"Certifications are shifting from a checkbox to a compass. They're less about proving you memorized syntax and more about proving you can architect systems, instruct AI coding assistants, and solve problems end-to-end," says Faizel Khan, lead AI engineer at Landing Point, an executive search and recruiting firm. "In the AI era, fewer students will get trained on the job, which means they have to train themselves," Khan says. "Certifications-especially architectural ones like AWS, Kubernetes, Terraform-are still the clearest path to do that."
Among the releases was the beta version of AI SDK 6, which adds an agent abstraction layer for defining and reusing AI agents in projects. This layer allows developers to specify agent behaviors once and apply them across different parts of an application. The SDK also incorporates tool execution approval, integrating human-in-the-loop processes to review and confirm AI actions before they proceed. Type safety extends across supported AI models and user interfaces, ensuring data consistency and reducing runtime errors through compile-time checks.
The first release candidate of Spring Boot 4.0.0 delivers bug fixes, documentation improvements, dependency upgrades and new features such as: support for the new Spring Framework interface; and completion of modularizing the codebase to " reduce the size of a typical Spring Boot application and provide stronger auto-configuration signals." More details on this release may be found in the release notes and this wiki page.
As modern software systems grow in complexity, they naturally become more modularized and distributed. Rather than maintaining a single, monolithic codebase, development teams increasingly structure their applications as loosely-coupled components. This approach allows teams to work autonomously, focusing on specific areas of the system without the need to grasp its entirety. Traditionally, modularity in software has been driven by technical considerations - separating frontend and backend services based on their runtimes, technologies, or infrastructure needs.
If you've used an AI coding assistant before, you've probably experienced vibe coding. You start with an idea, throw a high-level prompt at the AI, and wait to see what comes out. Sometimes it's close. Sometimes it's completely off. Either way, it often takes several rounds of tweaking to get what you actually want. That endless loop of prompting, generating, and fixing can get frustrating fast.
The platform, developed in collaboration with crypto wallet provider Dfns, combines IBM's infrastructure and security expertise with Dfns' institutional-grade custody and wallet technology. At its core, Digital Asset Haven wants to simplify what has long been a tricky and complex landscape for institutions. Many banks and governments have been cautious about crypto because it involves multiple blockchains, regulatory hurdles, and security risks. IBM's platform wants to change this and consolidate these moving parts, offering a single solution.
I've used so many GNOME and GNOME-based desktops over the years that I can't even recall them all. One thing that has been constant over the years is that GNOME is far more useful than you might think. Sure, it looks minimal, but that's all about getting out of your way and not stripping down features. One of the cool features of the GNOME desktop is the search functionality. At first blush, it seems the search tool is just a means to locate the app you want to run.
IDE Cursor launches version 2.0 with multiple improvements. Up to eight agents can now work in parallel on the same codebase, while a new proprietary model runs 4x faster than comparable alternatives. Voice control is also being introduced. Cursor introduces Composer, the first proprietary agentic coding model. This frontier model is four times faster than equally intelligent alternatives, the company claims. The model can generate and modify code based on natural language.
I pointed out that for software engineers, the code is the product. For research, the results are the product, so there's a reason the code can be and often is messier. It's important to keep the goal in mind. I mentioned it might not be worth it to add type annotations, detailed docstrings, or whatever else would make the code "nice".
The third shift is in the way that AI is reshaping developer choice, not just code. In the past, developer choice referred to choosing an IDE, language, or framework. In the present timeframe, that has changed. GitHub now sees a correlation between the rapid adoption of AI tools and evolving language preferences. This and other shifts suggest AI now influences not only how fast code is written, but which languages and tools developers use.
The core challenges impacting developer productivity and experience are clear. In the 2025 Stack Overflow Developer Survey, nearly half (45%) of developers spend more time debugging AI-generated code than writing it. This, coupled with constant context-switching and manual troubleshooting, leads to significant time loss. New Relic's unified Intelligent Observability Platform addresses these issues by integrating disparate systems and performance data, providing crucial context, and driving actionable insights.
