IA polymath with SEO, Content Strategy, UX, Human AI. Former Pres @iainstitute #inmemoriam. Constructive irritant. Avowed heretic. Heresy here is my own.
Seattle
Joined April 2008
- Tweets17.2K
- Following888
- Followers2.5K
- Likes7.3K
Marianne Sweeny retweeted
RSI doesn’t require new DC infra; but it will require your data not sold to the buyers
And I believe that this is best accomplished by having human factors practioners -- information architects, content strategists, UX research and SEO, involved in the design, development, deployment and reinforcement learning of intelligent applications. daedalusia.com/thoughts/mani…
I believe we need to make a deliberate effort to keep humans in the loop in all critical processes across our economy and society, regardless of whether it is technically necessary.
Even if AI develops the *capability* for advanced autonomy, we should not make it highly autonomous. We have to maintain control and keep visibility and understanding of all critical processes, we should not blindly hand over everything to AI agents just because we can. AI as a tool in the human hand is the only form of AI that is worth pursuing.
Marianne Sweeny retweeted
Been working on my new approach to building presentations.
Inputs:
Readwise: highlights and notes
Slack: All my crazy ideas and videos internally
Linkedin: All my posts, comments + performance
Code:
Compare my new reads and thoughts to existing slides and notes
Find what I am thinking about, saying, highlighting that could challenge my existing slides or make them better.
Output is what you see in the video - I get to decide what makes sense to add and not, in a loop that trains the system why I think the way I think about what makes it into my decks.
I successfully petitioned to reactivate my account and added the gift cards. After one order, the account was mysteriously deactivated again. I created another account using the same credentials and... the gift card balance of over $100 was gone. 2/3
Service Design Fail
I've been with @DoorDash for more than a few years and spent more than a few dollars on their fees. A Dark UX pattern had me deactivate my account. Afterwards, as luck would have it, I received many gift cards. 1/3
Marianne Sweeny retweeted
I think you got to look at everything holistically, but couldn’t you say:
How can you ‘only do SEO’ and not consider content marketing?
How can you ‘only do email marketing’ and not lifecycle marketing?
All the naming semantics is about business goals and framing.
Marianne Sweeny retweeted
A LOT of people think they are qualified for this gig and applied.
You can't control anthropic, you can control what you do next, maybe they got this decision wrong.
Maybe they'll scan your twitter handle and see this post and others like it and not consider you for future roles because messages like this aren't constructive and show low humility.
Saying they want a yes man is quite the jab. Maybe they do want a leader and maybe they define leadership differently than you do. That is OK.
Latsly, people would ask me in the early days when companies didn't pick me for jobs if I thought was it b/c you are black? I was like, how TF would I know? I would never assume anything about a company, and I don't control them, I did say...if you don't hire me, I'm going to try to get hired by a competitor and make you wish you did, I can't control my skin color, I can control my network and what I research and what I put into tghe world.
Ultimately, 20+ years later I have no idea if people didn't hire me because I was black or not, but by focusing on what I could control, I built Seer. Worked out ok.
Keep ya head up, focus on what you can control and what you put into the world and life will hopefully give you whatever it is you want.
Indeed. And take that a step further in learning more deeply exactly how these applications were. In addition to RAG, LLMs use training data with RLHF for ground truth. The problem here is that often the human feedback comes from developers and not human factors practitioners.
"Grounding" Doesn't Mean What You Think It Means 🗺️
Words matter, especially when they're quietly reshaping how an entire industry thinks.
"Grounding" comes from "ground truth," rooted in statistics and originally cartography, where it literally meant going outside to verify that your map matched reality.
In some AI models, "ground truth" is the objectively correct real-world data, like sensor readings or medical records, used to anchor the model to reality. Not documents. Not web pages. Reality.
The core problem with LLMs is that there's no ground truth signal during training or generation. The model isn't checking its answer against the facts; it's only predicting the next most likely word.
What Microsoft, a company I deeply respect + admire, calls "grounding" is actually RAG (Retrieval-Augmented Generation): retrieving web documents to supplement a response. Useful! But web text is written by humans, about reality, not reality itself. Those documents can be wrong, biased, SEO-manipulated, or outdated.
RAG is better-informed guessing. True "grounding" is fundamentally a different thing.
The uncomfortable part: Microsoft's own AI Guide features a quote from me where, after significant pushback on their "grounding" framing during a long interview, I said: "RAG does help the LLM ground its response in information from the web, but it's worth remembering that not everything online is true." The caveat got published. The correction didn't & the term has escaped into GEO AIO E-I-E-I-O gauntlet.
I've since watched real people repeat versions of Microsoft's definition & treat it as fact. And I don't blame them. They're trying to keep up with all of these changes.
Microsoft's new "Grounding Queries" metric in Bing Webmaster Tools makes this even more confusing. Those aren't user queries. They're background searches AI quietly generates when a user submits a prompt.
For example, when you ask "should I bring an umbrella in Seattle?" the AI might internally generate "Seattle weather today" to inform its response.
Calling those "grounding queries" buries an already-misused term one layer deeper.
