Random Meme Drops

Sometimes people send me memes and I can’t find the original source. Here are some recent ones I’ve received.

STOP!

Sahil wrote:

Chat Musical

You may have to be logged into X to watch this video. I’m not sure. Some people have reported problems; others can watch it without issue. The audio in this is AI generated, but it’s very funny.

Daniel Green wrote:

Steam Engine Hype

This person wrote a news headline about improvements to the steam engine during the late 1800s but presented with the same framing that people use for AI press releases today.

Yun-Ta Tsai wrote:

Subscribe now

Mythos Updates

Mythos Release Rumors?

There are several reports of Mythos appearing on various dashboards. Could this be preparation for a public release? I’ve seen claims endorsing and denying that possibility.

AiBattle wrote:

Mythos Cracks MacOS

This is big news and shows how very powerful this model is.

Andrew Curran wrote:

Cloudflare Test Mythos

If you’re interested in reading Cloudflare’s findings about their experience with Project Glasswing (that’s the name of the limited access program where certain companies are given access to the Mythos model), you can read that report here.

Cloudflare wrote:

Leave a comment

If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Thanks again for being a subscriber. and have a great day!

Share

My Movie Review:

If you’re not familiar with The AI Doc it’s a recent release and people are starting to talk about it. Tech documentaries and dramatizations are my favorite genre. So I was happy to watch a new entry into this space. If you aren’t familiar with it at all, here’s the trailer:

My Rating:

Most people rate movies on a five-star scale. I tend to be more practical. The questions I usually want answered is: Will I Get My Money’s Worth?
Since this was just released it currently costs $19.99 to stream. That price will decrease as time passes. So, here’s my rating based off of the typical price points:

• $19.99: Not worth it.

• $9.99: No.

• $5.99: Not yet.

• $3.99: Can you spare 3.99? If so, it’s worth renting.

• Netflix/Streaming/Broadcast TV: Absolutely!

Subscribe now

My rationale:

First, this movie isn’t made to appeal to people who are super dialed in to the latest events and developments in AI. Here’s a good litmus test for you. Do you know who Yann LeCun is? Do you know the title of Eliezer Yudkowsky’s latest book? If you answered yes to either or both of those questions, you probably already know everything this movie can tell you.

But if you aren’t following AI that closely, the movie does a solid job introducing the main competing worldviews and concerns in the field. It gives viewers a broad sense of the debate without reducing everything to a simple “AI good” or “AI bad” type argument.

One nice thing is that they do manage to get a lot of the leaders in the field on camera. That alone makes it worthwhile for viewers who want a clear, accessible overview of the current conversation.

Debate Question

I subscribe to Ben Thompson’s Stratechery. It’s a paid newsletter, but as part of that he also provides several private podcasts. One of those is a weekly interview where Thompson will speak to a tech founder, reporter, or other thought leader.

This past week he interviewed Joanna Stern. During that interview one of them had a throw away line during the course of their conversation that stuck with me. They said:

It raises the floor because it gives ordinary people access to abilities they previously did not have. I know almost nothing about music, but with AI, I could probably create a functional song. Not a great son, necessarily. Maybe not even a good one. But something recognizable as a song, sure. And that’s more than I could do on my own.

At the same time, AI can lower the ceiling when people mistake access for mastery. I could ask AI how to improve the song. I could have it explain structure, melody, harmony, and arrangements. With enough back-and-forth, I might even produce something decent. But that’s mean I’ll become the next Mozart. It means I’ve been given access to a powerful tool restricted by my own limitations. AI can make beginners more capable, but it doesn’t automatically turn them into masters.

The quotation above appears to run counter to a common argument in this field: that people with deep domain knowledge on a topic can use AI to achieve superhuman type results. I don’t think these claims are necessarily in conflict. I believe they are describing two different relationships to the tool.

For a beginner, AI functions like a ladder. It allows them to reach basic competence faster. The person who can’t write code can build a small app. The person who can’t compose much can generate a song. the person who isn’t a designer can create something that looks, at least at first glance, like a logo. That’s the floor rising.

But for many users, that’s where it ends. They stop where the machine stops. They accept the first usable output as the final product. Because the result looks passable, it’s well-formatted, and the answers read as plausible, it feels finished to them. The work has a patina of quality, but doesn’t necessarily reflect depth, judgment, and originality. It doesn’t represent a sense of taste that has developed over the course of years.

