A real pipeline, start to finish
Last time I made the case that Zapier is just “when this happens, do that.” This week, the proof: the actual pipeline that feeds Signal, the news section of this newsletter. It is not clever. That is the point. It runs every day, it never forgets, and it turns a chaotic firehose of industry news into a single, reviewable list I can sit down with.
Here is the whole thing, step by step.
The problem it solves
Keeping across AI in health communications means watching dozens of sources — trade press, company announcements, regulators, preprint servers, a few sharp individuals. Done by hand, that is an hour of tab-juggling every morning, and the day you skip it is the day the story breaks. I wanted the watching to happen on its own, so my time goes on the judgement: what matters, and why.
The pipeline
Trigger — a new item appears in my reading feeds. I keep my sources organised in an RSS reader (Inoreader), grouped into a single folder of things worth monitoring. Zapier watches that folder. The moment a new article lands, the Zap fires. No app to open, no button to press.
Filter — is this actually relevant? Most of what comes through is noise. A Filter step checks each item against a set of conditions — does the headline or summary mention the themes I track? — and quietly stops anything that doesn’t qualify. Nothing downstream happens unless the item clears the bar. This one step is the difference between a useful queue and an unreadable one.
Format — make it consistent. A Formatter step tidies the raw feed data into the shape I want: a clean title, the source, the link, the date in a sensible format. Feeds are messy; this makes every entry land the same way.
Action — add it to the queue. Finally, Zapier writes a new row into a Google Sheet — the Signal Queue. Title, summary, source, URL, date, each in its column, ready for scoring. That sheet is the thing I actually open.
That’s four steps: watch, filter, tidy, file. One trigger, three actions, running unattended.
What I’m left with
By the time I sit down, the morning’s reading has already sorted itself into a single list of candidates — filtered, formatted, and waiting. My job starts where the automation stops: reading each one properly, deciding what earns a place, and writing the line that makes it worth your time. The machine does the gathering. I do the choosing.
That division is deliberate, and it is the whole philosophy of this series. Automation is brilliant at collecting and hopeless at judging. Let it collect.
The honest limitations
The filter is blunt. It works on keywords, not understanding, so it lets through things that match the words but miss the point, and it occasionally drops something it shouldn’t. I’d rather it err towards letting too much through — a few extra items to skim beats a missed story. Making that filter smarter, so it judges relevance more like I would, is exactly where the AI steps come in — and that is the next stage of this series.
For now, the lesson is the one that matters most: you do not need anything sophisticated to claw back real time. A trigger, a filter, a tidy-up and a destination will do it.
Next: 12. Zapier: when one step isn’t enough — filters, paths and tidy data, and how to build a Zap that handles the messy real world.
Zapier for health communications is a practical series. New post every week.
— Ned