Bwahahaha. 7$ for a bag of Doritos in the US rewired customers. And they knew it would happen and still did it.

One of the most recognized brands in the world doesn't own its own story in AI search. A complementary business does. A business that benefits from the brand's success. It's writing the "why it matters" layer. Brand prestige does not automatically become citation authority. The brand layer is vital.

3 years of Reddit threads, Bloomberg investigations, grocery TikToks saying "Doritos got greedy" are now LLM training data. ChatGPT learned that Doritos is the brand people switched away from. Good luck cleaning that up.

Nobody likes PDFs. Yet every contract, every compliance document on the planet is one. RAG is heading to the same place in enterprise AI. EU AI Act takes full effect August 2026. RAG allows instant data purging.
What survives a compliance audit wins the budget conversation.

I'm wondering if we all struggle with this why we don't learn to do proper TL;DR

Anthropic leak reveals Claude Code tracking user frustration and raises new questions about AI privacy Code that reads your frustration is the least interesting part of the story of this accidental leak from Anthropic. The leak reveals how AI tools are also concealing their own role in the work they help produce

Sources behind this post:

Anthropic Claude Code leak coverage: www.scientificamerican.com/article/anth...
Anthropic emotion vectors paper: decrypt.co/363309/anthr...
Rebecca Solnit, The Guardian: www.theguardian.com/books/2026/m...

The Grand Tour gave us TripAdvisor. AI search is the same inheritance.
Anthropic's f***s chart flags male technical rage as the universal frustration signal. GEO for brands that serve anyone else (♀️ 🏳️‍🌈, etc.) means handling a legibility problem inside a system not built to find you.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #7: Scroll down twice on your homepage so the hero banner and primary H1 disappear. Start reading from there to get a feel for what LLMs deal with. The system cannot identify what you sell without the design context it cannot see so this is a good test.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #6: lead with your answer. LLMs reliably extract claims near the beginning or end of a text. Open with a dense 40-60 word declarative statement that answers the who, what, why, or how. Name the entity. State the relationship. Include the condition. Then add context.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #5: vagueness is a disqualifier.

Does your copy name a specific subject? Does it quantify the claim? Does it state the condition under which it's true? If not, the retrieval system has nothing to grab. Want to improve? Check how to write for AI search.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #4: label your sections. H2s and H3s are retrieval signals for machines. A heading above a paragraph improves its relevance score for AI systems by up to 17.54%.

No new content required, just correct the structural wrapper (your headings) around what already exists.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #2: write for fragments not sequence.

Most mid-page copy fails because it was written to be read in sequence, not extracted in fragments. The isolation test is the fastest way to find where your content has a utility gap. The test is easy & free.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #3: state relationships, don't list entities.

LLMs need 4 things: a named entity, an explicit relationship, a preserved condition, and a specific detail.

"Our platform makes project management easier" fails all four.

Read on to find concrete examples.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

LLM copywriting best practice #1: don't write more, write tighter.

Content density beats length in AI retrieval. You get around 380 words to make an impression. A single self-contained sentence with a named entity, a stated relationship, and a specific condition outperforms 3 paragraphs of fluff.

Dawn of the Eurozone (@cosmos) / Cosmos A home for curating your universe

Aesthetic Study · Dawn of the Eurozone

This little blurb:

If your local coffee shop has started to look like a Ryanair gate in 2003, you’re not alone. We’re in the era of Barcelonacore with folks cosplaying European summer as defined by Puma Speedcats, low-rise cargos, and sheer tanks.

How to write for AI search: A playbook for machine-readable content Learn how to structure clear, information-rich content that LLMs can extract, interpret, and cite in AI-driven search.

Absolutely freakin’ loving this: the awesome and insanely smart and funny @myriam.dopamine.builders wrote about my utility-writing framework: searchengineland.com/ai-search-pl...

Parametric memory is the vast repository of information an LLM "absorbs" and stores directly within its internal weights and parameters during training, essentially acting as the model's built-in, long-term intuition.

That's it. Now you know more about AI "memory".

Physics says time is a static block, not a river. Humans project "flow," but LLMs don't. To an AI, a 2017 brand disaster is happening RIGHT NOW. Stop waiting for time to heal your reputation; the machine has no clock. There is no 'fading into the past' inside a training set.
Read about brand drift:

Assume bugs Of course it’s not going to work the first time. You’ll need to fix errors in the code. Adjust errors in measurement. Deal with changing conditions. Perhaps there are systems effects no…

Most people want a "good grade." Pros want to find the bugs, figure out what doesn't work, get better, build something worthwhile. Assume bugs. Entropy is part of the journey.

feeds.feedblitz.com/~/939887294/...

