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• The PocketBook Q is a new ereader with a 5.84-inch screen
• It's slimmer and lighter than most phone-sized rivals
• However, it doesn't run Android, limiting your access to apps

It seems like there’s a growing hunger for small ereaders, as following in the footsteps of the Boox Palma series, the Viwoods AiPaper Reader, and the even smaller Xteink devices, there’s now the phone-sized PocketBook Q.

This new ereader has a 5.84-inch E Ink Carta 1300 touchscreen with a 788 x 1576 resolution, a front light that lets you adjust both brightness and color temperature, 1GB of RAM, 32GB of storage, and a 1,550mAh battery which supposedly allows for more than a month of reading on a single charge.

It measures 154 x 75.8 x 6.5mm and 130g, making it even smaller and lighter than the Boox Palma 2 Pro and Viwoods AiPaper Reader, though its screen is smaller too, with both of those having 6.13-inch displays.

So this essentially sits somewhere between those devices and the likes of the Xteink X4 Pro with its 4.3-inch screen.

Apps included but this doesn't run Android

(Image credit: PocketBook)

In any case, the PocketBook Q also has physical side buttons that you can use to turn pages, and it works with Libby for borrowing digital library books. It also has broad format support for both ebook and audio files.

Plus, it comes with an IPX4 rating, for resistance to splashes and moisture, and there’s a text-to-speech tool.

There are a handful of pre-installed apps such as a book store, a browser, and a dictionary, among a few others, but this doesn’t run Android. Rather, it runs PocketBook OS — an operating system based on Linux, so you’re not getting access to the wealth of apps you’ll find on Android.

That helps keep the device focused on books so you avoid distractions, but also means you don’t have access to the likes of the Kindle or Kobo apps on there. That limitation is another way this differs from devices from Boox and Viwoods — though it’s in line with Xteink.

If the PocketBook Q sounds appealing, you’ll be able to grab one for $235 / £175 (around AU$330) when it launches in “late fall” — likely meaning sometime in November.

President Trump is calling on world leaders to join his economic war against Iran. And, the Supreme Court is backing the president for now on his order to restrict mail-in voting.

(Image credit: Win McNamee)

• Report points to AirPods 5 launching in September, in two models
• A cheaper version and a pricier option with noise cancellation
• We're expecting the big iPhone 18 Pro event to happen in early September

Despite all these news stories about AirPods with cameras, we've been hearing that 'normal' AirPods are set to release before the end of the year — and a brand-new report paints a much clearer picture of what we're about to see.

According to a report from Bloomberg's Mark Gurman, a prolific Apple tipster, the brand is teeing up to release AirPods 5, consisting of a standard pair of buds and an ANC-toting model.

It's suggested that these buds could come in early September — Apple's regular late-year launch is expected to bring iPhone 18 Pro models, Apple Watch 12 and a folding iPhone Ultra — but, by the sounds of it, there's wiggle room for them to release a little later. Still, it's often Apple's style to have one big event with lots of products.

Back in 2024, Apple expanded its non-Pro AirPods line two have two versions. We received the standard AirPods 4, and also the AirPods 4 with Active Noise Cancellation, the latter of which received a slightly more positive review from us. It was a similar model, but with a slightly higher price and ANC. It seems that Apple is continuing that trend.

AirPods that are really 'new'

(Image credit: Future/Jacob Krol)

Apple's standard AirPods see fewer leaks and rumors than the Pro model, and so there aren't any serious reports as to what we could expect. But we weren't glowing in our review, and there are a few tweaks Apple could make to improve them.

The main thing is simply the value. The AirPods 4 weren't expensive, but they just didn't offer as good value for money as the competition — the likes of the Nothing Ear (a) were cheaper, offered features such as ANC, and sounded better.

They stood in contrast to the AirPods Pro 2 (which were current when AirPods 4 launched) and later the AirPods Pro 3. The premium buds are excellent value compared to the competition, packing in more features, impressive sound, and a comfortable and light design.

Apple had the same problem I saw in Samsung's Galaxy Buds 4: a brand not making its cheaper options cheap enough. I'd like to see AirPods 5 either cost less (unlikely in today's tech world…) or have more features to give them a reason to cost more than the rest of the budget earbuds world.

I also think fit reliability is an area that needs to see changes too. It's a common problem in semi-open buds like the AirPods, that they don't grip in your ears as well as those with in-ear tips — I've lost count of how many AirPods runners I've seen lose their buds mid-jog. Apple's done good design work in this area, but I want to see improvements still.

