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At Broadcom’s Spark VSM Summit—“VSM evolution meets AI revolution”—SD Times sits with VSM head Jean Louis Vignaud to explore AI’s impact on value stream management. Key takeaways include – AI automates tasks, assesses risk and progress, and augments work like user stories, while VSM offers the alignment, visibility and metrics AI needs. Top use cases include resource forecasting, strategic investment alignment and compliance flagging. Executives should break down silos, shift to product-based funding and boost AI literacy. Companies must tidy data and use VSM systems to capture proprietary knowledge. Vignaud predicts VSM will manage business knowledge as an asset with human–AI teams that adapt and optimize. Read the full article here . The post How AI Further Empowers Value Stream Management appeared first on SD Times . from SD Times https://ift.tt/EMWpGxB

MetaTrader 5 (MT5) is an advanced trading platform supporting a multitude of different assets like Forex, cryptos, commodities, and so on. It is incredibly popular among Japanese traders and regulated brokers. Many programmers in Japan are employing its MQL5 programming language to develop advanced trading algorithms and we are going to explain how they are using MT5 for advanced algorithm development and trading below. Identical syntax to C/C++ MT5 is free and offered by many reputable brokers that are regulated in Japan, making it a simple process to use the platform’s advanced features.  The main advantage of MQL5 is its similarity to the popular programming language C++, which makes it very easy to adopt and learn. The syntax of MQL5 is nearly identical and data types are also familiar, like int, double, char, bool, and string. Functions are declared and used the same way, and MQL5 also supports classes, inheritance, and other OOP (Object-Oriented Programming) objects like...

At Broadcom’s recent Spark VSM Summit, the theme was “VSM evolution meets AI revolution.” After the event, SD Times sat down with Broadcom’s Jean Louis Vignaud, the head of ValueOps at the company, to discuss the AI revolution and its connection to value stream management. This interview has been edited for length and clarity. DR: Everyone is talking about AI. But I’m curious to know how AI can make value stream management better. JLV: There are two powerful ways AI and VSM intersect. First, AI and VSM workflows, automating repetitive tasks, analyzing risk and progress and helping users create better, more complete artifacts like investment requests or features. And second, VSM provides the structure AI needs to thrive through alignment, visibility and measurable outcomes. DR: So, people who are implementing AI now with their value stream, what are the most promising use cases that you are seeing from your customers? JLV: From my perspective, AI is making a real impact across ...

AI technology is disrupting industries at unprecedented speed, yet Gartner research reveals 47% of AI initiatives fail to reach production. This session examines how enterprise-grade AI capabilities, now accessible to businesses of all sizes, are fundamentally transforming operations, while organizational readiness lags critically behind. Through case studies from financial services, manufacturing, and healthcare, attendees will discover how Broadcom’s integrated framework, which combines technology roadmapping, value stream management, and workforce development, converges. This webinar demonstrates how this approach aligns AI investments with corporate initiatives to deliver measurable financial returns, with top performers achieving 7.2% higher operating income growth. Our four-phase methodology—Assessment, Planning, Implementation, and Evaluation—provides a clear path to quantifiable business results across industries. The session follows a compelling narrative arc from AI dis...

APIs underpin most modern software systems. Whether you’re building a SaaS dashboard, a mobile app, or coordinating microservices, how you expose your data shapes your velocity, flexibility, and technical debt. Through several years of building production systems with React and TypeScript, I’ve shipped REST, GraphQL, and tRPC APIs. Each option presents distinct strengths, with real-world tradeoffs developers and engineering leaders should understand. This guide compares these technologies from a practical engineering perspective, focusing on architecture, type safety, toolchains, and developer experience. API Approaches Explained REST: The Web Standard REST (Representational State Transfer) organizes APIs around resources, linked to URL endpoints (e.g., /users/42 ). Clients interact using standard HTTP methods ( GET , POST , PUT , DELETE ). It’s simple, widely supported, and language-agnostic. GraphQL: Flexible Queries GraphQL, developed by Facebook, enables clients to query ...

