The Modern Publishing Pipeline: AI, AEM, and Edge Delivery

modern-publishing

Part 1: How to Automate and Accelerate Content from Draft to Live

The Content Bottleneck Problem

In almost every enterprise, content creation far outpaces content publishing. Marketing teams generate whitepapers, sales teams write proposals, and product managers draft feature briefs, yet only a fraction of this knowledge makes it onto customer-facing sites.

The reasons are familiar:

  • Manual copy-paste from Google Docs or Word into a CMS
  • Hours spent reformatting and cleaning up layouts
  • Bottlenecks when developers are needed for small publishing tasks
  • Long delays between content being approved and actually going live

I have seen this firsthand working with legacy CMS platforms. Publishing content in legacy systems has always been one of the biggest bottlenecks for marketing teams. Each CMS tends to ship with its own WYSIWYG editor or page builder template. These tools apply slightly different styling, they often reformat pasted content unpredictably, and they rarely allow you to preview the page as it will actually appear to a site visitor. This creates a frustrating gap between what the author intends in a Word or Google Doc and what the visitor ultimately sees.

And if you want to migrate content from one CMS to another, the pain is multiplied. Workflows get baked in, and moving them out can be slow and disruptive. The new modern publishing pipeline is designed to remove these friction points and let teams move content from ideation to publishing in a seamless flow that actually reflects the author’s original intention.

The Backbone: AEM and GitHub

At the center of this pipeline are two non-negotiable components:

  • Adobe Experience Manager (AEM) provides the enterprise CMS, block-based authoring model, preview and live environments, and integration with Adobe’s ecosystem.
  • GitHub Repository houses site scripts, CSS, and blocks for consistent rendering. It provides version control and collaboration between developer and content teams.

From my perspective, AEM and GitHub are irreplaceable in this setup. There are other platforms available, but for this type of publishing workflow, AEM provides the structure and GitHub provides the source of truth. Together they form the backbone that cannot be swapped. Everything else in the pipeline, from document storage to AI agents to CDNs, can be interchanged.

Modular Inputs: Storage and AI

While the backbone is fixed, the input stage is modular. Content can originate in:

  • Google Drive and Docs
  • Microsoft SharePoint and Office 365
  • AEM-native CMS authoring

Similarly, the AI agent layer is flexible:

  • Google Gemini, OpenAI ChatGPT, Anthropic Claude, or any LLM with agent modes and APIs can watch folders, interpret documents, and create blog-ready drafts.
  • AI can also enforce brand voice, SEO rules, or compliance checks before content ever reaches AEM.

I have tested AI tools in my own development work. They are helpful in limited ways, but only when scope, prompts, and context are clearly defined. Without clear definition, AI struggles to perceive how individual pieces fit into the larger whole. Used this way, AI can accelerate publishing. But it cannot be trusted to run a publishing workflow on its own. It needs to be constrained by guidelines, style rules, and a clear voice before it becomes valuable.

The Pipeline in Action (Example Flow)

Here is how a modern publishing cycle works in practice:

  1. Content Draft: A team member uploads a whitepaper to a shared folder such as Drive or SharePoint.
  2. AI Processing: A generative AI agent transforms the draft into a blog-ready article, complete with structure, headings, and optimized copy.
  3. AEM Ingestion: The AI output is placed into the AEM site folder, which automatically generates a preview page using GitHub blocks.
  4. Preview and Review: The marketing team reviews the post at a private .page URL, ensuring layout and compliance.
  5. Publish and Deliver: The post is published to .live, routed through Edge Delivery Services, and distributed via a CDN.

The result is a multi-day cycle reduced to hours.

The Delivery Layer: Edge and CDN

Publishing is only half the challenge. Delivery speed and resilience are equally critical.

Adobe Edge Delivery Services solves this by:

  • Delivering content at the edge, close to end-users
  • Enabling near-perfect Lighthouse scores by optimizing Core Web Vitals
  • Scaling globally without additional infrastructure overhead

On top of Edge Delivery, a CDN ensures resilience. Options include:

  • Cloudflare
  • Akamai
  • Fastly
  • AWS CloudFront

The CDN adds security, caching, and redundancy. Choice is flexible since the pipeline supports multiple enterprise-grade providers.

Benefits of the Modern Pipeline

Organizations adopting this model gain measurable benefits:

  • Speed: From draft to live in hours instead of days
  • Consistency: GitHub blocks ensure branding and UX are uniform across posts
  • Accessibility: Non-technical users can publish confidently without developer bottlenecks
  • SEO: Edge Delivery and CDN support near-instant load times, boosting rankings
  • Flexibility: AI, storage, and CDN are modular, ensuring no vendor lock-in

Example Alternatives at Each Stage

  • AI Agents: Gemini, ChatGPT, Claude
  • Storage: Google Drive, SharePoint, or AEM-native CMS
  • CDN: Cloudflare, Akamai, Fastly, AWS CloudFront

The only irreplaceables are AEM and GitHub. Everything else can be swapped depending on the enterprise environment.

Why This Matters

For marketing, operations, and IT leaders, the modern publishing pipeline is more than a technical upgrade. It is a strategic advantage.

Fresh insights reach audiences faster. Campaigns launch without developer bottlenecks. The pipeline is secure, performant, and future-proof.

In my own experience, I have seen how frustrating it is to spend days pushing content through a legacy CMS, only to have it appear slightly broken, misaligned, or delayed. This new pipeline removes that uncertainty. It ensures that what authors intend is what visitors see, and it does so with speed and reliability.

Conclusion

Legacy publishing models are too slow for the pace of modern business. By combining AEM and GitHub as the backbone with modular AI, storage, and CDN layers, enterprises can build a modern publishing pipeline that is fast, reliable, and adaptable.

The result is a system where content flows freely, from internal draft to global delivery, without friction. Publishing is no longer a bottleneck. It becomes a competitive edge.