Apple improved the battery life of its earbuds last time, and I hope it can do that again — they actually outperformed Apple's claimed figures, but it's normal to see earbuds hit close to 10 hours without ANC on, so it'd be great to see Apple get closer to that.

When it comes to audio, I hope they'll improve the way they handle detail. As we said in our AirPods 4 review, they lose fine resolution, which can affect the enjoyment of some tracks. Of all the upgrades I've listed, I'd imagine sonic tweaks are the ones most likely to come to fruition.

If Apple wanted to make some serious changes, it could make AirPods truly accessible to Android users (at the moment, most AirPods features require an iPhone, though they will function for basic audio with any Bluetooth device). I don't see the brand making this change, but it'd certainly shine a needed light on Apple's lesser-bought buds — however, Android support seems to be Beats' role in Apple's portfolio.

It's hard not to treat 2026 as a fallow year for AirPods. The fifth-generation models will likely be iterative updates, as the AirPods Max 2 were, and the camera-toting AirPods are expected to launch next year. But a few tweaks could help make the AirPods 5 feel like more than water-treading from Apple, even just two years after the previous models.

• Microsoft used to tell you when a bot was in the lobby, now you can automatically block it
• Watch out, because legitimate add-ons like AI assistants could end up being blocked
• More protections are coming to Teams soon, too

Microsoft is rolling out an important new security policy for Teams, and admins can now finally block external meeting bots automatically.

Previously, the software would identify bots and label them accordingly within the lobby, but leave the final decision to meeting organizers – this new update prevents external bots from joining in the first place.

The company hopes the upgrade will give organizations more control over security to reduce the risks associated with unwanted participants.

Teams now automatically blocks external bots

Despite the new change, the policy will be disabled by default, so Microsoft won't be banning third-party bots across the board. But company admins will be able to enable the policy for users or groups to reduce the burden and security risks accordingly, marking a major improvement over the earlier bot protections introduced just two months ago.

Importantly, any external bot detected in a meeting will be blocked from entering, thus legitimate tools could also be blocked, hence the decision to disable the tool by default. That includes legitimate tools like AI meeting assistants, transcription tools, recording add-ons and other similar tools.

"Bots have begun joining meetings that participants never intended them to attend," Meera Ajam explained in a June post, hinting at a shift to hybrid (human and machine) participants.

Nevertheless, it's an important change for the video conferencing platform, which has seen a rise in cybercriminal activity.

Further admin controls, like allow lists for approved bots and audit logs, are also set to come to the productivity suite. This latest update is starting to roll out now, with general availability expected by late September.

Most organizations in UK and across Europe don’t struggle to recover from cyberattacks such as ransomware because they lack backups. They struggle because they try to restore everything at once.

In the aftermath of a major cyber incident, the instinct is to bring every system back online as quickly as possible. It feels like the fastest path back to normality. However, in reality, this approach often slows recovery down, reintroduces cyber risk and undermines trust just when the organization needs it most.

In fact, those that recover fastest start from a different premise. They assume large parts of their organization will be unavailable or untrusted, and they plan accordingly. This mindset leads to a much clearer goal - restore what matters most, quickly, and in a state you can trust.

What is critical to survival?

Focusing on the critical areas of an organization is the idea behind the Minimum Viable Company (MVC) concept, sometimes referred to as the Minimum Viable Organization. It is a definition of what must exist for the organization to survive in challenging conditions such as a cyber incident.

It’s not just a technology concept, it’s a business definition of survival in terms of the minimum combination of people, processes, technology, documentation, facilities, and third-party dependencies required to keep a business functioning and creating value.

Where to start getting an MVC up and running?

There are five key capabilities when it comes to operationalizing an MVC:

1. Clarity on critical services:

A precise understanding of the systems and dependencies that directly support revenue and mission-critical operations is needed here. To understand the MVC, it is key to map systems to business value. Without this understanding, it’s impossible to accurately define the MVC.

The first steps focus on undertaking a structured assessment, aligning across business and technology stakeholders, and going through a realistic simulation of how recovery will unfold under pressure. This will uncover the key areas needed to provide just enough capability to keep the organization functioning safely during a crisis and guide recovery.

In practice, this means defining what must function in the first 24 hours, the first 72 hours, and the first week after a disruption.

2. A trusted foundation (Tier 0):

In the event of a cyberattack, many organizations miss the critical foundational layer that allows them to establish identity and access control independently of compromised systems.

