Internal and external newsletters are valuable communication tools, but they take disproportionate effort to produce. Someone has to find relevant content, write summaries, arrange the layout, and maintain a consistent publishing cadence. Most newsletters die because the effort exceeds the perceived value.

The Problem

Newsletter production involves content sourcing (finding articles, updates, and announcements worth sharing), content writing (summaries, commentary, introductions), and assembly (formatting, linking, scheduling). Each edition takes 2-4 hours, and missing a single edition breaks reader expectations.

The AI Approach

An LLM can curate content from defined sources, write summaries in your newsletter’s voice, and assemble a complete draft edition. Combined with content monitoring, the system can produce a newsletter draft that needs only editorial review.

Three-Step Build

Step 1 - Source monitoring. Define content sources: RSS feeds, internal announcement channels, industry news sites, social media accounts. Aggregate new content daily.

Step 2 - Curation and drafting. Periodically feed the content pool to an LLM with your newsletter’s editorial guidelines, past editions for style reference, and audience description. The model selects the most relevant items, writes summaries, and drafts an introduction.

Step 3 - Assembly and review. Format the draft into your newsletter template. Present to the editor for review, reordering, and any additions. Publish on schedule.

Where It Breaks

Automated curation may miss niche but important items that only a domain expert would recognize as relevant. The model’s summaries can be bland without strong style guidance. Time-sensitive content may be stale by the scheduled publication date.

The Production Path

Start with a weekly cadence to allow time for editorial review. Track open rates and click-through rates by content item to improve curation relevance. Gradually reduce editorial intervention as the system learns what resonates with your audience.