-
AI StrategyMCP Tutorial for Brand Teams: What You Actually Need to Know
TL;DR — Key takeaways Over 1,500 pre-built MCP servers are publicly available today — most brand teams will never need to write one from scratch. The MCP Adoption Ladder™ (Consume → Configure → Customize) cuts enterprise onboarding time by more … Read More
Carlos Martínez Barriga 12 min read
-
AI StrategyMCP Claude: How Brand Teams Connect AI to Their Real Systems
TL;DR — Key takeaways MCP (Model Context Protocol) hit 97M+ monthly SDK downloads by early 2026 — it is now the default way Claude connects to enterprise tools. Claude is the only major AI model where MCP was designed in-house, … Read More
-
AI StrategyClaude MCP for Brand Teams: The Decision Framework
TL;DR — Key takeaways Claude + MCP gives AI agents secure, real-time access to your brand’s live data — ERP, PIM, catalog systems — without rebuilding your integration layer from scratch. The brands moving fastest with Claude MCP are not … Read More
-
AI StrategyAnthropic MCP: What Actually Changed for Brand Teams
TL;DR — Key takeaways Anthropic launched MCP in November 2024; by mid-2026 it has 97M+ monthly SDK downloads and 5,800+ servers across the ecosystem. In December 2025, Anthropic donated MCP to the Linux Foundation’s Agentic AI Foundation — removing every … Read More
-
AI StrategyMCP Anthropic: What Brand Leaders Need to Know Now
TL;DR — Key takeaways Anthropic launched MCP (Model Context Protocol) in November 2024 and donated it to the Linux Foundation’s Agentic AI Foundation in December 2025 — it is now a vendor-neutral open standard, not Anthropic’s proprietary tool. 78% of … Read More
-
AI StrategyWhat Is Model Context Protocol? The Executive Guide
TL;DR — Key takeaways MCP (Model Context Protocol) is Anthropic’s open standard for connecting AI agents to external tools — adopted by OpenAI, Google, and Microsoft within its first year, with 2,000+ servers in the official registry. Without MCP, connecting … Read More
-
Epinium newsletter · no fluff, no spam
Every week, the most useful AI insights for your brand
I'm Carlos, CEO of Epinium. I share what actually moves the needle for brands and manufacturers.
Welcome aboard!Check your inbox to confirm your subscription.
-
AI StrategyWhat Is Model Context Protocol? The Brand Leader’s Guide
TL;DR — Key takeaways MCP (Model Context Protocol) is the open standard that lets AI agents connect to any business system — ERP, CRM, PIM, Amazon Vendor Central — through a single interface instead of dozens of bespoke connectors. Anthropic … Read More
-
AI StrategyWhat Is MCP: The Business Leader’s Guide to Model Context Protocol
TL;DR MCP (Model Context Protocol) is an open standard that lets AI agents connect to any data source or business tool without custom-coded integrations for each pair. Anthropic released it in November 2024; OpenAI, Google, and Microsoft adopted it by … Read More
-
AI StrategyModel Context Protocol Implementation: The Enterprise Roadmap
TL;DR — Key takeaways 71% of AI teams spend more than a quarter of their implementation time on data integration — MCP eliminates that tax, but only with the right sequencing (CData, 2026). The MCP Adoption Ladder™ breaks enterprise implementation … Read More
-
AI StrategyModel Context Protocol: Enterprise Security and Governance Guide
TL;DR — Key takeaways MCP hit 97M+ monthly SDK downloads in its first year — but over 1,800 active servers ship with no authentication enabled. The adoption curve and the security curve are dangerously out of sync. OAuth wasn’t part … Read More
-
AI StrategyModel Context Protocol for Brands: The Decision Framework Most Teams Skip
TL;DR — Key takeaways With 97M+ monthly SDK downloads and backing from OpenAI, Google, and Microsoft, MCP is settled infrastructure — the question is no longer whether to adopt it, but which strategy fits your current AI maturity. The “USB-C … Read More
-
AI StrategyModel Context Protocol: What Brand Managers Must Know
TL;DR — Key takeaways The Model Context Protocol is the de facto standard for connecting AI agents to enterprise tools — 78% of enterprise AI teams have at least one MCP-backed agent in production as of April 2026. MCP is … Read More