This foundational layer is what we call Tier 0 or the control plane for recovery. It includes identity and access management, networking and DNS, privileged access controls, core security tooling, physical access systems, and secure communication channels.

It also covers non-technical dependencies that are easy to overlook until they’re urgently needed such as incident response playbooks, contact lists and escalation paths, insurance policies, and contracts with external responders. These are the foundations underpinning the critical systems that need to be restored after a cyber incident. Without this layer, a trusted recovery is not possible.

3. Isolation of recovery assets:

In the event of a cybersecurity breach, organizations must establish control of their most critical systems. This requires recovering data separately from clean snapshots and investigating in parallel, not sequentially, to ensure the recovered systems are not infected by malicious software.

As part of this process, backups, configurations, and recovery tooling must be protected from the same blast radius as production. If key recovery assets can’t be isolated, a rapid and trusted control of critical systems can’t be achieved.

4. Clean-room recovery capability:

To set up an isolated environment to rebuild systems without reintroducing compromise, organizations need to set up what we call a ‘Digital Jump Bag’. This is a secure, isolated repository containing everything required to establish a trusted recovery starting point to rebuild systems without reintroducing compromise.

5. Validated ability to operate

The next step is to validate the ability of the MVC to operate through realistic crisis scenarios. Resilience must be proven under real-world conditions. Practice is important here because an untested plan remains theoretical. Rehearsals will also help to answer the Board’s most direct question in the event of a cyberattack - how long will it take to restore critical services to a trusted state?

Recovering faster by restoring what matters most

The most common cyber resilience risks are failing to define what must come back first and how to bring it back in a state that can be trusted. That’s the difference between recovery as a process and recovery as a capability.

The MVC isn’t static. As an organization evolves, its definition must evolve too. But the principle stays the same: recovery improves when organizations stop trying to restore everything and start restoring what matters.

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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Paying $20 every month for ChatGPT Plus has always been easy to justify professionally. I use it for research, document analysis, and more than a little organizational assistance around the house.

Still, it's another monthly subscription at a time when everyone is looking for ways to reduce the amount repeatedly drained from their bank accounts. That's why I've been pressing ChatGPT to justify its own cost using the finance feature it debuted a couple of months ago.

I didn't ask ChatGPT to defend its place on my credit card bill literally, though it probably could. Instead, I prompted it to use its analysis of some of my finances to identify places where my money might be evaporating without enough justification, or even awareness.

ChatGPT’s finances tool can review connected accounts, including spending. Although it can't make any changes to how the money moves around, it can point accusingly at a subscription, leaving me to cancel it myself.

If you haven't done so, the setup is straightforward enough. Using ChatGPT Work on the web, you add the Finances plugin and connect whatever accounts you wish.

You can analyze recent spending right away, but I've found the weekly update from ChatGPT and nearly real-time updates to be particularly useful in my quest to make ChatGPT Plus cover its own cost.

Subscription cuts

Only a couple of weeks after starting to use the feature, ChatGPT raised in its weekly report that one of my streaming services seemed abnormally expensive. It turned out to be due to an add-on costing $11.99 a month.

I had subscribed to watch one particular series, finished it, and then apparently just left the subscription in place. ChatGPT found the repeated charge and placed it beside my other entertainment subscriptions.

A second recurring payment belonged to a music app costing $9.99 a month. I remembered signing up for a trial, but I could not remember using it after the first week. The service had quietly collected nearly $60 since.

Canceling those two subscriptions saved $21.98 a month. ChatGPT Plus had technically paid for itself during the first review, with $1.98 left over. That is not enough to retire on, but it is enough to make my article headline legally defensible.

ChatGPT also spotted that my internet bill had increased by $10 from one month to the next. The promotional rate had expired, but ChatGPT suggested I could still get the savings with the right language. The AI wrote out a few talking points to get me any current discounts. After a surprisingly tolerable phone call, the company applied a new promotion and knocked the $10 back off my monthly bill.

Saving on food

The subscription cuts were easy to measure — I only had to cancel them once and the savings appeared again the following month without any further actions necessary. Food spending was more complicated because there was no single charge I could remove and forget about, but ChatGPT helped me save money there too.

Ordinary takeout is more expensive than ever, but it's the delivery charges and service fees that really raise the final number. I'm not going to stop ordering takeout altogether and deprive myself of all the dishes I can't make myself. But switching to pickup as much as possible would make a big difference, according to ChatGPT. And it saved me about $35 over the next month.

