Anthropic Says Build Skills, Not Agents. We've Been Shipping Them for Months.

Two days ago, Anthropic dropped a bombshell at the AI Engineering Code Summit. Barry Zhang and Mahesh Murag, the architects behind Claude's agent system, told the world to stop building agents and start building skills instead.

Their message was clear: The future of AI isn't more agents—it's one universal agent powered by a library of domain-specific skills.

Here's the thing: We've been shipping exactly this at Fortune 500 scale since mid 2025. We just call them ADRs.

Watch the Talk That Changes Everything

The Skills Revolution According to Anthropic

In their 15-minute talk, Zhang and Murag lay out a simple but revolutionary idea:

"Agents today are brilliant, but they lack expertise... They can't really absorb your expertise super well, and they don't learn over time. That's why we created Agent Skills."

What are Skills? According to Anthropic:

• •Simple folders containing markdown files and scripts
• •Package procedural knowledge agents can load at runtime
• •Shareable via Git, Google Drive, or zip files
• •As simple as a single SKILL.md file with documentation

Sound familiar? It should.

The Enterprise Reality They're Describing

Look at what Anthropic is showing: Fortune 100 companies deploying org-wide skills. Enterprise FinTech serving thousands of engineers. This isn't theory—it's happening now.

They report that in just 5 weeks since launch:

• •Thousands of skills created
• •Non-developers building them (legal, accounting, recruiting)
• •Fortune 100 companies treating them as organizational playbooks

We Call Them ADRs. We've Been Shipping Them for Months.

While Anthropic was theorizing about skills, we were deploying them in production. Our Architecture Decision Records (ADRs) are exactly what they're describing—markdown files that package organizational knowledge to guide AI.

The Spring PetClinic Proof

We've been running this system at Fortune 500 scale for months. But to publicly demonstrate the concept, we ran an experiment on a well-known open source project:

spring-petclinic/
├── dto/
│   └── PetStatisticsDTO.java
├── service/
│   └── PetStatisticsService.java
├── controller/
│   └── PetStatisticsController.java
└── exception/
    └── StatisticsException.java

spring-petclinic/
└── stats/
    ├── PetStatistics.java
    ├── PetStatisticsController.java
    └── PetStatisticsControllerTests.java

Three markdown files completely transformed the AI's output. It went from generic Spring Boot to pure Spring PetClinic patterns.

See the full comparison on GitHub →

The Perfect Alignment

We're not building what they're describing. We've already built it.

Why This Matters for Enterprises

Zhang uses a brilliant analogy in the talk:

"Is it going to be Mahesh, the 300 IQ mathematical genius, or is it Barry, an experienced tax professional? I would pick Barry every time. I don't want Mahesh to figure out the 2025 tax code from first principles."

Your AI is Mahesh—brilliant but lacking domain expertise. Our ADRs turn it into Barry—the expert who knows your patterns, your compliance requirements, your architectural decisions.

The Validation We Didn't Know We Needed

When the company that makes Claude—the AI engine powering enterprise transformation—says the future is markdown-based skills that guide AI... and you've been shipping exactly that for months... that's not coincidence. That's validation.

From Theory to Production

While Anthropic talks about the potential of skills, we're delivering:

• •Complete PRs generated at $2.24 each
• •100-200x ROI at Fortune 500 scale
• •Air-gapped deployment with zero IP leakage
• •Automatic compliance checking on every PR

The difference? They're teaching people to create skills. We've built the platform that turns skills into production code.

What This Means for You

If you're an enterprise looking at AI transformation, the path is clear:

The future Anthropic is describing? It's available today. It's called OutcomeOps.

The revolution isn't coming. It's here.

While others are learning to build skills, we're shipping them in production. That's the difference between theory and transformation.