Automated tests are the cornerstone of modern software development. They ensure that every time we build new functionalities, we do not break existing features our users rely on. Traditionally, we tackle this with example-based tests. We list specific scenarios (or test cases) that verify the expected behaviour. In a banking application, we might write a test to assert that transferring $100 to a friend's bank account changes their balance from $180 to $280.
But LLMs took it a notch even further, coders have started morphing into LLM prompters today, that is primarily how software is getting produced. They still must baby sit these LLMs presently, reviewing and testing the code thoroughly before pushing it to the repo for CI/CD. A few more years and even that may not be needed as the more enhanced LLM capabilities like "reasoning", "context determination", "illumination", etc. (maybe even "engineering"!) would have become part of gpt-9
Anysphere has introduced Cursor 2.0, an update to the AI coding assistant that features the tool's first coding model, called Composer, and an interface for working with many agents in parallel. Both Cursor 2.0 and Composer were introduced October 29 by the Cursor team at Anysphere. Cursor is a fork of Microsoft's popular Visual Studio Code editor, downloadable at cursor.com for Windows, MacOS, and Linux.
I've been writing code long enough to remember when computers had 5¼-inch floppy drives and exactly zero network cards. Connectivity was a 2400 baud modem talking to a local BBS via the plain old telephone system. The notion of two computers talking to each other was conceivable-but just the two. The Internet was just a twinkle in the eyes of a few DARPA engineers.
Percona, a provider of open source database support services and Database-as-a-Service (DBaaS), has warned that more than half its MySQL instances remain on MySQL 8.0, support for which ends on April 30, 2026. Peter Zaitsev, Percona co-founder, told The Register: "Every piece of complex software has bugs which may not have been found yet. Some of those bugs are also security bugs.
Leapsome is the AI-powered people platform revolutionizing HR for modern teams. Leapsome drives HR excellence and empowers high-performing teams by automating, connecting, and simplifying every HR process across the employee lifecycle - from onboarding and performance management to engagement and development. Built with ease of use in mind, our platform ensures high adoption by employees, managers, and People teams alike.
Since launching Google Play (née Android Market) in 2008, Google has never made a change to the US store that it didn't want to make-until now. Having lost the antitrust case brought by Epic Games, Google has implemented the first phase of changes mandated by the court. Developers operating in the Play Store will have more freedom to direct app users to resources outside the Google bubble. However, Google has not given up hope of reversing its loss before it's forced to make bigger changes.
They had previously invested in a homegrown command line interface program that would run their entire environment on a continuous integration runner, but it turned out it took 15-30 minutes to get the framework up before even running a test, Chia said. There were also build failures from time-outs, and the developer of the system left the company, and nobody knew how to maintain it.
Microsoft announced in August 2025 that support for the Model Context Protocol (MCP) is generally available in Visual Studio. MCP enables AI agents within Visual Studio to connect to external tools and services via a consistent protocol. The announcement notes that Visual Studio now provides new means to configure and manage MCP servers. MCP, introduced by Anthropic in 2024, is an open standard that simplifies interactions between AI‑enabled development workflows and external systems such as databases, code search engines and deployment pipelines.
Large organizations rarely have just a handful of applications. They have thousands, often representing billions of lines of code. These code bases span decades of frameworks, libraries, and shifting best practices. The result: outdated APIs, inconsistent conventions, and vulnerabilities that put delivery and security at risk. Manual refactoring doesn't scale in this environment. OpenRewrite was created to solve this. OpenRewrite is an open-source automated refactoring framework that enables safe, deterministic modernization for developers.
Businesses around the world come here due to its superior infrastructure, abundant talent pool and supportive business environment; hence businesses from around the globe choose UK mobile app development companies over others globally. In this article, we investigate why so many choose an UK mobile app development or UK web development firm and examine why its tech ecosystem uniquely positions it for global success.
Google has revealed it's ported around 30,000 of its production packages to the Arm architecture and plans to convert them all so it can run workloads on both its own Axion silicon and x86 processors. The search and ads giant documented its move in a preprint paper published last week, titled "Instruction Set Migration at Warehouse Scale", and in a Wednesday post that reveals YouTube, Gmail, and BigQuery already run on both x86 and its Axion Arm CPUs - as do around 30,000 more applications.