Joseph Parker

We run an automated pipeline that drafts articles for our product. During our first test attempts we let the model do almost everything, including the mechanical bits: fixing dashes and quotes, tracking which stage each article was in, creating SEO json, naming image files etc. It worked, but the quality was uneven, sometimes the model would miss some things, and, of course, it was rather expensive in terms of tokens.
Then we changed our approach and started treating AI like a creative employee and providing it with "software" (python scripts) to help with any mechanical tasks that could be automated by code. The model only does the part that actually needs intelligence and creativity now.
And honestly, the result surprised me - quality went up, because we now let it focus on what it's actually good at. As a pleasant bonus - the costs of running the pipeline dropped too. One of the first things we scripted was stripping the em-dashes the model loves to add but my co-founder has an allergy for

How do you improve the quality of your AI results, especially automated pipelines?

Hey builders

We just added Obsidian export to Browser Notes, and wanted to share what s new + the fastest way to use it.

July 2026 has been a turning point for search. Two major updates landed within weeks of each other, and they change how visibility works.

1. Google: AI visibility is now part of Search Console

In early July, Google launched generative AI performance reports inside Search Console. The data is now isolated: impressions from AI Overviews, AI Mode, and generative AI in Discover are separated from classic search. For the first time, you can see whether your content is actually being surfaced inside Google's AI answers not just rankings, not just clicks, but presence.

The message is clear: AI visibility is not a separate discipline. It's search visibility. Google put it inside the tool SEOs already use.