-
AI StrategyModel Context Protocol Server: Architecture Guide for Business Teams
TL;DR — Key takeaways Anthropic released MCP in November 2024; by March 2026, over 10,000 public MCP servers are live with 97 million monthly SDK downloads. MCP is not a developer tool — it is an architecture decision that determines … Read More
-
AI StrategyMCP Server: What Enterprise Brands Must Know Before Deploying AI in 2026
TL;DR — Key takeaways MCP (Model Context Protocol) is an open standard that lets AI agents connect to your systems, data, and tools — solving the N×M integration problem that was quietly killing enterprise AI ROI. From zero to 2,500+ … Read More
-
AI StrategyMCP Server: The AI Protocol Redefining How Brands Connect to Live Data
TL;DR — Key takeaways An MCP server is the standardized bridge that lets AI agents access live business systems — databases, CRMs, marketplaces — without rebuilding custom integrations for every new AI tool. Anthropic launched the open protocol in November … Read More
-
AI StrategyCAISI Pre-Release Testing: Why Brand Manufacturers Should Track Which Frontier Models Clear Washington
Voluntary federal pre-release testing of frontier AI is becoming a procurement filter. Manufacturers in regulated supply chains need to know which models clear it. Executive Summary The Center for AI Standards and Innovation (CAISI), successor to the AI Safety Institute, … Read More
-
AI StrategyAnthropic Mythos and Project Glasswing: A New Tier System for Cyber Defense
Executive summary Anthropic’s Mythos model surpasses all but elite humans at finding software vulnerabilities and has already flagged thousands of high-severity bugs across major OSes and browsers. Project Glasswing limits access to roughly 40 firms — AWS, Apple, Cisco, CrowdStrike, … Read More
-
AI StrategyAI Implementation Strategy: What Enterprise Brands Get Wrong and the Framework That Fixes It
TL;DR — Key takeaways Only 34% of enterprises are genuinely reimagining their business with AI — the rest are running disconnected pilots with no path to scale (McKinsey, 2025). Gartner warns that 40% of AI projects fail to scale, and … Read More
-
AI StrategyBest AI Apps for Fashion Brands: What Actually Works at Scale
TL;DR — Key takeaways McKinsey estimates generative AI could create $150–275B in value for the fashion industry — yet most brands still treat it as a design shortcut, not a business system. The biggest ROI in fashion AI is not … Read More
-
AI StrategyAI Ecommerce Website: The Architecture Most Brands Build Wrong
TL;DR — Key takeaways 65% of organizations now regularly use generative AI (McKinsey, 2024) — yet fewer than 1 in 3 report measurable value from ecommerce AI deployments. The gap lives in architecture, not tools. The AICE Stack™ (AI Infrastructure … Read More
-
AI StrategyEcommerce AI Design: The Conversion Layer Nobody Talks About
TL;DR — Key takeaways AI-driven ecommerce traffic converts 42% more often than non-AI sources — but only when the design layer supporting it is structurally sound, not just visually polished (Digital Commerce 360, March 2026). Most brands invest their AI … Read More
-
AI StrategyAgentic AI Certification: Which Programs Actually Prepare Enterprise Teams
Executive summary 88% of organizations use AI, but barely 1% have achieved true enterprise deployment maturity. Buying software licenses isn’t an AI strategy—your team needs systems thinking, not just basic prompt engineering. The shift to Agentic AI means autonomous multi-step … Read More
-
AI StrategyHow Luxury Brands Are Using AI — and Why Most Are Getting It Backwards
TL;DR — Key takeaways LVMH’s internal AI agent MaIA handles 1.5 million queries per month from 40,000 employees — proving AI at scale is operational, not creative. By mid-2026, AI agents account for 15–25% of luxury travel bookings. The buyer … Read More
-
AI StrategyEcommerce AI Automation: Why Your Catalog Is the Real Bottleneck
TL;DR Ecommerce AI automation is real, measurable, and increasingly standard practice — but 42% of companies abandoned their AI initiatives in 2024, and the leading cause was not bad tools. It was bad data. Before integrating another automation platform, your … Read More
