News JetBrains PHPverse – a community-inspired professional event for PHP developers – returns once more on June 9, 2026. This year, we’re gathering some of the most influential voices in the PHP ecosystem to share their insights on shaping the modern PHP language, the internals of ecosystem tools and frameworks, and the adoption of agentic workflows for shipping PHP code. Expect a one-day event of curated talks, live Q&As with the speakers, several special announcements, and even a few surprises (after all, it’s PHP’s 31st birthday). When: 11:00 am – 3:50 pm UTC on June 9, 2026. Where: Streamed live…
Author: drweb
Early Access Program The Early Access Program (EAP) for the next major PhpStorm 2026.2 release is now open! PhpStorm’s EAP builds are a great opportunity to try upcoming features for free in your real workflows and share feedback with the PhpStorm team. Your input directly influences what makes it into the final release. This release, our main areas of focus are: Native mode for remote development scenarios, as we aim to significantly improve interaction with the projects located on WSL 2 and in Dev Containers. Ongoing enhancements in PhpStorm’s understanding of PHPDoc-based generics. Overall performance and stability improvements, including reduced startup…
News JetBrains PHPverse, un événement professionnel inspiré par la communauté développeurs PHP et conçu pour elle, est de retour le 9 juin 2026. Cette année, nous rassemblons plusieurs des acteurs les plus influents de l’écosystème PHP, qui partageront leurs réflexions et analyses sur l’évolution du langage PHP moderne, les coulisses des outils et des frameworks de l’écosystème, et l’adoption de workflows agentiques pour la livraison de code PHP. Attendez-vous à un événement d’une journée avec des conférences, des questions-réponses en direct avec les intervenants, plusieurs annonces spéciales et même quelques surprises (après tout, c’est le 31e anniversaire de PHP). Quand : de 13h00 à 17h50 CEST le 9 juin 2026. Où :…
Teams spend a lot of time on regression testing. They write scripts to confirm that existing functionality still works after changes. Bugs still escape to production anyway. Not because the tests are poorly written, but because they test assumptions about how the system should behave, not observations of how it actually behaves. A regression test checks what a developer thinks will happen. Production reveals what actually happens. That gap is where escapes live. When a microservice changes its response format slightly, the test might still pass because it checks the expected structure, not the actual structure real clients use. When an…
Engineering teams rarely fail migrations because they lack technical skill. They fail because they measure movement when they should be measuring meaning. Record counts match. New deployments are up. The target control plane is serving traffic. The rollback switch still exists. None of that proves the platform is preserving meaning. It only proves the system is moving. On our multi-cloud team, that distinction was the difference between a migration that ‘looked’ successful and one that actually was. Control planes are where this matters most. A control plane decides what a resource means: Which downstream infrastructure it owns, which tenant it belongs to, what life cycle state it’s in and which operations are safe to perform. If…
I ran into an issue last week where a financial report I was generating had numbers like 1234567.89 printed without any spacing. My manager squinted at the screen for ten seconds before asking if that was a million or a billion. I fixed it with Python’s float formatting, and I have not looked back since. Formatting floating point numbers comes up all the time in data science scripts, financial dashboards, and any tool that prints numbers for humans to read. Python gives you several ways to do it, and I will walk through each one in this article. By the…
DevOps teams have developed reliable software delivery through automated pipelines, repeatable deployments and standard observability. However, AI systems now operate in production environments that these practices do not fully govern, revealing growing gaps. ISO/IEC 42001 is the first international standard for AI management systems. Practitioners should view it not as a compliance formality but as a framework addressing the challenges engineering teams face in production. The Problem With AI in Production Traditional service failures are usually traceable, such as bad deployments, misconfigurations or resource constraints. Ownership is clear, rollback procedures are defined and postmortems follow a standard process. AI systems fail differently. Models that performed well initially can degrade as…
A survey of 700 developers and engineering leaders published this week finds 89% have seen an improvement in the productivity metrics their organization tracks following the adoption of artificial intelligence (AI) tools and platforms, with 81% noting that the amount of time spent reviewing code has increased. However, just under a third of their day is now consumed by AI-related tasks that existing metrics don’t track.Conducted by Harness, a full 94% said technical debt, validation time, and developer burnout are not being tracked by existing productivity metrics. Specific activities not being tracked include time spent reviewing AI code for accuracy…
The AI coding agent market just got a new competitor. Elon Musk’s xAI is rolling out its first coding agent, called Grok Build, in a bid to challenge Anthropic’s Claude and other established tools in the developer workflow space. For DevOps teams already sorting through a crowded field of AI-assisted coding tools, the arrival of Grok Build adds another option — and a few fresh ideas worth paying attention to.What Grok Build IsThe agent, currently in early testing and available only to paying subscribers, can complete complex coding tasks based on user commands. But the more interesting part isn’t what…
I keep coming back to Python’s replace() function whenever I need to clean up messy text data. Whether it’s stripping unwanted characters from a CSV import or standardizing user inputs, replace() handles it without ceremony. No regex needed for simple substitutions. The article covers how str.replace() works, the count parameter, case sensitivity, multiline strings, and common pitfalls. I’ll also show how pandas extends this function to work with entire DataFrame columns at once. By the end, you’ll know exactly when to use replace() and when to reach for regex instead. TLDR str.replace(old, new) swaps every occurrence of old with new…