I use AI in creating my newsletter

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How I use AI in creating my newsletter – Peter Gasston

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For a few years now I’ve written a weekly newsletter, Tech Landscape , that rounds up new feature and product announcements in digital technology (90% AI these days), social media, and online culture, with some comment and insight where appropriate. It’s broadly aimed at people who work in or around digital marketing, or just want to stay up to date with what’s going on, and is pretty useful, I think.

But the increased pace of change in the last few years means I have a lot more to cover than I did when I started, and it takes up more of my time. So recently I’ve been looking at ways to use automation and AI to help me with some of that burden.

The Words

Producing the written content is a balancing act; I want to automate to save me time, but I don’t want to automate too much because then it loses any value. Here’s my current workflow:

Throughout the week, I save all the links in Airtable

At the end of the week I paste all of the links into a custom app I built, which uses Gemini to crawl and summarise them in an approximation of my voice.

Some links (especially social links) are blocked to crawlers, so I write those myself

When all the summaries are generated or written, I paste them back into Airtable

I export from Airtable (as a CSV file) and import it to another custom app I wrote which formats it for the newsletter

I post that into Substack, then do a few rounds of editing, writing, and rewriting

Those final rounds are critical; that’s where my voice shows up. I write all of the comments and asides myself, but also the automated summaries are rarely perfect and I almost always have to make tweaks or changes. That could be to make a sentence more human, to change American spellings, or to focus more on the things that I think are important.

For example, this is how Gemini summarised a recent story:

Adobe announced a definitive agreement to acquire Topaz Labs, an AI company specializing in advanced video and image enhancement models.

And this is what I edited it to:

Adobe is buying Topaz Labs, the company that specialises in video and image enhancement and upscaling.

Whereas this one I had to rewrite entirely; not because it’s wrong, but because I think it focuses on the wrong features:

Figma summarized new product updates from Config 2026, an update that introduces a built-in timeline animation feature, AI-generated shaders, and prompt-driven custom plugins.

Here’s my final, more detailed version with a more appropriate emphasis:

Figma announced several product updates at its Config 2026 event. The headline was code layers, which makes every layer on the canvas editable with code, unifying design and build in a single interface; it’s coming soon in closed beta. Figma Motion is a timeline editor for the canvas, enabling motion design of every element. Figma and Weave are becoming more tightly integrated. And the design agent is coming to all users, and now lets them code their own shaders and plugins.

I reckon my current semi-automated process saves me an hour or more each week, but maybe 75% is still hand-written. My next project is working out ways to make the process much simpler, while bringing that writing ratio down to about 50%, but still preserving my voice.

The Cover Image

I’m also trying to get a better grip of agentic workflows and MCP, so I paid for a Manus subscription and set myself a starter task: to create a cover illustration. These were the steps I settled on:

Check the Airbase table [via MCP] where I store each week’s stories, and get all of the written summaries for each story.

From those, synthesise an over-all cover concept, research [via the Web] current design and illustration trends, and turn that into an image prompt.

Send the prompt to Magnific [via MCP], choosing the image model best suited to the task

After testing and revising it a few times, I turned it into a repeatable Skill. And here’s the result, generated with Reve 4.1:

Clearly it isn’t great; it’s a bit overly-literal in some places, overly-metaphorical in others, needs more of a high concept. But I’m learning a lot about how to prompt multi-step workflows, which is useful, so I’ll revisit this in the future.

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