How to Automate Newsletter Curation With AI Workflows

A great newsletter is 90% curation and 10% writing. The problem: curation takes hours. Scanning RSS feeds, reading articles, judging relevance, writing summaries, and assembling the edition — it's a full afternoon every week. According to Substack's 2024 creator economy report, top newsletter creators spend an average of 6-8 hours per edition on research and curation alone. Learning how to automate newsletter curation cuts that to minutes. CodeWords lets you build a workflow that sources content, scores relevance, generates summaries, and assembles a draft — ready for your editorial polish.

TL;DR

• Automated newsletter curation sources articles from multiple channels, scores them for relevance, generates summaries, and assembles a draft edition.
• CodeWords workflows combine SearchAPI.io, Firecrawl scraping, and LLM summarization to do in minutes what takes hours manually.
• The human curator adds voice and judgment; the AI handles sourcing and summarization.

Unlike generic AI automation posts, this guide shows real CodeWords workflows — not just theory.

Why Is Manual Newsletter Curation So Time-Consuming?

The bottleneck isn't writing — it's discovery and evaluation. A typical curator maintains 50+ RSS feeds, monitors Twitter lists, scans Hacker News, and checks industry Slack channels. Each source requires context-switching and mental evaluation: Is this article relevant? Is it high quality? Have we covered this angle before?

This cognitive load compounds weekly. By edition 20, curation fatigue sets in, and quality starts to vary.

Automation handles the mechanical parts — sourcing, deduplication, initial relevance scoring — so the curator's brain is reserved for the editorial decisions that actually require human taste. Think of it like a research assistant who prepares a briefing folder: the executive still makes the decisions, but they don't have to dig through the filing cabinet.

What Can Be Automated in Newsletter Curation?

Break the process into seven steps and identify which ones a machine can handle:

1. Source monitoring — Watch RSS feeds, social media, and search results. Fully automatable.
2. Article extraction — Pull full text from URLs. Fully automatable.
3. Relevance scoring — Rate each article's fit for your audience. Largely automatable with LLM.
4. Deduplication — Filter out articles covering the same story. Fully automatable.
5. Summarization — Write 2-3 sentence summaries. Largely automatable with LLM.
6. Edition assembly — Group articles by theme, order them, write transitions. Partially automatable.
7. Voice and polish — Add your personality, hot takes, editorial commentary. Human only.

CodeWords automates steps 1-6 and delivers a draft edition for step 7.

How Do You Build This in CodeWords?

Open CodeWords and tell Cody: "Every Wednesday at 8 AM, search for the top articles in AI automation from the past 7 days using Google News and Hacker News. Score each for relevance to our audience of technical founders. Summarize the top 10. Assemble them into a newsletter draft in Markdown and post it to our #newsletter-draft Slack channel."

Cody generates:

1. Source collector — Queries SearchAPI.io for Google News results and the Hacker News API for top stories in the target category. Also scrapes RSS feeds using Firecrawl.
2. Extractor — For each URL, pulls the full article text using Firecrawl. Strips ads and navigation.
3. Scorer — Sends article summaries to an LLM: "Score this article 1-10 for relevance to technical founders interested in AI automation. Consider: novelty, actionability, and quality of analysis."
4. Deduplicator — Groups articles by topic using LLM clustering. Keeps the highest-scored article per cluster.
5. Summarizer — For the top 10 articles, generates a 2-3 sentence summary with the key insight highlighted.
6. Assembler — Groups summaries by theme, adds section headers, and formats as Markdown. Posts to Slack.

The curator reviews the draft, adds commentary, and publishes. Total human time: 30 minutes instead of 6 hours.

How Do You Source Content Beyond News?

Great newsletters include content from unexpected places. Extend your sources:

• Twitter/X threads — Monitor specific accounts or hashtags via Composio. Extract threads and score them alongside articles.
• Reddit discussions — Track subreddits relevant to your niche. The scorer evaluates comment quality and discussion depth.
• Research papers — Query arXiv or Semantic Scholar APIs for new papers in your field. The LLM translates abstracts into plain-language summaries.
• Podcast episodes — Use transcription APIs to extract key quotes from recent episodes.

Store all sourced content in Airtable with columns for source, URL, score, summary, and inclusion status. This becomes your editorial database — searchable, sortable, and persistent across editions.

How Do You Maintain Consistent Quality?

Automated sourcing can drift if the scoring prompt isn't calibrated. Build a feedback loop:

After each edition, rate each included article on whether it resonated with readers (track via open rates, clicks, or replies). Log these ratings in Google Sheets. Monthly, feed the ratings back to the LLM: "Here are articles our readers liked vs. didn't like. Adjust your scoring criteria accordingly."

Over time, the scorer learns your audience's preferences — not through fine-tuning, but through prompt evolution. A Litmus 2024 State of Email report found that data-driven curation increases click-through rates by 34% compared to intuition-based selection.

Can You Automate Distribution Too?

Once the edition is final, automate the last mile:

1. Publish to your email platform (Mailchimp, ConvertKit, Beehiiv) via their APIs.
2. Post a teaser to Slack communities and social media.
3. Archive the edition in Google Drive and your Airtable archive.
4. Schedule a reshare for next week using CodeWords' scheduling patterns.

Tools like Zapier and Make can trigger email sends, but the full pipeline — sourcing, scoring, deduplication, summarization, assembly, and distribution — requires CodeWords' Python + LLM capabilities.

Frequently Asked Questions

Can I customize the scoring criteria per newsletter section? Yes. Create section-specific prompts. "For the 'Tools' section, score based on practical utility. For the 'Ideas' section, score based on novelty and provocation."

How do I avoid the newsletter sounding AI-generated? The AI handles sourcing and summarization. You add the editorial voice in step 7. The draft is raw material, not the final product.

What if the same article shows up every week? The deduplicator checks against a rolling 30-day history stored in Redis. Articles seen in recent editions are automatically excluded.

Can n8n or Pipedream handle newsletter curation? They can aggregate RSS feeds and trigger actions, but relevance scoring, LLM summarization, and intelligent deduplication require CodeWords' native AI capabilities.

Conclusion

Automating newsletter curation reclaims the hours spent sourcing and summarizing, so you can invest that time in the editorial voice that makes your newsletter worth reading. CodeWords handles the mechanical curation; you handle the taste.

Start automating your newsletter curation on CodeWords →