The Eclipse Foundation today announced the release of Jakarta EE 11 Platform, which builds on the releases of the Core Profile in December 2024 and Web Profile in March.  This update adds significant enhancements, including a modernized Test Compatibility Kit (TCK) framework, updates to several specifications, and a new data specification. According to Tanja Obradovic, senior director of Java Programs for the Eclipse Foundation, TCKs are essential for testifying the quality of any application built based on Jakarta EE.  Part of the modernization includes moving from Apache ANT and Java Test Harness to JUnit 5 and Apache Maven. The structure of the TCKs themselves were also streamlined to reduce complexity so that they are easier to learn and use.  “The work that has been put into TCK is tremendous,” Obradovic said. “First off, we’re going to be able to enhance the pool of contributors and committers in that project because we’re using more modern tools. The second thi...

Qodo , maker of an AI coding platform, today announced the release of Qodo Gen CLI, an agent framework that enables developers to create, customize, and deploy their own AI coding agents. With the framework, creating agents can be done by writing configuration files that add autonomous AI agents throughout the software development life cycle, according to the company’s announcement. “Every developer should be able to create their own AI agents, just as they create scripts and automation today,” said Itamar Friedman, CEO and co-founder of Qodo. “By making agent creation simple and accessible instead of requiring complex AI engineering, we’re democratizing access to real automation that teams fully control.. Now a developer can create a custom agent for their unique workflow in minutes, not months.” Qodo was built to help developers  add autonomous coding capabilities to their applications without requiring expertise in AI systems, which can lead to solutions that sync up with an ...

Warp is undergoing a significant transformation with its 2.0 launch, shifting from its origins as a terminal emulator with AI integrations into an Agentic Development Environment (ADE).  “The products on the market today, from AI IDEs to CLI coding agents, all miss the mark supporting this workflow. They bolt agents onto code editors through chat panels and bury them in CLI apps. What’s needed is a product native to the agentic workflow; one primarily designed for prompting, multi-threading, agent management, and human-agent collaboration across real-world codebases and infrastructure,” Zach Lloyd, the company’s CEO and founder, wrote in a blog post .  Lloyd says that Warp 1.0, aka the terminal, was the foundation for supporting this workflow, because being a terminal allowed it access to proper context for working across projects and tasks. However, where it fell short was its lack of primitives for managing multiple agents, controlling their permissions, and giving them m...

The Overture Maps Foundation today announced the launch of its Global Entity Reference System (GERS), which assigns a unique ID to geospatial entities, including 2.6 billion buildings, 61 million places, 321 million road segments, and almost 447 million addresses.  The system will allow developers to more easily join datasets, share information, and onboard new data, without the complexity of trying to conflate different sources of data that may have different names for the same geospatial entity.   According to Marc Prioleau, executive director of the Overture Maps Foundation, an explosion in mapping data has led to an increase in expectations as well, such as people wanting real-time traffic conditions on their route or to know what specific lane of a road to be in.  “What that means is now you’re pulling together data not just from a single data supplier, but more like a dozen or 20 suppliers, and you’re trying to conflate all that data to the same thing,” said...

The Android development team has announced the addition of Agent Mode for Gemini in Android Studio.  With Agent Mode, a developer can describe a complex goal, then the agent will come up with an execution plan and then complete the tasks.  Examples of tasks Agent Mode can tackle include building a project and fixing errors, extracting hardcoded strings and migrating them to strings.xml, adding support for dark mode to an app, and implementing a new screen in an app from a screenshot.  Developers will have the ability to review, accept, or reject any of the agent’s proposed changes, or ask it to iterate on their feedback. There is also an auto-approve feature that can be enabled for situations when a developer wants to iterate quickly on ideas.  The default Gemini model has a no-cost daily quota with a limited context window, or a developer can add their Gemini API key to significantly expand the context window.  Agent Mode also supports MCP so that the agen...

At the Open Source Summit North America, it was announced that Google donated its Agent2Agent (A2A) protocol to the Linux Foundation. The A2A protocol offers a standard way for connecting agents to each other. In this way, it complements Anthropic’s Model Context Protocol (MCP) , which provides a way to connect agents to different data sources and applications. “Drawing on Google’s internal expertise in scaling agentic systems, we designed the A2A protocol to address the challenges we identified in deploying large-scale, multi-agent systems for our customers. A2A empowers developers to build agents capable of connecting with any other agent built using the protocol and offers users the flexibility to combine agents from various providers,” Google wrote in a blog post when it first launched A2A in April.  When it was first announced, Google revealed that there were over 50 partners contributing to the project, including Atlassian, Cohere, Datadog, Deloitte, Elastic, Oracle, a...