Behind the Scenes: Technical Setup of AEM & Adobe Commerce

aem-technical

Part 3: How to configure, and integrate AEM, Adobe Commerce, and Edge Delivery

Why Go Technical?

In the first two posts, I looked at why modern publishing pipelines matter. The first post focused on how to accelerate publishing, and the second focused on unifying content and commerce. This final post explains the how: the technical setup, integration steps, and performance benchmarks that make the entire system work.

This is where my perspective as both a developer and a digital strategist comes in. I have seen the bottlenecks of legacy publishing workflows, and I have seen how composability and edge delivery resolve those pain points.

The Pipeline Architecture at a Glance

At the core of the architecture are two non-negotiable elements:

  • Adobe Experience Manager (AEM), which provides the CMS and publishing backbone
  • GitHub, which serves as the source of truth for scripts, styles, and reusable blocks

Surrounding this backbone are modular, swappable layers:

  • Authoring: Google Docs, Microsoft SharePoint, or AEM-native CMS
  • AI Agents: Gemini, ChatGPT, Claude, or any API-driven LLM
  • CDN: Cloudflare, Akamai, Fastly, or AWS CloudFront

The flow looks like this:

Author drafts → AI processes → AEM ingests → GitHub blocks render → Edge Delivery publishes → CDN distributes → Visitor consumes.

This is not theory. It is a practical pipeline that I have worked through in different contexts.

Setting Up AEM with GitHub

AEM uses a doc-based authoring model. Content created in Docs or SharePoint can be ingested into AEM and transformed into structured blocks.

Key technical elements include:

  • Blocks: The building blocks of content and commerce pages, such as columns, cards, and product recommendations
  • GitHub Repo: Stores scripts.js, commerce.js, initializers, and blocks. Version control ensures stability and safe collaboration between teams
  • Preview vs. Live: AEM provides .page for staging and .live for production, enabling safe review cycles before publishing

In my experience, block-based authoring is one of the most powerful features. It allows content teams to work in familiar tools like Docs or Word but still outputs structured, reusable site components. It bridges the gap between non-technical authors and developers, which is exactly where legacy CMS systems used to break down.

Adding AI to the Workflow

AI is not required, but it is a force multiplier.

A typical workflow looks like this:

  1. An AI agent watches a folder in Drive, SharePoint, or Dropbox.
  2. A new file triggers an API call to Gemini, ChatGPT, or Claude.
  3. The AI converts the draft into a blog-ready version.
  4. The output is placed in the AEM site folder for publishing.

From my own testing, AI is most effective in limited, well-defined scopes. If you provide a clear prompt, context, and rules, it can be extremely helpful. If you treat it as one-size-fits-all, it does not deliver. That is why I believe AI can never run a publishing workflow alone. It needs guardrails: style guides, tone, and structure. Used this way, AI reduces friction in the pipeline.

Commerce Integration Basics

For teams running Adobe Commerce, additional setup ensures product data flows seamlessly into content.

  • Version: Adobe Commerce 2.4.7 or higher with SaaS storefront services enabled
  • Services: Catalog Service, Live Search, and Product Recommendations must be configured
  • Drop-In Components: Pre-built modules for cart, checkout, account, and product discovery connect directly to AEM blocks

Without this integration, blog content often falls out of sync with the catalog. I have seen countless examples where a blog post linked to products that were out of stock, or the cart button simply disappeared when a user navigated from catalog to blog. With integration, this friction disappears. The blog and catalog stay aligned, and the customer experience stays consistent.

Edge Delivery and CDN Configuration

Publishing is only half the story. Delivery speed is what makes the experience shine.

  • AEM publishes to .live
  • Edge Delivery Services hosts content at the edge, close to end users, ensuring sub-second load times
  • CDN (Cloudflare, Akamai, Fastly, AWS CloudFront) adds caching, security, and redundancy

I like to describe composable commerce as “deconstructing the monolith.” Instead of forcing every visitor to interact with the full stack of a giant platform, we deliver only the components they need. Edge Delivery ensures those components arrive quickly, without performance bottlenecks. For me, that is the heart of why this matters.

Performance Expectations

What should you expect once the pipeline is live?

  • Core Web Vitals Benchmarks
    • Largest Contentful Paint (LCP): under 2.5 seconds
    • Cumulative Layout Shift (CLS): under 0.1
    • Interaction to Next Paint (INP): under 200 milliseconds
  • Lighthouse Scores
    • 95–100 across Performance, Accessibility, Best Practices, and SEO
    • Edge Delivery with lean blocks makes near-perfect scores achievable
  • Scalability
    • SaaS storefront services and global CDNs handle enterprise traffic automatically
    • No need for custom scaling infrastructure

I have seen firsthand how Edge Delivery can help achieve these near-perfect Lighthouse scores. The combination of modular blocks and CDN delivery removes most of the bloat that slows traditional platforms down.

Pipeline Best Practices

To keep the system resilient and future-proof:

  • CI/CD Integration
    • Connect the GitHub repo to CI/CD (GitHub Actions, Jenkins, or another tool) for automated deployments
  • Monitoring and Observability
    • Use Adobe Data Layer, New Relic, or Datadog to monitor performance and user behavior
  • Governance
    • Create publishing guardrails so non-technical users can safely preview and publish without risking errors
  • AI in the Loop
    • Let AI accelerate formatting and compliance, but always require human review for accuracy

Conclusion

The modern publishing pipeline is not just theory. It is a practical, achievable setup today.

With AEM and GitHub as the backbone, AI agents accelerating draft-to-ready content, Adobe Commerce services enriching content with live catalog data, and Edge Delivery and CDN ensuring speed and reliability, enterprises can move from draft to live faster, unify storytelling with selling, and maintain near-perfect performance scores at scale.

The payoff is clear: a content and commerce pipeline that is fast, flexible, and future-ready.