Emergent has raised $70 million in new funding as it looks to accelerate the adoption of no-code software development across enterprise and mid-market organizations. The investment underscores growing demand for platforms that allow non-technical users to build, deploy, and scale applications without writing traditional code.

Every engineering team has encountered that one piece of code. It works - technically. It passes tests (most of the time), delivers value, and quietly sits in production like a ticking time bomb wrapped in good intentions. Ask a developer about it, and the response is often the same: “It’s a bit messy, but it’s fine… for now.”

Accenture and Anthropic announced a multi-year partnership designed to advance the adoption of artificial intelligence (AI) within enterprise software development and digital transformation initiatives

When one of your developers would jump out of his well worn chair, hand grabbing his hair and screaming “The server is down!!” - it meant exactly one thing: a very real, very physical machine was catching on fire in a rack somewhere, waiting for an engineer to put out the flames and bring it back to life. You could kick it, reboot it, or bribe it with a fresh config file. But in the serverless era, that comforting ritual has vanished. Now it’s less “find the broken server” and more “solve the my

Forward-thinking organizations are solving this problem by shifting compliance left and embedding it directly into the CI/CD pipeline. The result is a model where security and compliance are not checkpoints at the end, but continuous, automated processes that run alongside development. The question on everyone’s mind is - How can DevSecOps teams automate compliance within CI/CD pipelines, enabling continuous validation, faster delivery, and stronger security outcomes?

In theory, the cloud is sleek, elastic, and endlessly efficient. In practice, it often behaves more like a garage stuffed with forgotten boxes labeled “might need later.”

OpenAI and ServiceNow have announced a strategic partnership aimed at embedding advanced AI agents directly into enterprise software development workflows. The collaboration is designed to help organizations automate complex tasks, accelerate development cycles, and improve operational efficiency across IT and business teams.

The central question is no longer just whether machines can write better tests than humans. It is whether AI systems - training pipelines included - can be built to respect privacy by design. Generative AI in testing relies heavily on data. Systems such as large language models, anomaly detection engines, and automated test case generators need vast and diverse datasets to function effectively. Yet this data dependency increasingly clashes with emerging privacy regulations that limit how persona

A few years ago, training an AI model felt like hosting an all-you-can-eat buffet. The more data piled onto the plate, the happier the algorithm seemed. Engineers collected logs, user clicks, purchase histories, and behavioral signals with enthusiasm. Storage was cheap. Compliance was an afterthought. Everyone went back for seconds. Then the regulators showed up. Suddenly, that generous buffet looked more like a liability. Data retention policies became urgent. Legal teams began asking

Like a snake slithering in the grass, Technical Debt has an uncanny ability to stay hidden - until it suddenly does not. It rarely announces itself with flashing warnings or dramatic system failures. Instead, it shows up as small annoyances: a feature that takes longer than expected, a bug that “should have been simple,” or a release that feels riskier than it used to.

As kids, we were basically tiny demolition experts with no formal training. We broke toys, snapped bike chains, shattered lamps, and occasionally our own bones. Sometimes by accident, and sometimes for fun to see what would happen. And every adult in the…

One of the most common microservices security mistakes is encrypting only north–south traffic (client to service) while leaving east–west traffic (service to service) unprotected. In a Zero Trust model, this is unacceptable.

Microsoft has announced a significant expansion of its GitHub Copilot platform, introducing new enterprise-focused capabilities aimed at improving developer productivity and code quality. The update reflects Microsoft’s continued investment in AI-assisted software development tools as demand grows across large organizations.

Amazon Web Services has unveiled a new set of features designed to simplify serverless application development, reinforcing its position as a leader in cloud-native infrastructure. The updates focus on improving developer experience, observability, and performance across serverless workloads.

Collateralized loan obligation (CLO) managers, who have historically played a major role in funding software firms, are now scaling back investments in the sector. Software-related loans currently make up a significant portion of CLO portfolios, but declining confidence has led to reduced demand and increased risk premiums.

In today’s competitive landscape, marketing is no longer just about selling; it’s about building a brand, creating lasting relationships, and staying ahead of the curve. While traditional marketing tactics may have served your business well

It is hard to believe, but the art of shopping on-line started over 40 years ago, with the introduction of early technology like Electronic Data Interchange (EDI) and teleshopping in the 1970s paving the way for the modern-day E-commerce store and our accompanying empty wallets.

Your dream website will make you billions and you already know how you want it to look like, but having the most beautiful website in the world will not make you a Billionaire.

Everyone is realizing the opportunities that AI can bring to business, unfortunately this also includes people whose business is taking advantage of other people’s business. Those people are realizing the AI can help them commit their crimes and help them steal millions of dollars. In this podcast Dave Erickson and Botond Seres are going to look at how AI can be twisted into a force of evil and crime with Guy Morris - Author and IT Executive. Guy is a retired business executive who spent over 38

Video is now a critical part, if not the most important part of today's online marketing; but today’s algorithms demand more content, more often, just to stay visible. So how do you stand out with original, effective content without burning out or drowning in production demands? In this ScreamingBox Technology and Business Rundown podcast podcast, we are going to look at how AI can help companies generate quality marketing content flows with Lisa Vecchio - Marketing Lead at VEED.

It is hard to believe, but this is the 62nd monthly ScreamingBox Podcast, and everyone wants to know - why is this still a thing after 5 years?!

The Snowflake Data Cloud Summit 2026 (June 1–4 in San Francisco) is shaping up to be one of the most important events of the year for data engineers, AI practitioners, and analytics leaders. Hosted by Snowflake, the summit brings together thousands of professionals to explore how modern data platforms are evolving to support real-time analytics and production-grade AI systems.

The Data + AI Summit 2026, hosted by Databricks, is one of the largest and most technically robust gatherings for data professionals, machine learning engineers, and analytics leaders. The event focuses on the convergence of data engineering, analytics, and AI within unified platforms, with a strong emphasis on real-world implementation.

Red Hat Summit 2026, hosted by Red Hat, brings together developers, platform engineers, and enterprise IT leaders to explore the future of open-source innovation at scale. The event is widely recognized for its deep technical focus on Kubernetes, Linux, hybrid cloud infrastructure, and automation tooling that powers modern application platforms.