If you manage a large Sitecore implementation, you’ve probably experienced this at some point:

• Hundreds or even thousands of legacy pages
• Migrated content that all shows a recent create date
• Outdated messaging still indexed by Google
• SEO authority diluted by content that no longer reflects your brand

Your campaigns are optimized. Your dashboards look strong. But your content library might be quietly working against you.

In this article, I’ll walk through:

1. The real marketing problem behind stale content
2. My original idea of using a single Sitecore AI agent
3. Where the current product presents opportunities to evolve
4. Why I pivoted to a marketplace app plus AI approach
5. How this same pattern can solve other marketing challenges

The Real Problem: “New” Content That’s Actually Old

In our case, we migrated a large set of content within the last year. On the surface, everything looked fresh.

But in reality:

• All items had recent create dates
• Metadata did not reflect true content age
• “Last updated” timestamps were not reliable
• Search engines were indexing content that no longer aligned with our brand strategy

So the real question was not:

When was this created?

It was:

Does this content still represent who we are today?

That is not something a date field can answer. It requires interpretation. It requires context. And that is where AI becomes incredibly valuable.

The Original Plan: One Agent to Do It All

My initial idea was straightforward.

Build a single agent inside Sitecore AI that would:

1. Analyze all pages
2. Determine whether content is stale
3. Evaluate brand tone and alignment
4. Generate a marketer friendly archive report
    

In theory, this would allow marketers to run a single process, review recommendations, and confidently archive outdated content.

It was clean. It was simple. And it highlighted how powerful AI inside the CMS can be.

As I began implementing it, I also discovered areas where the platform has clear opportunities to mature.

Opportunity #1: Expanding Deterministic Content Retrieval

Sitecore AI agents are not completely isolated from the CMS.

They can leverage the Marketer MCP to fetch item details, which is a meaningful step forward. This allows an agent to retrieve structured content information rather than relying purely on pasted text.
 

That is powerful.

However, today this interaction is not as deterministic as running a full item query by path, template, or structured GraphQL query.

For example, while an agent can request item details, it does not yet operate like a developer driven query that says:

“Give me every item under /blog using Template X where Field Y contains Z.”

That level of precision still lives in traditional APIs.

From a maturity standpoint, this opens an exciting opportunity.

As Sitecore AI evolves, deeper integration between agents and structured query capabilities could allow:

• Path based targeting
• Template based analysis
• Bulk evaluation across defined sections of the tree
• Deterministic, repeatable governance scans

That would move agents from helpful assistants to fully orchestrated content evaluators operating with CMS level precision.

Today, the Marketer MCP gives agents visibility into items. Tomorrow, tighter query controls could give them surgical accuracy.

Opportunity #2: Expanding Retrieval Beyond MCP and Enabling External API Calls

While the Marketer MCP allows agents to fetch item details, it does not yet provide the same deterministic precision as structured CMS queries. That is why pairing agents with traditional Sitecore APIs or GraphQL remains valuable today.

In practice, this means:

• Use structured APIs for deterministic retrieval by path, template, or field
• Use the agent for qualitative analysis such as tone, relevance, and brand alignment

This hybrid model works well and gives marketers both precision and intelligence.

Another natural area for evolution is support for more generic external API calls directly from within agents.

Today, agents are primarily focused on analysis. If future iterations allow them to:

• Execute structured internal queries
• Call external APIs
• Interact with third party systems
• Trigger workflow actions programmatically

They would move closer to becoming fully autonomous marketing assistants.

Imagine an agent that could:

• Identify stale content
• Validate performance metrics from an analytics API
• Cross reference campaign data
• Automatically initiate an archive workflow

That level of orchestration would significantly expand the impact of AI inside Sitecore.

For now, pairing deterministic APIs with agent intelligence provides a practical and powerful architecture. But the path forward is clear. As deeper query capabilities and external API flexibility are introduced, agents can evolve from intelligent evaluators into true operational copilots for marketing teams.

The Pivot: Marketplace App Plus AI Agent

Instead of trying to force the agent to handle everything, I separated responsibilities.

The orchestration moved outside the agent.

The updated approach looks like this:

1. A marketplace app initiates the process
2. The app uses Sitecore APIs to retrieve content
3. Metadata and structure are evaluated programmatically
4. The content is sent into a Sitecore AI agent for qualitative analysis
5. The agent returns structured recommendations
6. The app generates a marketer ready report

This approach combines structured CMS access with AI powered interpretation.

The agent focuses on analysis.
The app handles retrieval, orchestration, and reporting.

It is a practical solution today, and it still leverages the strengths of Sitecore AI.

What Marketers Actually See

Instead of raw AI responses, the final output is clear and actionable:

This allows marketing teams to:

• Filter by “Archive Recommended”
• Focus on high confidence suggestions
• Trigger workflow updates
• Improve crawl efficiency and strengthen authority

The result is a scalable content governance process rather than a one time cleanup effort.

This Pattern Extends Beyond Archiving

Once you think this way, the use cases multiply:

• Brand voice audits
• Metadata generation
• Campaign consistency checks
• Regulatory compliance reviews
• Personalization alignment analysis

The broader takeaway is this:

Agents are powerful. Their impact increases when paired with thoughtful orchestration.

As Sitecore AI continues to mature and expand its integration capabilities, the line between analysis and automation will likely become thinner.

Looking Ahead

One area I am still evaluating is whether custom Sitecore AI agents can be invoked directly through an API.

We already have APIs for:

• Pages
• Items
• Personalization
• Structured content

If agent invocation becomes available programmatically, it would simplify this architecture significantly and unlock new automation scenarios.

If not, we can still replicate prompt logic externally or leverage other model APIs.

Either way, this is an evolving space, and the trajectory is promising.

Final Thoughts for Marketers

AI inside Sitecore is not just about generating copy.

It is about:

• Governance at scale
• Protecting brand integrity
• Strengthening SEO performance
• Making better decisions faster

Stale content is inevitable in growing organizations.

Allowing it to dilute your authority and brand is optional.

When you treat AI agents as strategic assistants and combine them with smart orchestration, you create a system that continuously improves your content ecosystem.

That is what digital maturity looks like.