Here's what caught my eye in the world of AI this week:

1. Every AI Copyright Lawsuit in the US, Visualized

   The AI copyright battlefield is heating up, with a pivotal lawsuit, Thomson Reuters v. Ross Intelligence, setting the stage back in 2020. Initially a niche debate, this case foreshadowed a tidal wave of legal challenges from authors, artists, media giants, and music labels accusing AI companies of improperly using copyrighted content to train powerful models. At the heart of the fight is the "fair use" doctrine—can AI development justify unlicensed use of copyrighted material? With major players like OpenAI, Google, and Meta now embroiled in lawsuits, the stakes couldn’t be higher for the future of AI innovation and the broader digital information ecosystem.

Quote of the week

2. What are the five goals you want to achieve professionally and how will you know you have simply and objectively achieved them?

Why Goals Matter:

Goals are your personal GPS, keeping you on course toward growth and purpose. They provide clarity, motivation, and a clear benchmark to measure your progress and celebrate your wins!

My goals are a work in progress. I am still refining mine to be more Outcome vs. Output:

1. Meet and/or Exceed all my work goals

2. Read four books in the field of AI / New Technology / Take four trainings course and/or attend conferences so that I have deep valuable knowledge to share at work and with my subscribers.

3. Post one Beehiiv / LinkedIn Newsletter per week

4. Post 3 - 5 LinkedIn posts a week

5. Create Awesome content for my subscribers so that my YouTube Channel organically grows to 1,500, and Beehiiv Newsletter to 10,000.

3. Four Ways to Exponentially Multiply Your Enterprise AI Success

Executive Summary

Data is the foundation of AI success, and in the era of generative AI, how businesses manage their data determines whether they gain a competitive edge or fall behind. Generative AI transforms processes like drafting RFPs, but its efficiency depends on clean, organized, and high-quality data. By mastering four critical pillars—Discover, Understand, Govern, and Use—organizations can unlock "AI brilliance," leveraging generative AI to create transformative efficiencies, minimize risks, and amplify business outcomes. Now is the time for companies to treat their data as a strategic asset, setting the stage for innovation and sustainable competitive advantage.

Key Takeaways

1. Data Prep Powers Generative AI

   • Generative AI thrives on structured, high-quality data. Properly managing contracts, proposals, and unstructured data ensures AI outputs are accurate, efficient, and trustworthy.

   • Without robust data preparation, AI risks producing errors, creating inefficiencies instead of solving them.

2. Four Pillars of Data Excellence

   • Discover: Locate and identify data across diverse repositories, including unstructured sources like emails and social media.

   • Understand: Classify and differentiate data, like contracts or policies, for better insights and management.

   • Govern: Secure and regulate data to meet compliance and lifecycle requirements.

   • Use: Leverage organized data to generate actionable insights and maximize AI potential.

3. AI Brilliance Equals Competitive Advantage

   • Industries from insurance to government are revolutionizing processes with generative AI, creating time savings and uncovering new possibilities.

   • Organizations with clean, governed data are best positioned to amplify AI’s impact, driving innovation and long-term success.

Pro Tip: Embrace data management now to transform it into a strategic powerhouse. It’s your ticket to unlocking the full potential of AI and staying ahead in a competitive landscape.

4. The Rise of AI Agents: What Enterprises Need to Know for 2025

This week, we’re diving into the transformative world of AI Agents—the buzzword everyone’s talking about, but few truly understand. 2025 is poised to be the year AI agents move from concept to real-world enterprise deployment. But here’s the catch: success hinges on mastering the foundational pillars of AI success—Discover, Understand, and Govern your data—as explored in Four Ways to Exponentially Multiply Your Enterprise AI Success.

Even more critical is distinguishing AI agents from their less sophisticated counterparts: automation and AI workflows. Why does this matter? Because too many so-called "agents" are merely workflows or automations in disguise, and understanding the distinction is key to using the right tool for the right task.

The Key Differentiators:

• Automations: Rule-based systems that execute predefined tasks—fast, reliable, but rigid.

• AI Workflows: Automations enhanced with LLMs (like ChatGPT) for specific steps—adding flexibility but still deterministic.

• AI Agents: Adaptive, autonomous programs designed for non-deterministic tasks, capable of handling new variables and scenarios.

AI agents are the ultimate goal, but they require robust data preparation, governance, and strategic deployment. Businesses eager to leap into AI should first assess their needs—whether automation, workflows, or true AI agents—and focus on solving real-world problems, no matter the tool.

Insight: Success with AI isn’t about chasing trends—it’s about mastering your data, understanding the tools, and driving results with precision and purpose.Author - Tomas Chamorro-Premuzic

5. Introduction to AI Agents

   AI agents are taking automation beyond simple chat interfaces, and 2025 is set to be their breakout year. This free hour by Allie K. Miller breaks down AI agents and Claude computer use so business leaders can understand and implement this technology. Enroll now to see how AI agents can transform your daily operations and position your team for success in the AI-first future.

6. Friday Funnies 🤣.

My favorite Bond, Daniel Craig a close #2.

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7. Building effective agents

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   Building on Allie K. Miller’s video, Anthropic recently published a must-read article on crafting AI agents, emphasizing the importance of simplicity and transparency. One critical takeaway: avoid the common pitfall of overcomplicating solutions with flashy, cutting-edge techniques. Often, a simpler approach not only solves the customer’s problem effectively but is also easier to maintain, delivering long-term value without unnecessary complexity.

Writer RAG tool: build production-ready RAG apps in minutes

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Integrated into Writer’s full-stack platform, it eliminates the need for complex vendor RAG setups, making it quick to build scalable, highly accurate AI workflows just by passing a graph ID of your data as a parameter to your RAG tool.

Learn more about our production ready RAG tooling here.

8. Impressive Growth

Until next time, take it one bit at a time!

Rob

Thank you for scrolling all the way to the end! As a bonus check out the below electricity demand forecast. Here’s my crystal ball prediction: the real winners in the AI Gold Rush won’t just be those mining for AI breakthroughs—it will be those supplying the "picks and shovels." During the original Gold Rush, everyone needed tools like picks and shovels to dig for gold. In today’s AI boom, the modern "tools" are power, chips, and data centers—the essential infrastructure driving AI innovation.

Over the next five years, investing in these foundational industries will position you to thrive as demand skyrockets. Power the revolution, and you'll never be on the losing side. The future is in your hands—build it wisely.

P.S.

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