News Roundup - July 2026
Frictionless Decisions brings you counterintuitive, original, jargon-free ideas for connecting data to decisions.
Spending too much time thinking about AI can fool you into pretending you’re a sophist, a paid teacher of philosophy. Don’t worry, I learned that lesson long ago.
But I do want to help find ways to avoid the negative effects of data technologies, in your company and in your soul. This month’s news roundup articles focus on AI’s personal impact, global tech trends, and data engineering. You might notice how I’ve developed some favorite writers in this month’s list. Oh, and have fun with the robots!
The articles below suggest a deeper, more thoughtful approach than most. Digesting all this takes a lot of time (which you probably don’t have), so I’ve started condensing and curating the best articles and posts for you.
Give them a read!
Amor Fati Entropy by Hollis Robbins, Anecdotal Value, July 6, 2026.
is a writer’s writer. This little piece on the redundancy of Internet-written content reminds me of Herman Melville writing about the ship’s ropes while chasing the White Whale. Just read it and enjoy.
I asked Robbins if she had some advice, simple guardrails, for preventing AI from infiltrating my writing? She says, “Focus on things only you know that it doesn’t know about! And push back hard (the thumbs-down button at the end of every chat is there for a reason).”
How to Plagiarize - by Jessica Talisman, Intentional Arrangement, July 6, 2026.
A weighty essay here. gives us the nuance we need to personally resist.
As a writer, plagiarism terrifies me. Not that I think anyone would want to steal any of my ideas, but that I might accidentally steal from someone else. A simple rule helps me: never write with AI. Never. Never paste any text from the internet (or any AI tool) into my writing. This doesn’t solve the problem but works as a starting guardrail. Another guardrail: always include attribution as an editing pass.
Plagiarism is a massive problem, and almost everyone who uses AI for writing is guilty, even if unknowingly. You can even plagiarize your own writing, like I just did in the previous paragraph.
The Robots Are Here by Jordan Schneider, China Talk, July 6, 2026.
Don’t discount robot dogs. and his guests draw a very helpful analogy to DJI creating the market for drones. Five years from now, you might wish you’d read this.
What Actually Happens When a New Chip Powers On for the First Time by Dr. Anu Asokan, LinkedIn, June 27, 2026.
When your confidence exceeds your knowledge, you become an armchair quarterback. That’s me when it comes to launching a new chip. In this fun, short LinkedIn post, the author gives everyone, even those not in the business, a window into the lived experience of design engineers.
Adopting AI Augmented Knowledge Work by Clayton Chancey, Foray Consulting, June 4, 2026.
I’ve recently started following Chancey. He’s really thoughtful about using AI as a tool, and he brings the credibility of an integrator. In this video presentation, he explains how AI is best used to accelerate processes you already understand. Makes a lot of sense to me; I hear the same message from most real experts and I’ve developed the same perspective in using AI for writing.
Chancey develops a solid thesis here: think about AIs impact on everyday workflows. This prepares you best for the transformation.
Forward Deployed Engineering Is About To Get Diluted by Ben Rogojan, Seattle Data Guy, July 6, 2026.
I love ’s data engineering updates; jargon-free, friendly, perceptive, and written with a ton of practical credibility. I think we’re all going to be FDEs five years from now.
How To Transfer Knowledge Every Time A New AI Buzzword Gets To Your Feed by Alejandro Aboy, CQL (Career Query Lessons), June 7, 2026
I’ve honed in on a couple bright, young writers for data engineering insights and to complement my own focus on connecting data to decisions. is one of the best.
“Using old terminology makes you sound outdated even when you’re describing identical work, so please don’t use terms from 2 weeks ago, which is the pace in which AI tech deprecates definitions,” he says. Love it.
I always felt that most data architecture questions boil down to “Where do we put the logic?” It’s a great way to cut through jargon. Non-technical nuggets like this can help you find your way around the ever-changing terminology world.
How Anthropic enables self-service data analytics with Claude by Chen Chang et al., Claude.com, June 3, 2026.
Check out my recent post reflecting this Anthropic article. I call it “Anthropic’s Common Sense Approach” to using AI in analytics.
I wouldn’t worry about Claude eliminating data analysts. Most of the article sounds like something I would write in Frictionless Decisions, in the sense that it emphasizes integration at the data foundation level. We can take this “data foundation” idea much further, even to building the foundation within business systems themselves. Maybe a future Frictionless Decisions article?
To remind you of this week’s data concept, enjoy Cruel Summer by Bananarama, from the Frictionless Data Spotify playlist.
For the full story about making data flow faster and better, check out Frictionless Data on Amazon.