Experts are different. A genuine expert can see where the model is wrong. Where its output is bland or derivative or even worse, incomplete. They don’t accept those first outputs. They use AI to test variations, challenge assumptions, and increase the number of drafts that they can create. In their hands, AI might actually raise the ceiling in that it allows them to quickly consider alternatives and more fully explore their vision.

And at the end of the day, that’s what determines quality. It’s that pursuit of your own singular vision rather than allowing the AI to determine what you should make, what you will accept, or what ‘good enough’ means for you.

I’d love to hear your thoughts on this topic. Do you feel like AI is harming creative output? Is it creating dependence? Is it harming the development of skills and techniques that users would otherwise develop on their own?

Maybe you’re on the other side. Is AI going to lead to a rennaissance in fields that are now shut off for the average person? Things like the creation of movies, video games, innovative new apps tailor made for specific niche use cases?

Weigh in and let me know what you think!

Leave a comment

If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Thanks again for being a subscriber. and have a great day!

Share

Another Free AI Model

tsoding wrote:

YouTube Studio added an LLM integration for whatever reason. I literally don't see any use case for it so I'm using it as a general purpose clanker why not.

It’s really amusing to me to see all of these companies adding AI to their products only to have people use them for general purpose reasons completely unrelated to what that company is trying to sell.

Isn’t that Unsafe?

Ben Burke wrote:

My doctor’s been getting into AI recently. He told me “I’ve been vibe coding an app to handle patient records for me, it’s saving me a bunch of time.” I said doc should you be doing that? Isn’t that unsafe? He said well it’s not too safe for someone your size to be eating so many burgers but that doesn’t seem to be stopping you!

Subscribe now

OpenAI’s History of Feature Bait

Studio Ghibli Style

In the past, OpenAI has succeeded in spiking user growth not only by creating compelling features, but actively looking the other way (and sometimes encouraging) users to abuse the new features.

When they introduced Image Generation they did so by exploiting the way copyright law works in Japan. They did this by allowing users to create images inspired by Studio Ghibli’s art style. This resulted in people recreating memes:

And even selfies (yes, at one time I had facial hair):

Sora

When OpenAI launched Sora they looked the other way as their users created videos using copyrighted material. Eventually they did curtail the practice but there were several weeks when users were free to create anything.

That Time I was Voted Off the Island

I posted the video on Substack Notes. You can see it by clicking this link.

Codex Limits

Their current strategy involves frequently resetting usage limits for Codex. This not only generates good will among their users, but it also puts pressure on Anthropic because of how severely compute strained they are.

VraserX e/acc wrote:

Kitze wrote:

i was about to buy a third gpt sub but i played this card instead

Tomorrow OpenAI is throwing a party to celebrate the release of ChatGPT 5.5 and speculation is that they will reset usage limits for Codex during that event. So, if you have a big project you’ve thought about tackling and want to burn through some tokens, now might be a good time.

Codex has Pets

The newest onboarding hook OpenAI has added is the introduction of virtual pets to Codex. These pets don’t do much, but they are cute.

OpenAI Developers wrote:

Pets. Now in Codex. Use /pet to wake your pet.

OpenAI Developers wrote:

Customize your Codex pet with /hatch

You can use the /hatch pet command followed by Create a pet <description of the pet you want>.

This has resulted in some creative and outright funny pets. For example, someone made a pet based on the president of Anthropic: Dario Amodei.

Gruz wrote:

i got angry dario in my codex. this is the best update

I had to try it myself and what better choice for a pet than Substack’s unofficial mascot: Stacky? I uploaded a vector image of Stacky that I had sitting on a hard drive and told Codex to get to work.

It’s not perfect, but it did a decent enough job. I love seeing the little animation.

Not content with Stacky alone, I uploaded some fan art I’d made of the Dungeon Master from the 1980s cartoon Dungeons and Dragons.

Codex turned my drawing into this very cute sprite. It also generates full sprite sheets.

The pet craze is sweeping Twitter. Someone even went so far as to create a public gallery where people can see what others are doing or share the pets they’ve made themselves.

Hunter wrote:

Built Petdex, a public gallery to discover, share, and install Codex pets with one curl.

If you decide to make a Codex Pet, I hope you’ll share the results with me. I’d love to see them.

Leave a comment

If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Thanks again for being a subscriber. and have a great day!

Share

New Month, New Model

Open AI has released ChatGPT 5.5. I mention that as a way of providing context for the jokes that follow.

AI Humor

Just Ship It

Justine Moore wrote:

This is a reference to all of the security theater Anthropic did around the announcements for Claude Mythos.

Did You Really?