ChatGPT also picked up several trips to convenience stores. Each transaction was small, usually a drink or some paper goods I'd forgotten to pick up at the grocery store. Nonetheless, convenience stores are more expensive than the grocery store, and the result added up quickly, as ChatGPT found in its analysis.

Just staying aware of that fact changed my habits and made me more likely to remember everything I needed to get at my regular shopping run and to bring my own drink when hitting the road.

After two months, the changes were saving me about $67 in a typical month. That figure included $21.98 from the two canceled subscriptions, $10 from the restored internet discount, and approximately $35 from spending less on delivery. Food costs will naturally move around, but the recurring savings alone were already covering the price of ChatGPT Plus.

I wouldn't blindly trust ChatGPT with finances or anything else. And I definitely wouldn't make it my first consultant for any big financial decisions. But these smaller changes are more important than you might think at first.

My Plus subscription still appears on the statement every month, but the reduced streaming and internet costs, not to mention fewer delivery fees, more than justify the $20 a month I'm paying for it.

Cyberattacks are increasing in speed and sophistication, ranking among the biggest threats to businesses of all sizes and industries.

Previously unprecedented costs have made headlines; in October, a report from the Cyber Monitoring Centre revealed that the cybersecurity incident which affected Jaguar Land Rover in August cost the UK economy an estimated sum of 1.9 billion pounds.

Meanwhile, in North America, the aerospace sector has seen a spate of attacks, with WestJet’s June cyberattack resulting in the theft of 1.2 million passengers’ data while the data sets of 1.5 million flyers are believed to be compromised following September’s attack on Collins Aerospace.

Research released earlier this year revealed a stark dip in public trust; when questioned on which industry consumers trusted with their data, no single sector saw an approval rate of above 50%.

Without a clear and modernized security strategy, businesses are leaving themselves vulnerable to the far-reaching consequences of a breach, including reputational damage, operational delays, and financial loss.

Why Zero Trust Matters

AI has given everyone with a computer, tablet, or even smartphone easy access to automation, including those using it with malicious intent. In the cyber space, this allows criminals to continually change their approach, scaling their efforts and exploiting vulnerabilities in their target’s software. To keep up with evolving threats, Zero Trust is vital, prioritizing data over assumptions is not optional.

The contemporary approach to the principle of Zero Trust has been developed from the work of the Jericho Forum, made up of industry experts keen to establish a ‘de-parameterized’ model that enables a more granular and flexible approach to security.

The group, which later became part of The Open Group Security Forum, paved the way for John Kindervag’s popularization of the Zero Trust principle in 2009, emphasizing the importance of 'Never trust, always verify'. In a conversation with Gartner’s Neil MacDonald, he further explained that “Zero Trust is not a technology; it’s a security philosophy that rewires how we think about access”.

It's a smart idea; allowing security systems to keep up with industry change. In reality, however, despite the majority (96%) of companies incorporating, or planning to incorporate, a Zero Trust strategy, only 35% have made it to the implementation stage.

To decrease the frequency of corporate security breaches, this needs to change. The key to success? A mutually agreed understanding of what Zero Trust is and a cross-industry implementation drive.

Steps to a Modernized Security Strategy

The traditional business approach to cybersecurity, including an over-reliance on VPNs, led companies to draw a single ‘perimeter’ around their data. Thus, once breached, cybercriminals were able to steal and duplicate data from across the organization. In contrast, with a strategy led by strict adherence to the Zero Trust principle, access is confined to the singular section where the incident occurred.

The successful implementation of the Zero Trust principle requires a focus on data and information security across all networks and platforms. For example, the evaluation of risk should take place on a case-by-case basis, with deliberate decisions made to accept, mitigate, or transfer. With this approach, security teams have the flexibility needed to safeguard data and, when inevitable breaches do occur, ensure hackers can only access the top layer of information.

The use of Zero Trust as a basis for risk management necessitates a security infrastructure that does not become stagnant but is ever-changing to prevent cyberthreats from impacting the organization. At any point, a key tech stack component can become a target for criminals. In response, to drive resilience, security professionals should track any attempts, and techniques used, amending infrastructure in tandem.

Across sectors, cybersecurity budgets are growing. In March, the IDC's Worldwide Security Spending Guide predicted a spending growth of 12.2% in the year that followed, growing to $377 billion by 2028. Though this reflection of increased enthusiasm to strengthen security infrastructure is a step in the right direction, organizations need to ensure this investment isn’t just a one-off. Every element, and everyone’s access, must be continually questioned to protect from the escalating threat posed by a breach.

