Greetings, Future Tech Titans! 👋

Over the past few weeks, we went on a fascinating dive into one of the newest developments shaking up the AI landscape: the Model Context Protocol, or MCP. What we found challenged our assumptions, sparked our imagination, and left us more excited than ever about what’s coming — even though we aren't integrating AI agents into our business just yet.

In this newsletter, I’m sharing my personal reflections on our exploration of MCP and what it could mean for the future of AI-driven work. We’ll dive into:

• The hidden problem MCP solves: Why connecting AI to tools has been harder than it should be.

• How MCP works: A simple, powerful model that changes everything.

• A real-world glimpse: How MCP turned theory into possibility for us.

• My personal take: What it means, where we’re headed, and why I’m more optimistic than ever.

If you’re ready to think beyond today’s AI hype and glimpse what true AI collaboration might look like, this one’s for you.

Erwin Dwight

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FREE CONTENT

MCP Unveiled: The Mind-Blowing AI Protocol Redefining Integration Forever

What if AI could seamlessly collaborate with your tools and data without the chaos of custom coding? That’s the electrifying promise of the Model Context Protocol (MCP), a revolutionary standard that’s turning heads in the AI world—and we couldn’t resist diving in. Over the past few weeks, we’ve explored MCP not as developers integrating it, but as curious minds peering into its potential to transform how AI interacts with everything from databases to GitHub repos. What we found wasn’t just a technical marvel—it was a glimpse into a future where AI becomes a true workflow partner. Join us as we share our personal journey, unpack MCP’s genius, and reveal why it’s sparking excitement even for those of us not yet wiring it into our businesses.

FREE CONTENT

Steps to build an engineering strategy

Will presents a systematic five-step method for developing a successful engineering strategy: Exploration, Diagnosis, Refinement, Policy, and Operations. He stresses that even though adhering to these steps does not ensure success, they can help prevent the usual mistakes made by busy individuals who tend to overlook challenging aspects. Nevertheless, the framework can be modified as necessary.

FREE CONTENT

Shared Understanding At Scale

In this post, John explores information management challenges in organizations through five themes. He examines how goal hierarchies often become unnecessarily complex and how information-gathering approaches affect leadership decision-making. John argues against the myth of a single perfect dashboard, emphasizing that effective views must be purpose-specific. He also warns against over-nesting workflow loops when different processes operate at varying speeds. Additionally, he explains how organizational models compress complexity, reflecting power dynamics and inadvertently prioritizing certain work.

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That’s it for this episode!

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