🚀 Executive Intelligence Protocol™ (EIP) – Core Edition v1.0
After months of research, writing, and countless iterations, I'm excited to share something I've been building finally.
Everyone is focused on building more powerful AI models.
I became interested in a different question:
How should AI reason when supporting executive-level decisions?
That question became a 223-page behavioral specification defining how AI should:
• reconstruct context before responding
• evaluate assumptions instead of accepting them
• reason through trade-offs
• make transparent recommendations
• support executives rather than generate answers
The result is 74 behavioral requirements, organized into 5 reasoning layers, designed to work with virtually any modern AI model.
This isn't another prompt library.
It's a framework for building AI that thinks with greater structure, accountability, and executive judgment.
I'd genuinely love to hear feedback from founders, AI builders, consultants, researchers, and anyone interested in the future of decision intelligence.
We designed and built a high-trust Framer landing page for an enterprise AI platform, turning complex back-office workflows and policy-driven governance into a high-converting visual experience.
What does practical, agentic AI look like in a real business workflow?
Our new TechFoundry IMS case study walks through seven demos—from purchase-order intake and catalog conflict resolution to vendor orders, shipments, client shipping, and invoice reconciliation.
It shows how AI agents, document processing, and software integrations work together, with human review where judgment matters. I’ve also included the technology stack behind the platform.
This is exactly the agentic AI discussion we need more of — moving from chatbots to actual Ops: PO intake, vendor orders, shipments, invoice reconciliation. That's where ROI is.
Loved the TechFoundry IMS visual — that IMS AI Agent as the central orchestrator with Review & Approve...