, figuring out who wrote anonymous posts. And they can do it at scale. Are we surprised?
• It used to be safe to expose Google API keys for services like Maps in code. But with AI in the picture, these keys are no longer safe; they can be used as credentials for Google’s AI assistant, letting bad actors use Gemini to steal private data.
• WIth AI, it’s easy to create fake satellite images. These images could be designed to have an effect military operations.

People and organizations

The workforce implications of AI are more complicated than either the optimistic or pessimistic predictions suggest. The cognitive load on individuals is increasing, and the collaborative habits that distribute that load across a team are eroding. Managers should track not just velocity but sustainability. The skills that AI cannot replace, including judgment, communication, and the ability to ask the right question before writing a single line of code, are becoming more valuable. And the volume of AI-generated content is now large enough that organizations built around reviewing submissions, including app stores, publications, and academic journals, are struggling to keep up with it.

• Lenny Rachitsky’s report on the job market goes against this era’s received wisdom. Product manager positions are at the highest level in years. Demand for software engineers cratered in 2022, but has been rising steadily since. Recruiters are heavily in demand; and AI jobs are on fire.
• Apple’s app store, along with many other app stores and publications of all sorts, is fighting a “war on slop“: deluges of AI-generated submissions that swamp their ability to review.
• Teams of software developers can be smaller and work faster because AI reduces the need for human coordination and communications. The question becomes “How many agents can one developer manage?” But also be aware of burnout and the AI vampire.
• Brandon Lepine, Juho Kim, Pamela Mishkin, and Matthew Beane measure cognitive overload, which develops from the interaction between a model and its user. Prompts are imprecise by nature; the LLM produces output that reflects the prompt but may not be what the user really wanted; and getting back on track is difficult.
• A study claims that the use of GitHub Copilot is correlated with less time spent on management activities, less time spent collaboration, and more on individual coding. It’s unclear how this generalizes to tools like Claude Code.

Web

• The 49MB Web Page documents the way many websites—particularly news sites—make user experience miserable. It’s a microscopic view of enshittification.
• Simon Willison has created a tool that writes a profile of Hacker News users based on their comments, all of which are publicly available through the Hacker News API. It is, as he says, “a little creepy.”
• A personal digital twin is an excellent way to augment your abilities. Tom’s Guide shows you how to make one.
• It’s been a long time since we’ve pointed to a masterpiece of web play. Here’s Ball Pool: interactive, with realistic physics and lighting. It will waste your time (but probably not too much of it).
• Want interactive XKCD? You’ve got it.

Welcome to the Cloud Wars Minute — your daily cloud news and commentary show. Each episode provides insights and perspectives around the “reimagination machine” that is the cloud.

In today’s Cloud Wars Minute, I explore how Microsoft’s latest Windows changes reveal a strategic shift toward more intentional AI integration and focused Copilot experiences.

Highlights

00:09 — It was only a short paragraph in a blog post by Microsoft’s Pavan Davuluri, Executive Vice President of Windows and Devices, discussing the changes the company is making to Windows in response to community feedback. However, it has significant implications and, if you pick it apart, could provide a better understanding of where Microsoft is directing its AI ambitions.

00:36 — Here’s the paragraph in full: “With craft and focus, you will see us be more intentional about how and where Copilot integrates across Windows, focusing on experiences that are genuinely useful and well crafted,” says Davuluri. “As part of this, we are reducing unnecessary Copilot entry points, starting with apps like Snipping Tool, Photos, Widgets, and Notepad.”

01:05 — When Microsoft went all out on the Copilot rollout across its massive ecosystem of products, platforms, and services, some commentators argued that this push could overwhelm consumers. Instead, a more targeted approach would perhaps make it easier for customers to see the benefits and, critically, the use cases that Copilot can amplify.

01:28 — It seems that Microsoft has taken these concerns into consideration and is now scaling back the areas where Copilot is utilized. This is a smart move from a Windows perspective, as it prioritizes value over volume, and this approach aligns well with the evolving direction of Copilot Studio, which focuses on creating agentic experiences.

01:53 — Now Microsoft is consolidating its AI offerings by moving away from the idea of having Copilot everywhere. Instead, agents developed through Copilot Studio will be able to plug into specific execution environments, just like Windows.

The post Inside Microsoft’s Shift From “Copilot Everywhere” to Intentional AI Integration appeared first on Cloud Wars.

DRAM is pretty expensive these days. In the latest issue of Raspberry Pi Official Magazine, we rounded up a range of project ideas that make good use of the 1GB Raspberry Pi 5, helping you select the right amount of RAM for your applications. This article forms part of a larger feature on how to make your memory go further.

With the same powerful BCM2712 system-on-chip (SoC) as the other Raspberry Pi 5 models, the 1GB variant offers a more affordable entry point for users who need extra processing grunt and/or features, such as a PCIe connector to add a Raspberry Pi NVMe SSD or AI HAT+. To this end, we’ve rounded up a range of project ideas that make good use of the 1GB variant’s performance without requiring a large amount of RAM.

Media centre/NAS

Since the 1GB variant of Raspberry Pi 5 has a PCIe connector, you can use it with a Raspberry Pi M.2 HAT+ (or alternative) to connect an M.2 NVMe SSD (solid-state drive). Not only does this provide extra storage, but it also allows you to boot Raspberry Pi OS from the SSD instead of the standard microSD card.