Designing a Forward-Looking Security Strategy

Solutions adopted with cybersecurity in mind may differ between organizations but, to drive resilience in the long-term and successfully embrace the principle of Zero Trust, vendor-neutral definitions of methodology and standards will be a necessity.

Once these are widely acknowledged, a commitment should be made to strengthening the underlying security infrastructure over the long-term, driven primarily by the principle of Zero Trust. In a landscape where security threats are ever-evolving, so too should each corporation’s ability to protect themselves from malicious actors. This includes blocking access to valuable data sets in the event of a breach and ensuring each person responsible for security is kept up to date with the latest insight on the nature of threats.

When applied in practice, though the exact methods and vision may differ, the guiding principles should remain consistent. To establish necessary considerations, organizations can start with the Zero Trust Commandments, which include the need for security to be integrated through culture and processes, the implementation of asset-centric controls, and the explicit validation of trust through using all relevant information available.

A news landscape dominated by security breaches and cyberattacks has created a generation of consumers that, more wary than before, are no longer shocked when the personal information they have willingly shared with corporations is taken with malicious intent. It should be expected that they will think twice before trusting a new organization with their information, placing an onus on businesses to prove that their infrastructure is robust.

As we look ahead to 2026, the companies that succeed will prioritize security, consider wider society expectations, and prove their commitment to Zero Trust in each decision they make.

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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Investors will buy your life insurance policy today — and collect the payout when you die.

• Agentforce is now worth around $1.2 billion annually, and climbing
• Customers aren't so sure about their data readiness and agentic maturity
• Many AI projects could be cancelled as users experiment with use cases

Even though Salesforce says its Agentforce business has reached a staggering $1.2 billion in annual recurring revenue, a new report has revealed that partners aren't actually seeing that same surge in revenue.

While the company may be bringing in plenty of revenue from pilots and trials, it seems that customers are yet to see the meaningful results they were hoping for, holding them back from large-scale deployments.

A new TD Cowen report (via The Register) backs this up, uncovering customer dissatisfaction, particularly around data readiness and agent maturity.

Agentforce isn't delivering... yet

According to the survey, 11% of partners hadn't see much immediate interest, with more than half (56%) anticipating upcoming interest but acknowledging that customers need time for initiatives to mature. Only one-third said there was strong interest in Agentforce at this moment in time.

The report also uncovered a 10pp drop in Salesforce partners meeting or beating commercial targets, at 33% this quarter compared with 43% last quarter, with TD Cowen describing adoption as "subdued."

This latest report reflects similar findings from an earlier KeyBanc Capital Markets study (via The Register), where analysts found that customer data still isn't good enough to fully benefit from agentic AI. Around two years after Agentforce was introduced, customers are also dissatisfied with the product's maturity itself.

More broadly, though, it could just be a sign of the broader landscape rather than an Agentforce problem. Last year, Gartner predicted that more than two in five AI projects would be cancelled by the end of 2027 due to factors like "unclear business value" – in other words, this expensive and senseless period of experimentation is just a natural part of the process as users find their feet and reveal the true use cases.

Salesforce is still filled with optimism after transitioning to become an AI-first company – after an "outstanding" quarter, CEO Marc Benioff described agentic AI as "the biggest growth opportunity for [the company's] customers."

For the last two years, many organizations have treated AI adoption as the goal. The more users, tools and experiments, the better. Today, leaders are no longer measuring success by adoption alone. They are asking what it costs, where it creates value and whether the business can afford to scale it responsibly.

That is the next chapter of AI and technology spend management. The companies that thrive in this environment won't necessarily be the ones consuming the most technology. They will be the ones that can connect technology consumption to measurable business value.

This shift from maximizing usage to maximizing value, what I call valuemaxxing, is becoming a defining challenge for technology leaders.

Executives who take these five steps now will be prepared for a future where technology consumption and business value must be measured together:

1. Gain real visibility across the full technology stack

Organizations cannot manage what they cannot see. This becomes far more urgent when costs are variable, distributed and constantly changing.

Today’s technology consumption does not sit neatly in one budget or one system. It spans SaaS applications, cloud infrastructure, data platforms, AI models, agents and infrastructure. AI adds another layer of complexity because spend can show up through tokens, credits, model usage, GPU consumption, data movement and AI-enabled applications.

With only 31% of organizations reporting visibility into AI software today and 59% reporting increased wasted AI spend year over year, gaining a single source of truth across the technology stack has never been more important.

