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Software Development

Is IBM i Ready for AI Coding Without Git-Native DevOps?
DevOps
Is IBM i Ready for AI Coding Without Git-Native DevOps?

Lead: The Moment AI Met the Green Screen Across busy IBM i shops, a quiet shock rippled as developers watched AI assistants generate usable RPG, CL, and DDS in minutes—code that compiled, ran, and even passed early tests without the usual handholding many expected to be required for legacy platforms once considered immune to such leaps. That speed thrilled management

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Is Adversarial Testing the Key to Secure AI Agents?
AI and ML
Is Adversarial Testing the Key to Secure AI Agents?

The rigid boundary between human instruction and machine execution has dissolved into a fluid landscape where software no longer just follows orders but actively interprets intent. This shift marks the definitive end of predictability in quality engineering, as the industry moves away from the comfortable “Input A equals Output B” framework that anchored software development for decades. In this new

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Autonomous AWS Frontier Agents – Review
AI and ML
Autonomous AWS Frontier Agents – Review

The long-standing dream of a self-healing cloud infrastructure has finally shifted from experimental whiteboards to production environments with the introduction of the Autonomous AWS Frontier Agents. These tools represent a fundamental departure from the era of generative AI chatbots that merely suggest code or summarize logs upon request. Instead, AWS has pivoted toward task-oriented systems capable of independent reasoning and

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Will New Hires Help Legit Secure AI-Native Development?
Core HR
Will New Hires Help Legit Secure AI-Native Development?

Lead: A Market Racing Ahead Code increasingly arrived not only from humans but from coding agents sprinting through backlogs, and with that speed came tangled risks—opaque attack paths, model abuse, and policy drift that hid inside automated workflows.Enterprises that chased velocity discovered a new truth: getting AppSec wrong in the AI era did not just mean missed tests; it meant

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Can AI Now Find Critical Zero-Days in Minutes?
AI and ML
Can AI Now Find Critical Zero-Days in Minutes?

The rapid evolution of large language models has fundamentally altered the cybersecurity landscape, moving past simple code completion into the realm of autonomous security research. In today’s digital environment, the speed at which a system can be compromised is no longer limited by the biological constraints of human analysts but is instead dictated by the sheer processing power of advanced

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Trend Analysis: Agentic AI in Software Engineering
DevOps
Trend Analysis: Agentic AI in Software Engineering

Weeks collapsed into hours as agentic AI rewired Motorway’s delivery engine, turning cautious release trains into a high-velocity, test-anchored pipeline that ships faster and breaks less, while reframing code itself as disposable fuel for evaluation rather than an artifact to preserve. The shift mattered because volume without discipline creates fragility; Motorway’s answer—spec-first rigor, governance-as-code, and lifecycle integration—revealed how to unlock

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Is Plain Text the New Executable in AI Security?
Cyber Security
Is Plain Text the New Executable in AI Security?

Lead: When a README Becomes an Attack Vector A single, well-placed sentence inside a memory file quietly rewrote an AI coding assistant’s habits, tilting choices toward insecure defaults and scattering hardcoded secrets through production branches before anyone spotted the pattern.It sounded improbable until a routine dependency install triggered a post-install script that edited a local memory.md file, which the assistant

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Is Tencent’s Hy3 the Blueprint for Efficient, Deployable AI?
AI and ML
Is Tencent’s Hy3 the Blueprint for Efficient, Deployable AI?

Procurement teams had stopped asking who owned the biggest model and started asking which model could hit latency budgets, run inside a 256K context, and still clear month-end cloud invoices without red lines. Tencent’s Hy3 preview entered exactly that conversation with an unusual stance for a flagship: 295 billion total parameters but only 21 billion activated at inference, a measured

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How Should You Choose Between Waterfall, Agile, and DevOps?
DevOps
How Should You Choose Between Waterfall, Agile, and DevOps?

Selecting an optimal software development methodology has become a defining factor for corporate survival in an era where digital infrastructure underpins every facet of the global economy. As organizations navigate the complexities of 2026, the decision to implement a specific framework is no longer relegated to technical leads but occupies a central position in executive strategy. The choice between Waterfall,

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Alipay AI Pay Enables Payments for Autonomous AI Agents
Robotic Process Automation In Fintech
Alipay AI Pay Enables Payments for Autonomous AI Agents

As we stand at the threshold of the “agentic commerce” era, the landscape of digital payments is shifting from manual transactions to autonomous interactions facilitated by AI agents. Our guest today has been at the forefront of this revolution, observing how these intelligent tools—affectionately known as “lobsters” in certain markets—are reshaping the way consumers and developers interact with financial systems.

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How Will Open Source Evolve in the Era of AI?
AI and ML
How Will Open Source Evolve in the Era of AI?

The rapid rise of artificial intelligence is fundamentally altering the landscape of software development, forcing a reevaluation of what it means for a project to be truly “open” in a world where machines frequently act as primary contributors. Traditionally, the open-source movement focused almost exclusively on the accessibility of source code and the transparency of licensing agreements that allowed for

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How Local-First Tools Improve Node.js Security Workflows
Cyber Security
How Local-First Tools Improve Node.js Security Workflows

The modern landscape of Node.js development has reached a critical juncture where the proliferation of automated security scanners often creates more friction than it resolves within the typical engineering lifecycle. While the industry is currently saturated with various security platforms, a profound “workflow shortage” remains the primary obstacle to achieving true software resilience. Developers frequently find themselves at the end

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