Events are essential inputs to modern front-end systems. But when we mistake reactions for architecture, complexity quietly multiplies. Over time, many front-end architectures have come to resemble chains of reactions rather than models of structure. The result is systems that are expressive, but increasingly difficult to reason about.
A router is the hub that sends internet traffic from the modem to every connected device. Even with a fast plan, an outdated or weak router can throttle home internet speed, causing buffering, lag, and slow loading times. This often shows up when multiple people stream, game, or join video calls at the same time.
Long-range radio waves can pass through obstacles more easily, which makes them perfect for monitoring expansive factories or outdoor infrastructure. A recent report by Fabrity highlighted that these systems use very little power. This allows sensors to operate for 5 to 10 years on a single battery. Using such tech means you do not have to install expensive wiring across your entire site.
The answer is to run a wired network connection to your home office. Wi-Fi is great for mobility, but a wired connection offers many advantages when it comes to working from home. It's faster and more reliable, with lower latency, all of which matters if you regularly share large files, participate in high-quality video meetings, or even (ahem) play games.
AI and ML are critical for enabling autonomous, self-optimizing Wi-Fi networks capable of managing dense deployments and real-time performance demands. AI/ML reduces operational costs, improves reliability and security and delivers a more consistent quality of experience. Proprietary approaches, inconsistent data quality, and closed interfaces slow innovation and increase integration costs. Interoperable frameworks - not algorithms - will be key to success. Interoperability must include data models, telemetry, APIs, and model lifecycle management.
For more than a decade now, Ethereum has offered the tantalizing promise of a global computer, available to anyone, that can be used to create decentralized alternatives to Big Tech's data-gobbling monopolies. The blockchain popularized smart contracts, and has been a springboard for thousands of projects backed by billions of dollars. It has also spawned legions of mostly fly-by-night imitators.
Whilst many of the tools of social media - blogs, ugc, forums - are now increasingly brought into new web design and development, there are companies, from British Airways to Lego who view social media as the starting point - not the added feature. Others, such as ruumz.com, are already operating the 'next generation' of social networks with a new blend of online and offline activity.
The internet you experience daily-endless scrolling, algorithmic feeds serving content you didn't ask for, AI-generated slop clogging search results-isn't the only internet available. It's just the one that's easiest to stumble into. You're not stuck with the internet that has evolved alongside the rise of hegemonic platforms. We're 20-plus years into the social internet, and the winners of the last round of audience capture have made clear they're shifting to optimize for social broadcasting instead of networking, to maximize market share and market cap.
Originally developed by Nest (before the Google acquisition), Thread has existed since 2011. Devised as a power-efficient mesh networking technology for internet-of-things (IoT) products, Thread gathered pace after the 2014 formation of the Thread Group, which develops the technology and drives its adoption as an industry standard. Founding members like ARM, Samsung, Google, and Qualcomm have been joined by Apple, Amazon, and many other big companies over the years.
At that point, backpressure and load shedding are the only things that retain a system that can still operate. If you have ever been in a Starbucks overwhelmed by mobile orders, you know the feeling. The in-store experience breaks down. You no longer know how many orders are ahead of you. There is no clear line, no reliable wait estimate, and often no real cancellation path unless you escalate and make noise.
Edge computing is a type of IT infrastructure in which data is collected, stored, and processed near the "edge" or on the device itself instead of being transmitted to a centralized processor. Edge computing systems usually involve a network of devices, sensors, or machinery capable of data processing and interconnection. A main benefit of edge computing is its low latency. Since each endpoint processes information near the source, it can be easier to process data, respond to requests, and produce detailed analytics.
Retail point-of-sale systems today offer a wide range of options for peripherals and hardware. Their technical specifications play a major role in selection, and big retailers often choose multiple vendors to reduce a single point of failure. This gives them an advantage to negotiate price or support as well. Technically, these peripherals also require updating with new models and may have new feature sets. This necessitates the redevelopment of point-of-sale applications, increasing development costs.
Over the past few years, I've reviewed thousands of APIs across startups, enterprises and global platforms. Almost all shipped OpenAPI documents. On paper, they should be well-defined and interoperable. In practice, most fail when consumed predictably by AI systems. They were designed for human readers, not machines that need to reason, plan and safely execute actions. When APIs are ambiguous, inconsistent or structurally unreliable, AI systems struggle or fail outright.
We live in a time where privacy is something we actually have to work to enjoy. Achieving a level of privacy we once had takes work, and you need to start thinking beyond a single desktop, laptop, tablet, or phone -- all the way to your LAN. Before I scare you all off, understand that this starts on the desktop and extends to the LAN. By beefing up both your devices and your network, you'll achieve a level of privacy that you wouldn't otherwise have.
According to Tamas Cser, Founder and CEO of Functionize, the industry is on the verge of a structural shift. By 2026, development teams will transition from AI copilots to agentic fleets: coordinated groups of specialized AI agents operating semi-autonomously across the entire software lifecycle. In this new paradigm, engineering excellence is measured less by syntactic mastery and more by the ability to orchestrate intelligent systems-delegating, validating, and refining work continuously, at machine speed.
Kubernetes Horizontal Pod Autoscaler (HPA)'s delayed reactions might impact edge performance, while creating a custom autoscaler could achieve more stable scale-up and scale-down behavior based on domain-specific metrics and multiple signal evaluations. Startup time of pods should be included in the autoscaling logic because reacting only when CPU spiking occurs delays the increase in scale and reduces performance. Safe scale-down policies and a cooldown window are necessary to prevent replica oscillations, especially when high-frequency metric signals are being used.
For any IT department, these four words are the beginning of a familiar, often frustrating, journey. In our modern world, where business success is built on distributed applications and hybrid cloud architectures, the network is the circulatory system. When it fails, everything grinds to a halt. Yet, despite its critical importance, it often remains a black box-a source of blame that is difficult to prove or disprove.
When I manage infrastructure for major events (whether it is the Olympics, a Premier League match or a season finale) I am dealing with a "thundering herd" problem that few systems ever face. Millions of users log in, browse and hit "play" within the same three-minute window. But this challenge isn't unique to media. It is the same nightmare that keeps e-commerce CTOs awake before Black Friday or financial systems architects up during a market crash. The fundamental problem is always the same: How do you survive when demand exceeds capacity by an order of magnitude?
What Is the Agent Internet? In early 2026, a new layer of the internet has emerged -- one built by and for AI agents. Over 95 platforms now exist where autonomous AI agents communicate, trade, create, play, govern, and conduct research. This is not a speculative whitepaper. It is happening right now. The Agent Internet is a decentralized network of platforms where AI agents -- not humans -- are the primary users.
Moltbook was developed as a sort of experimental playground for interactions among AI "agents," which are bots that have access to and can use programs. Claude Code, a popular AI coding tool, has such agentic capabilities, for example: It can act on your behalf to manage files on your computer, send emails, develop and publish apps, and so on. Normally, humans direct an agent to perform specific tasks.