I raised this concern with Microsoft & suggested alternatives like "Retrieval Queries" or "AI Queries," which I feel would be more accurate and less confusing but to no avail.
The real irony? Microsoft employs SO many world-class AI researchers. They know the difference. By rebranding RAG and synthetic AI queries as "grounding," a precise technical term has now become a marketing buzzword.
SEOs are now optimizing for a word we don't have a shared definition of. And when AI researchers hear you use "grounding" this way, it'll erode your credibility.
As AI continues to reshape industries, it's more important than ever for us to understand these nuances. By learning the true meaning behind AI terms & tech we can communicate more effectively, make better decisions & drive real results.
19 Days until the next Actionable AI For Marketers Course 🎓
And there are humans, enterprise information architects, that are qualified to do so with both technical and behavioral expertise. Cross discipline education and cooperation is our path to more humane AI.
The bottleneck of current AI is simple: the techniques we use are still predicated on pattern memorization and retrieval, and thus they need *someone* to tell them which patterns to memorize (training data, RL envs...)
That role cannot yet be played by AI in a truly open-ended and autonomous way. We can't yet remove the humans in the loop. In that sense, current AI is still purely a reflection of human cognition (both in terms of which tasks/goals it pursues and the patterns it uses to solve them). It isn't yet its own thing.
Note to us all: Google is not our friend. Never has been. Never will be. It is a publicly traded company whose mission is to make money for stockholders through search dominance.
This Post is from an account that no longer exists. Learn more
Partial credit as they are also learning as they go
Why do LLMs suck so much?
It's not because they are as stupid as you think.
It's because they are balancing quality with... speed.
It's been bothering me for such a long time:
Google is so focused and has made so much progress on separating out quality content from low-quality content on the SERP, but its AI properties seem so far behind. Why don't they utilize those quality systems they already have more?!
And it's so simple, and I feel like such a putz for not seeing this clearer sooner...
It's because they are prioritizing speed. (h/t Matt G. Southern & @sejournal's coverage of Google's Jeff Dean's recent interview)
They will figure this out. Other LLMs will also figure out the balance between quality and speed as the tech evolves.
What's the upshot?
If you are trying to hack for LLM visibility, you are basically betting on LLMs NOT figuring out how to keep the speed while increasing quality.
I have never placed a bet in my life, but that seems like a stupid bet!
Marianne Sweeny retweeted
If you're a researcher in academia using Keras 3 (PhD student, postdoc, professor...) and you want to train on TPUs, you could receive compute awards from Google for your research. Google is running a new academic grant program, separate from the TPU research cloud.
You can contact me with a few words about your research and I can refer you -- [email protected]
First, John, Barry and others are not subject matter experts for Gemini and generative search. They offer stellar guidance on what SEO should focus on.
Second, it is NOT POSSIBLE to optimize for generative search, AIO or any other neural component of online information retrieva.
This one caught my eye.
Check out the transcript below to see Danny Sullivan from Google's perspective on "chunking content" - one of the most popular techniques currently believed to improve discoverability in AI search.
In the past year or so, I've seen many different interpretations and approaches for how to "chunk" content, and in many cases - yes, some of them can and do work well for AI search visibility. For now, at least.
But in this case, I'm reading between the lines a bit...
When you start to hear Googlers commenting on popular, widespread SEO/AEO tactics (and talking to their engineering teams about those tactics), my 'SEO spidey senses' start to go off.
We've seen this pattern so many times before, and it's why I spent last year giving multiple presentations about the 'cycle of SEO' (link in comments):
SEO/AEOs discover an effective tactic for driving traffic/visibility that is more focused on optimizing for machines, rather than humans ➡️
SEO/AEOs share this tip with the masses, lots of tools are built to automate and scale these tactics ➡️
Google identifies widespread use of this tactic and determines it's not great for their users ➡️
Google develops systems/policies to demote or penalize these tactics either algorithmically or through updated spam policies (this part can take a while to get right) ➡️
The tactic no longer works, and misusing/abusing it can lead to major setbacks in performance.
It will be interesting to see how this one pans out because we haven't had any clear examples yet of AI search-specific tactics being demoted in the way many SEO approaches have been over the years with algorithm updates, penalties, etc. But as AI search is evolving, it would make sense that Google would have to update its own systems accordingly.
Now, I'm not saying "don't chunk your content." As always, I would recommend only adjusting your content in ways that are *also helpful and valuable for your readers,* not just blindly following what a tool (or an LLM, lol) told you to do.
I've also heard a lot of noise about "writing for machines, not humans" in the past year. I would be very careful to follow that advice, as it is literally the exact opposite of the guidance Google provides in all of its documentation.
Like it or not, Google is still here, and your performance on Google has a massive impact on your overall performance in Search - yes, including AI Search.
Maybe add some information scientists, content strategists, user experience professionals, information architects and search optimization professionals? This entries that the human users protected by these standards have a voice as well.
This quoted post is unavailable.
Yes, it certainly can be of the client has ranking content for contextually similar topics. Next SEO ships it’s focused to user engagement on the site. What the site ranks for and where is an indication of the strength of content for that query.