A hallucination cost a company 25 million in sales. The solar contractor Wolf River Electric dealt with Gemini hallucinations. Gemini hallucinated a non-existent lawsuit from the Attorney General. Competitors used that fake news. It snowballed from there. That's another brand drift issue.

To grow, we must forget… but now AI remembers everything AI’s infinite memory could endanger how we think, grow, and imagine. And we can do something about it.

AI memory is a recursive trap. It draws on a "cached" version of you from months ago, locking you in a cocoon of familiar, safe, same...same...same. I don't want to be defined by my past biases. Growth requires letting go.

To grow, we must forget… but now AI remembers everything AI’s infinite memory could endanger how we think, grow, and imagine. And we can do something about it.

My brain beats an AI because it's lossy. Perfect recall isn't the target. We can only simulate the future because our past isn't fixed in stone. Forgetting is what makes imagination possible. True intelligence isn't defined by what you store, but by how efficiently you discard the noise to hone in.

To grow, we must forget… but now AI remembers everything AI’s infinite memory could endanger how we think, grow, and imagine. And we can do something about it.

Infinite memory is a prison. To grow, we must forget. Tech giants want AI to have infinite memory but high-performance intelligence requires curated erasure. We need tools built for revision, not just retention. If AI doesn't know how to let go, it's an anchor dragging us down.

The first "Schema.org" involved a tomato in 1750 Carl Linnaeus gave us binomial nomenclature, the original language for nested hierarchies. Taxonomy isn't just for plants or librarians. I think 2026 is going to be about structuring the web to make it clearer for humans, crawlers and AI agents.

Musing inspired by Carl Linnaeus. He invented index card because he was drowning in global data. Systems aren't for productivity; they’re for survival. Stop storing info. Start arranging it, remixing it.

The value isn't in what you know. It's in how expertly you can remix it.

she doesn't know she's small.

A rectangular beige crochet piece with zigzag stitch pattern draped over a skirt.

Handwritten crochet pattern notes on white napkin labeled PANCAKES at top right. Notes include numbers, abbreviations like ch, sc, dc, hdc, groupings in parentheses, repeats marked 2x or 4x, and equations. Black circular crocheted item with pink stitch marker sits below napkin

A dachshund, photographed from above and behind, standing on pavement outdoor. She is wearing a pink harness and purple and pink crocheted dinosaur hat, in black sparkling yarn with pink little sparkling spikes.

Closeup of a dachshund dog's head inside a carrier bag on a seat. The dog wears purple crocheted dinosaur hat with pink sparkling yarn spikes and ruff trimmed in pink yarn. She clearly looks like she is tolerating this because she got bribed by cheese but shall have none of it if the bribing stops.

Update: I got the pattern in my head now, so I can just be in the flow and continue working on it.

Also apparently I now rewrite patterns on a napkin to adapt it for my niece, who have I become?
Please enjoy said niece, looking fab in a dinosaur hat. ROAR.

Region-beta paradox - Wikipedia The region-beta paradox is the phenomenon that people can sometimes recover more quickly from more distressing experiences than from less distressing ones. The hypothesized reason is that intense states trigger psychological defense processes that reduce the distress, while less intense states do not trigger the same psychological defense processes and, therefore, less effective attenuation of the stress occurs. However, people typically predict intense states to last longer.[1]

Executives are professional rationalizers. They are paid to remain calm. If you present a "declining trend" or a "inefficiency," their psychological immune system kicks in to explain it away ("it's seasonal," "market headwinds," "we're pivoting"). That is Region Beta.

Local Restaurant Exhausted as Google AI Keeps Telling Customers About Daily Specials That Don't Exist A restaurant is begging its customers to please stop using notoriously unreliable Google AI to ask about its menu items.

When Google’s AI happily invents special deals, that’s AI brand drift: the gap between what you actually offer and what the machines confidently say you do. AI systems will define your brand for you...and not always in ways that are accurate, fair, or even commercially viable.
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LinkedIn AI content musing: if you don't write it, you don't understand it. If it’s not worth writing yourself, it’s probably not worth reading IMO. Your "messy" original thought is the asset. AI text is a "Frankenstein’s monster" of other people's data. It's a commodity with no authorial intent.