Without a complete view of technology consumption, organizations are left making decisions with fragmented information. Visibility isn't simply about controlling costs; it's about understanding where investment is delivering value and where spend is wasted.

2. Build a governance model for consumption

Many organizations encouraged broad AI experimentation, only to later discover that usage had outpaced oversight. Having an internal governance framework in place is critical to any company’s success. Governance gives teams the guardrails they need to scale responsibly.

For AI in particular, leaders need to move from “use more” to “use better.” It’s figuring out whether AI is improving cycle time, customer experience, operational efficiency, revenue growth, or another important business metric.

To guide the process, increasingly large enterprises (85%) are appointing dedicated teams or senior leaders for AI and tech governance to enable visibility, control, and cross-team collaboration. It’s vital for companies to prevent AI from becoming an uncontrolled cost center.

3. Renegotiate contracts for flexibility and accountability

Technology pricing models are changing rapidly. Long-term fixed agreements may still have a place, but they are becoming harder to manage in environments where usage can shift quickly.

Today, leaders should regularly evaluate vendor agreements to ensure they reflect actual usage patterns and future business needs. This is particularly important as AI providers continue introducing new consumption models and monetization strategies.

Enterprises should expect more pricing complexity, not less. The goal is not simply to negotiate lower costs. It is to create agreements that give the business room to innovate while maintaining control over spend.

4. Align technology, finance and procurement

Usage-based costs impact multiple teams. While technology teams drive how much is used, other departments manage the needed oversight, with finance owning the budget impact and procurement handling vendor contracts. Without alignment, organizations can easily lose control of spending.

The organizations that manage consumption well will build a shared view of usage, cost and value. They establish common metrics, clear accountability, and regular collaboration across departments.

When teams work from the same data and the same definition of value, those decisions become more intentional and avoid costly surprises.

5.Use AI to move optimization from reactive to continuous

Use AI tools to help manage the growing complexity of technology consumption itself.

Optimization cannot remain a periodic budget exercise. By the time a cost issue appears in a report, usage may have already shifted again.

AI can help teams detect unusual usage patterns, surface waste, forecast demand, and support smarter planning across teams. But AI-driven optimization must be connected to human-defined goals. The objective is to help teams make better decisions faster, with clearer insight into what is being used, what it costs and where it creates value.

Turning tech consumption into value

The next phase of enterprise AI will look very different from the first. For the last several years, the focus was on experimentation and adoption. The future belongs to organizations that can demonstrate accountability, governance, and value.

AI has accelerated the industry's shift toward consumption-based technology models, introducing new economic challenges alongside new opportunities. As organizations continue scaling AI, understanding the relationship between usage, cost, and business impact will become a critical competitive advantage.

The AI adoption spree is ending. What comes next is more disciplined visibility, governance, and financial accountability, defining who can successfully scale innovation and who gets overwhelmed by the bill.

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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Frustrated by workflow limits and token-based billing on AI automation platforms? n8n is a “fair-code” automation platform that you can host on your own device or servers, free from the usage restrictions that plague cloud-based platforms.

We’ve covered n8n on TechRadar before, so head over to our first-time user guide and list of compatible hosting solutions if you’re looking for more information. For now, however, I’ll walk you through the exact step-by-step process of setting up a self-hosted n8n environment using Docker, Docker Compose, and a Linux-based virtual machine or server.

What you'll need for this setup

• A virtual machine, server, or NAS with at least 2 vCPUs and 4GB of RAM. Heavier workloads will benefit from more CPU cores and memory.
• A compatible version of Linux installed on your server or machine, such as Ubuntu, Debian, or Raspberry Pi OS. CentOS Stream, Fedora, and RHEL are also supported.
• Access to the Docker and Docker Compose repositories using your Linux distro’s package installer. All of this can be installed through the Linux terminal.
• A managed Kubernetes cluster if you intend to run production-grade workflows (optional).

Step-by-step installation guide for self-hosting n8n

(Image credit: n8n)1. Install Docker and Docker Compose

Power up your Linux terminal. Then update your Linux software catalog by running this command:

sudo apt-get update

This will update your software packages, install any necessary certificates, and prep the system for installing Docker. Once done, execute the next command to install Docker and Docker Compose, along with any dependencies your system needs:

sudo apt-get install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

You can manually confirm that your Docker engine is installed and running by executing this command:

docker --version
docker compose version

2. Write your Docker Compose file

Create a new directory for your n8n setup, then navigate into it:

mkdir n8n-compose cd n8n-compose

Now, you need to create a new .env file inside the new directory. It should look like this:

DOMAIN_NAME=example.com SUBDOMAIN=n8n GENERIC_TIMEZONE=Europe/London SSL_EMAIL=you@example.com

Make sure to replace these values with your domain name, time zone, and email address. If you’re running n8n locally on your device, you can simply remove the domain name, subdomain, and SSL email fields to leave only the GENERIC_TIMEZONE field in there.

