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MCP Security Pitfalls: Exposing the Hidden Risks Powering Agentic Workflows

Model Context Protocol (MCP) unlocks powerful new Agentic workflows but also brings hidden security risks. Learn how attackers exploit common weaknesses in MCP-powered workflows to steal data and take over your AI agents.

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The Cost of Feature Bloat: How to Say No to Unnecessary Features and Focus on Core Value

In the race to innovate, even the best products can become cluttered and complex. This guide provides a clear framework to spot feature bloat, say ‘no’ effectively, and anchor your product roadmap to core user value.

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The Cost of Bad Hires in Engineering: How to Spot Red Flags Before Making an Expensive Mistake

Bad engineering hires cost more than time and money; they impact team morale, project quality, and your credibility. Discover proven interview techniques to spot red flags early and hire with confidence.

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Good Names, Clean Code: A Developer’s Guide to Clarity

Discover practical tips for mindful code naming to create a foundation of readable, maintainable, and collaborative code, and understand how it drives better development outcomes.

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MCP under the hood

If you’ve been following the exciting developments in AI, you may have encountered the Model Context Protocol, or MCP. This article uses a real-time weather query via the Claude Desktop App to walk through how MCP works under the hood, step by step.

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Hiring AI & ML Engineers: What Skills Actually Matter in Real‑World AI Development?

Curious what sets a top-tier AI & ML Engineer? It involves more than evaluating resumes or checking for framework fluency. This guide outlines the four essential skills every AI & ML Engineer needs to thrive in real-world projects.

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AI system development: LLM → RAG → AI Workflow → AI Agent

Confused by LLMs, RAG, & AI Agents? We break down the spectrum of AI system design with a familiar resume-screening example to show the leap in capabilities (and complexity) at each level.

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From AI Hype to Real Value: Four Pillars of Successful Generative AI Deployment

In this article, we explore 4 key pillars for deploying Generative AI using the corporation’s own data. By integrating a robust data strategy, skilled talent, clear application plans, and proactive risk management, you can turn AI ambition into real, measurable business success.

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Best Practices in Prompt Strategy & Prompt Engineering: A Real-World AI Storyboarding Case Study

This in-depth exploration of prompt engineering best practices showcases a real-world AI storyboarding project. We'll demonstrate how applying clear strategies and iterative refinement techniques significantly enhances the quality and coherence of AI-generated narratives.

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Launching the Communication & Media Product Vision in Canada

Explore how to launch the Communication & Media product vision in Canada’s market with trends, challenges, strategies, and case studies to drive success.

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