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Claude Code for .NET Developers: Agentic Coding in the Enterprise

Veteran enterprise developer Mark Perry explains how Claude Code is changing his .NET development workflow, from understanding legacy business logic and handling multi-repository projects to prompting for better results, controlling scope and reviewing agentic changes.

Agentic Design Patterns: When, Why, and How to Use Them

Microsoft's Jocelynn Hartwig explains why enterprise architects should first ask whether a problem needs an agent at all, and how autonomy, orchestration, human oversight and production complexity should shape agentic AI design.

The AI Productivity Paradox

AI may help employees create more content faster, but increased output, rising expectations, and the need for careful verification can prevent those gains from producing meaningful business value.

From AI Pilots to Platforms: Designing Enterprise-Grade Agentic AI

Samantha St-Louis explains why scaling agentic AI requires more than successful pilots, outlining how reusable architecture, shared context, governance and business-outcome discipline can keep enterprise AI from turning into costly sprawl.

AI Hallucinations: Why AI Confidently Lies and the Business Opportunities It Creates

For business professionals, AI hallucinations can transform a helpful tool into a potential liability.

Can Artificial Intelligence Be Creative? What it Means for Business

AI lacks human intent but delivers functional creative value to businesses -- the key is treating it as a collaborative tool that enhances human creativity rather than replacing it.

The AI Coding Revolution: Productivity Boom and Employment Crisis

AI coding assistants are rapidly moving from helper tools to autonomous development agents, boosting software productivity while accelerating disruption in technology hiring -- especially for routine engineering roles.

Explainable AI: Why Black Box Models Are a Problem

Explainable AI helps organizations improve trust, governance, and accountability by making model decisions understandable in high-stakes business scenarios.

Why Data Is the Real Artificial Intelligence

Data -- not sophisticated algorithms -- is the true driver of AI competitive advantage, as companies with proprietary, high-quality datasets build compounding feedback loops that are far harder to replicate than any model architecture.

The Ethics of Ethical AI

The concept of ethical AI concentrates enormous decision-making power in the hands of fewer than 70 people worldwide -- raising serious concerns about cultural bias, corporate virtue signaling, and ethics committees dominated by developers with increasingly outdated technical skills.

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