Next up, we need to create a compose.yaml file in the same directory along with the .env file. It should read like this:

services:
n8n:
image: docker.n8n.io/n8nio/n8n
restart: always
ports:
- "127.0.0.1:5678:5678"
environment:
- N8N_HOST=${SUBDOMAIN}.${DOMAIN_NAME}
- N8N_PORT=5678
- N8N_PROTOCOL=https
- NODE_ENV=production
- WEBHOOK_URL=https://${SUBDOMAIN}.${DOMAIN_NAME}/
- GENERIC_TIMEZONE=${GENERIC_TIMEZONE}
- TZ=${GENERIC_TIMEZONE}
volumes:
- n8n_data:/home/node/.n8n
- ./local-files:/files

volumes:
n8n_data:

This maps n8n to port 5678 on your device and stores all your workflows, credentials, and encryption key in a Docker volume. Again, if you’re installing locally, you can simply remove the N8N_HOST, N8N_PROTOCOL, and WEBHOOK_URL lines.

In the same directory, create a local-files folder to store all your workflows:

mkdir local-files

(Image credit: n8n)3. Launch n8n

You can launch all your Docker Compose containers simultaneously using a single one-line command:

docker compose up -d

After about a minute or so, run this command to see if the containers are up and running:

docker compose logs -f n8n

You can now open the n8n editor at https://localhost:5678 on your local device using any web browser.

4. Create a n8n account

When you launch the n8n editor in your browser for the first time, it will ask you to create a new account. Enter your email, name, and a password with at least one capital letter and a number. Once you complete the form, you’ll become the instance owner, which is similar to a super-admin in n8n.

This will give your account full access to every workflow and credential, but you should still set up member-level accounts if you intend to have other people use your instance and want to track changes.

5. Build your first AI workflow

You’ll now be able to access n8n’s workflow editor. This is a node-based visual interface that looks a bit like a flowchart with the option to add triggers and actions to create complex automations. If you’ve used a tool like Zapier or Make before, it shouldn’t take you long to figure out the basics.

n8n lets you use the Execute step button to trigger different parts of a workflow during editing, which is useful in testing and troubleshooting. Once you’re confident that everything works, you can save the workflow and toggle it on so that it stays active.

(Image credit: n8n)FAQsIs n8n open-source?

n8n isn’t open-source but free-to-use with certain limitations. It’s distributed under a fair-code license that lets you use the platform for personal or internal business workflows free of cost. If you wish to commercialize it as a consumer-facing product, however, you’ll need to pay for a commercial license.

Does it cost anything to self-host n8n?

There’s some cost involved in setting up a self-hosted n8n environment, but it’s much less compared to how much you’d pay with a cloud-based automation platform with a subscription. Your only expenses here are your hosting costs for the server you use, but even that can be removed if you have a powerful enough local rig that can run workflows on its own.

Does n8n come with its own database?

n8n comes pre-loaded with SQLite on with every installation, which is fine for internal use. If you want to run production workflows, however, I’d recommend switching to PostgreSQL, which can better support complex multi-user workflows.

How do I keep my n8n instance secure?

Make sure to run your n8n instance over an HTTPS connection instead of plain HTTP. If you’re using an external server or a local network that’s shared by other users, take extra care to keep your encryption keys secure and do not put them directly in your .env file. Depending on your server configuration, you can use a secret manager like Azure Key Vault or Google Cloud Secret Manager to avoid attackers from reading your API keys by scanning the source code in plain text.

The European Union's new Tech Sovereignty package highlights a challenging question for governments across Europe, including the UK: how can countries benefit from AI without becoming dependent on technologies developed elsewhere?

AI is becoming a critical driver of economic growth, public service transformation and business competitiveness. Yet much of the AI technology stack continues to be developed and operated primarily in the United States and China, creating a growing tension between AI adoption and strategic control.

Although the UK is pursuing its own approach to AI regulation, European policy developments will continue to shape the environment in which many British organizations build, deploy and govern AI systems.

Recent UK government warnings that Britain must secure "greater control and leverage over frontier AI" show that AI sovereignty is moving from a theoretical debate to a practical policy challenge.