As well as speeding up general performance with lightning-quick read/write speeds, the SSD is ideal for creating a media centre (to stream movies, TV shows, and music) and/or NAS (network-attached storage).

The easiest way to create a media centre is by using a Kodi-based OS such as LibreELEC or OSMC. For more details, check out our media player guides in issue 132 and 155.

Alternatively, you could set Raspberry Pi 5 up as a discrete NAS box, allowing files to be accessed wirelessly by other devices on your network using the Samba sharing protocol. For setup details, see our NAS tutorial.

Retro gaming

As with most other models, the 1GB variant of Raspberry Pi 5 can emulate many classic computers and consoles. Higher RAM is only really needed when trying to emulate more modern systems, so anything up to and including PlayStation 1, Saturn, and Dreamcast should work fine — this includes NES, SNES, Mega Drive/Genesis, GBA, MAME, ZX Spectrum, C64, and Amiga.

The choice of OS is up to you: Recalbox, Lakka, and Batocera should all work fine — as does RetroPie, though you’ll need to install it manually in Raspberry Pi OS as there’s no ready-made OS image for Raspberry Pi 5.

Game ROMs can be added via a USB drive or over the network. Be careful downloading them from sites hosting copyrighted games illegally, however. There are lots of other legal ROMs available, including many modern ‘homebrew’ titles developed for classic hardware.

Internet radio/hi-fi

While the 1GB Raspberry Pi 5 doesn’t have a built-in audio output, you can listen via Bluetooth headphones or speakers, or through a TV connected via HDMI. Alternatively, for superior sound, several DAC HATs are available to link it to your hi-fi equipment. With the Raspberry Pi DAC Pro, for instance, you can even enjoy high-definition 24-bit audio at 192kHz — far better than standard 16-bit CD quality.

Software-wise, there are numerous ways to enjoy music on your Raspberry Pi, including specialist operating systems such as Volumio, moOde, and piCorePlayer. Most should enable you to listen to locally stored files, popular streaming services, and internet radio stations. You can even cast playback to multiple smart speakers for multi-room audio. For aesthetic effect, house your Raspberry Pi in a vintage radio case.

Magic mirror

“Mirror, mirror on the wall… who’s the smartest of them all?… Ah, it’s you, because you’re powered by a Raspberry Pi and can display all sorts of useful information, such as news, weather, traffic, and my calendar.”

The magic mirror is a classic Raspberry Pi project, and building one isn’t as daunting as it sounds. You just need to source a suitably sized TV or monitor, cover it with some two-way mirror glass (which you can buy ready-made or make yourself by applying special film to ordinary glass), and install it in a wooden frame — you can even DIY this part if you’re keen on carpentry.

Then it’s just a case of installing the software, which you can find — along with all of the documentation and an array of add-on modules — at magicmirror.builders. It’s a good project for a 1GB Raspberry Pi 5, though you will need to have it running the desktop version of Raspberry Pi OS for the software.

Check out the rest of the feature in issue 164 of Raspberry Pi Official Magazine, including tutorials on memory optimisation in Raspberry Pi OS and how to generate images using the Stable Diffusion deep learning model.

The post Mighty projects for your 1GB Raspberry Pi 5 appeared first on Raspberry Pi.

Nate Amidon: When the Blame Game Between Product and Engineering Destroys Your Scrum Team From the Inside

Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.

"Product and engineering are in the same boat. We need to visualize and internalize that it's one team, one fight." - Nate Amidon

Nate was working as a Scrum Master on a full-stack team building an internal mobile application when he noticed tension forming between product and engineering. It started small — finger-pointing about missed requirements — but quickly escalated into a full-blown blame game. The QA started siding with product, creating a product-and-QA-versus-engineers dynamic. Engineers began refusing user stories unless they were "100% baked" with every detail spelled out, turning the team into lawyers negotiating contracts rather than collaborators building software. What's revealing about this pattern is what it looks like from the outside: a project manager might see meticulously detailed user stories and think the team is doing great work. In reality, it's a symptom of broken trust. Nate points out that in high-performing teams, you actually see less detail in the issue tracker — because people are talking, aligned, and adapting together in real time. His approach? He drew stick figures in a boat on sticky notes — one labeled PO, the other Engineering — and stuck them on people's monitors. Simple, visual, and direct: you're in the same boat.

Self-reflection Question: What are the smells you're noticing in your team's interactions — and could overly detailed user stories actually be masking a deeper trust problem between product and engineering?

Featured Book of the Week: Deep Work by Cal Newport

Nate recommends every Scrum Master read Deep Work, and here's why: "Shoulder taps are expensive. If you go and bother an engineer that's in the zone, in deep work, you're adding about a 15-minute reset for them to get back into that zone." For Nate, safeguarding engineers' time is one of the most important things a Scrum Master can do. He also recommends Project to Product by Mik Kersten for Scrum Masters moving into Agile coaching — especially its emphasis on team structure and why "the team needs to be sacrosanct, and work should go to teams."

[The Scrum Master Toolbox Podcast Recommends]

🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥

Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people.

🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue.

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[The Scrum Master Toolbox Podcast Recommends]

About Nate Amidon

Nate, founder of Form100 Consulting, and a former Air Force officer and combat pilot turned servant leader in software development. Nate has taken the high-stakes world of military aviation and brought its core leadership principles—clarity, accountability, and execution—into his work with Agile teams.

You can link with Nate Amidon on LinkedIn. Learn more at Form100 Consulting.