When to use AI Agent

Starting with the right mindset

Think of the AI Agent as a capable assistant for pattern-based, repetitive content work. It excels at tasks that would otherwise require you to manually process dozens or hundreds of content items. The key is recognizing when automation saves time and effort. If you’re facing unique creative work or a single content change, manual work is often faster. But when you’re doing similar work across multiple items following a consistent pattern, the AI Agent becomes extremely valuable.

Scenarios where AI Agent shines

The AI Agent handles the following types of content work particularly well:

• Content audits and discovery – Find content needing attention: items missing required elements, outdated metadata, or content stuck in draft or review workflow steps.
• Bulk operations – Update multiple items at once: change workflow steps, move content between collections, assign taxonomy terms across your content inventory.
• Multilingual workflows – Translate items into their respective language variants, maintain cross-language consistency, audit translation completeness.
• Content generation and optimization – Generate SEO and GEO metadata or article summaries. These tasks require clear instructions about what “good” looks like. You’ll learn how to provide that guidance later in this path.
• Content cleanup after migrations – Review migrated content for consistency, update outdated references, and standardize formatting across hundreds of items.
• Ensure brand standards – Reference existing content to maintain a unified brand voice without manually referencing style guides.

How AI Agent works within your project

The AI Agent respects your project’s existing structure. It works within the same boundaries as you. It can’t bypass role-based access or modify content you don’t have permission to change. If you can’t publish content manually, the AI Agent can’t publish for you either. Your workflow steps remain in control. When the AI Agent moves content through workflows, those changes follow your project’s approval requirements. Content modified by the AI Agent goes through the same review process as manually created content.

Deciding when to use AI Agent

Here’s how to evaluate whether the AI Agent fits your task. Let’s look at two example scenarios to see how this works in practice.

Example 1: Content discovery and bulk tagging

You have 50 blog posts about agentic CMS that were migrated without taxonomy terms. Why AI Agent fits: This is a repetitive task (assigning terms) across multiple items (50 posts) that follows a clear pattern (analyze content, assign relevant terms from your existing taxonomy). Time savings are significant: manually tagging 50 items means at least 150 clicks: opening each item, selecting the term, and returning to the inventory. The alternative? Asking your development team to write a migration script. With the AI Agent, you describe what you want in a single prompt.

Example 2: Unique content creation

You need to write a hero headline for your new product launch page that differentiates you from competitors. Why manual work fits: This is a single, unique item requiring strategic thinking. It needs brand voice nuance, competitive positioning, and creative judgment that varies based on market context.

Always review AI Agent’s work