Every iOS app I've shipped over the last nine years started the same way: a Rails developer with a great web app, users who want it in the App Store, and weeks spent on Xcode, signing certificates, and Swift boilerplate that has nothing to do with the actual product.
The Google Open Source Software Vulnerability Reward Program team is increasingly concerned about the low quality of some AI-generated bug submissions, with many including hallucinations about how a vulnerability can be triggered or reporting bugs with little security impact.
When a site feels unsafe, unreliable or even slightly "off," users don't rationalize the problem. They react to it. They leave. And in many cases, they don't just abandon the session - they go straight to a competitor.
Just learn to vibe code recently, last week I manage to make a small e-com website for pet shop. After adding tons of new product onto website, I notice my vibe agent been shovel out more error. Whenever I fix one things, my vibe gave out like 3 new bugs. I feel exhausted have to manually checking everything and test this check out button working or not.
A global survey of 2,039 Java developers published today finds 63% reporting that dead and unused code adversely affects their team's productivity, with 22% describing the impact of that technical debt as being severe. Conducted by Dimensional Research on behalf of Azul, a provider of a distribution of OpenJDK, the survey also finds that more than half (56%) now deal with a Common Vulnerability and Exposure (CVE) involving Java on a daily or weekly basis.
Performs root cause analysis based on new evidence from live environments, without needing prior instrumentation. Suggests runtime-validated code changes to eliminate guesswork and reduce rollback-and-redeploy cycles. Performs live issue debugging in safe remote sessions with execution-level behavior inspections.
Kacper Borucki blogged about parameterizing exception testing, and linked to pytest docs and a StackOverflow answer with similar approaches. The common way to test exceptions is to use pytest.raises as a context manager, and have separate tests for the cases that succeed and those that fail. Instead, this approach lets you unify them. I tweaked it to this, which I think reads nicely: One parameterized test that covers both good and bad outcomes. Nice.
I've always found traditional visual HTML editors frustrating because they force you into rigid grid systems. To solve this, I spent the last 1,800 hours building HtmlDrag ( https://htmldrag.com/). It's a "freeform" editor that feels more like Figma or Photoshop but outputs production-ready HTML. Key Features: True Drag-and-Drop: Move elements anywhere on the canvas without grid constraints. URL Import: Import any live website via URL and edit its layout visually. Clean Code Export: No proprietary tags, just clean HTML/CSS.
Web development is an ever-evolving industry. That means we're constantly adapting to what's new, all while maintaining quality and efficiency. No sooner are we comfortable with something than it changes on us. This applies to our workflow just as much as it does to other parts of our business. The way we build websites must align with modern best practices. The good news is that you don't have to scrap your tried-and-true processes. Rather, it's about adjusting to your project's needs.
This extends to the software development community, which is seeing a near-ubiquitous presence of AI-coding assistants as teams face pressures to generate more output in less time. While the huge spike in efficiencies greatly helps them, these teams too often fail to incorporate adequate safety controls and practices into AI deployments. The resulting risks leave their organizations exposed, and developers will struggle to backtrack in tracing and identifying where - and how - a security gap occurred.
A new generation of tools that let anyone - designers, marketers, founders, students - describe an app in plain English and watch it get built in real time. No compiler knowledge. No debugging in terminals. No Stack Overflow. Just a conversation with a machine that builds things.
Your coding apprentice can build, at your direction, pretty much anything now. The task becomes more like conducting an orchestra than playing in it. Not all members of the orchestra want to conduct, but given that is where things are headed, I think we all need to consider it at least.
To find the typical example, just observe an average stand-up meeting. The ones who talk more get all the attention. In her article, software engineer Priyanka Jain tells the story of two colleagues assigned the same task. One posted updates, asked questions, and collaborated loudly. The other stayed silent and shipped clean code. Both delivered. Yet only one was praised as a "great team player."