Building every layer of the technology stack domestically is neither practical nor necessary. At its core, AI sovereignty is about maintaining the freedom to choose, adapt and innovate without becoming dependent on any single provider or platform.

Choice, not self-sufficiency

Some countries are pursuing far-reaching self-sufficiency strategies. Others are building on existing infrastructure and expertise while using partnerships to close technological gaps. For most economies, the latter approach is likely to be more realistic. Sovereignty is not about building every component domestically; it is about ensuring strategic control and avoiding excessive dependence on any one supplier.

Regulation may have a role to play. While concerns remain about compliance burdens and their impact on innovation, the broader objective is clear: creating an environment in which organizations can adopt AI with confidence.

This is where dynamic and competitive AI markets become essential. A diverse digital supply chain creates options, strengthens resilience and reduces the risks associated with concentration. Recent restrictions on access to Anthropic's frontier AI models in some non-US markets are a reminder that when access to advanced AI capabilities is restricted, choice itself becomes a strategic asset.

Infrastructure is only useful if everyone can use it

Much of the AI policy debate focuses on the data centers needed to train large models. Yet infrastructure for broad adoption is equally important.

Distributed edge networks located closer to users help deliver AI applications with the low latency, performance and scalability required for real-world deployment. At the same time, access to AI tools must extend beyond a small number of well-resourced organizations.

Usage-based and serverless models can lower barriers to entry by reducing upfront costs and allowing organizations to pay only for the resources they consume. This enables SMEs, researchers, public institutions and larger enterprises alike to experiment with and adopt AI technologies.

Control over data is another critical element. Sovereignty depends less on where data is stored and more on whether organizations can manage access, security and compliance requirements effectively. Global, distributed architectures enable the implementation of access rules and controls over where data is processed and AI applications are operated.

Openness is a strategic advantage

Open standards and interoperable technologies are becoming increasingly important building blocks of digital autonomy. They reduce switching costs, strengthen competition and help prevent dependency on individual providers.

The same principle applies to AI models themselves. Organizations increasingly need access to a range of different open-source and proprietary models, allowing them to select the best solution for different use cases rather than relying on a single platform.

Control through openness

The debate around AI sovereignty is often framed as a choice between dependence and isolation. In reality, the most effective path lies somewhere in between.

Countries do not need to own every layer of the AI stack to exercise meaningful control. What they do need is access to open, competitive and resilient markets that provide genuine choice.

For the UK, and Europe alike, strategic control will come not from limiting access to technology, but from ensuring organizations have the freedom to choose how they adopt, deploy and govern it. In an increasingly interconnected world, that freedom of choice may prove to be the most important form of sovereignty of all.

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• The Ninja CrushBOSS is a blender, food processor and to-go tumbler in one
• It has a 1,200W motor, with presets for precise chopping, slicing and dicing
• It's on sale now for $319 / £239 (about AU$460)

If, like me, you love a good kitchen device you'll be well aware of the perennial problem: finding space for all your gadgets and their accessories on your counter or in your cupboards. So I'm intrigued by the strangely-named but fun-looking Ninja CrushBOSS, which is designed to replace three distinct products: a blender, a food processor and a smoothie maker, all with the same shared base.

The CrushBoss has a 1,200W motor and a 2.1 liter / 72oz jug for blending and a 710ml / 26oz tumbler cup for drinking on the go. And it has a smart menu system that promises to make even the most tedious chores quick and easy.

Ninja CrushBOSS: key features and pricing

The Ninja CrushBOSS's jug has a curved square design to eliminate dead zones, and the SmoothSense system offers optimized blending, presets for chopping and mincing, and a custom control with 10 manual speed settings.

There's an integrated touchscreen display and a straightforward dial control, and it's designed to handle everything from smoothies and ice to shredding, slicing and dicing. There's an optional dicing kit accessory designed to deliver consistent dicing for more intensive tasks such as chopping ingredients for salads, salsa and other ingredients.

It's an interesting alternative to a full food processor whose various bits and bobs require quite a lot of storage: while there are still individual blades and bodies here they're not as numerous as the ones gathering dust at the back of my kitchen units. And if you've been disappointed by all-in-ones in the past, the high power here – 1,200W, which is 100W more powerful than the Ninja BlendBOSS — should make short work of even the toughest veg and effortlessly crush ice for your cocktails.

The Ninja CrushBOSS (including all attachments) is available for $319.99 in the US, and £239.99 in the UK. That's about AU$460, though the Australian release date has yet to be confirmed.

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