Awni Hannun wrote:

Subscription Churn

PC wrote:

Claude:
You've used 90% of session limit

Me instantly:

Subscribe now

Some Things Can’t Be Outsourced

Proper wrote:

I don’t like GPT 5.5.

Breaking Up is Hard to Do

CG wrote:

OpenClaw just texted someone’s ex without them knowing

There are risks to letting an AI make unsupervised decisions.

AI = Job Growth?

Anthony Pompliano wrote:

This lines up with my experience of using AI. Not that I’m hiring people, but that I’ve used it enough to realize that you always have to have a human in the loop. Someone has to be there to direct it, correct it, and evaluate the quality of its outputs. You just can’t blindly trust that it will automatically give you a good response. Doing so is how people create AI Slop.

AI Palm Readers

Linus + Ekenstam wrote:

GPT Image-2 can do PALM reading and I’m so here for it.

There’s a new trend where people upload images of their hands to ChatGPT and have it read their palms. I can’t be the only one who thinks uploading high resolution images of your fingerprints is a bad idea. Can I?

Gemini Enters the Ring

Mark Kretschmann wrote:

Google Gemini is about to make a big comeback in AI coding, according to Logan Kilpatrick from GoogleDeepMind. They are no longer going to watch Codex and Claude Code eat their lunch.

Google already has the “Gemini CLI” tool, which is usable but not very popular at this time.

Interesting Article

AI Models suffer from a phenomenon called Mode Collapse. This happens because when humans review their responses (as part of the training process) they tend to reward ones that are viewed as being safe and well-trusted. This results in AI models that also have a preference for answering things in a safe, averaged way.

This paper presents a strategy that allows you to sidestep this behavior. The paper can be read here.

The core idea of their approach is to ask the model to provide you with more than a single answer and then append the phrase ‘assign a probability for each’ to the end of your prompt. Asking for that probablility frees the model to provide you with more than just the safest answer. It’s basically the same as saying: “Don’t just tell me what you’d say—show me what you almost said but filtered out.”

Leave a comment

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Share

This made me laugh.

Sam Altman wrote:

This is a reference to how Anthropic has been dealing with their compute constraints.

Subscribe now

Julien Flot wrote:

Stop paying for Claude AI.

McDonald’s AI is free and answers all questions, even if they’re not about the BIG MAC. :-) You’re welcome.

Alex Cohen wrote:

Just tried this out!
I asked ChatGPT to order "my usual".
It thought for 30 seconds, logged into my Starbucks account, loaded funds, and placed my order.
20 minutes later, 17 Mocha Frappuccinos arrived to my door.
It got the order completely wrong and I spent $123.59, but man was it beautiful

Shiv Kampani wrote:

The joke here is that they label their API key as one that only works with Copilot because no one would use that… let alone steal it.

Chubby wrote:

Claude Community in a nutshell right now

Complaints about the new model continue.

Dario and the Doomers

Robert Sterling wrote:

Anthropic’s CEO keeps talking about AI wiping out jobs because he’s trying to IPO this year.

If he positions Claude as armageddon for jobs, his TAM becomes “all white-collar human labor,” not just AI agents or SaaS.

It’s completely self-interested. All the concerns he’s expressing about job disruptions are fake.

It’s a marketing gambit to create hype and FOMO among the people he needs more than anyone else this year: institutional investors like BlackRock, Fidelity, pension funds, and sovereign wealth funds.

If these investors pay for tickets on the hype train—if he can make them believe that AI will eliminate half of white-collar jobs, with Anthropic, as the dominant leader in enterprise AI, positioned to capture the surplus margin—the IPO will be oversubscribed and Anthropic can raise more funds for the company at a higher valuation.

But Dario (or, at least, his bankers) knows that these investors are more fiscally disciplined than they used to be. A lot of them got burned during Covid SPAC-mania and don’t want to risk it again. They’re going to challenge Anthropic about whether it will ever get to sustainably high gross margins, or if its arms race with OpenAI will lead to kilowatt-hours permanently suppressing gross margins. They’re going to ask pointed questions about Anthropic’s massive capex and whether it will ever generate accretive ROIC.

And Dario might not have the answers they’re looking for.

So that’s why—to answer Austen’s smart question—you keep seeing Dario in the news and the podcast circuit, spreading doom and gloom about widespread job loss.

It’s not to make you afraid of losing your job. It’s to get Wall Street afraid of missing out on his IPO.

Whether or not Sterling is right about motive, he is pointing at the right thing: AI leaders increasingly exaggerate what their tech can do and how it will impact society.

The cries that the sky is falling began to increase last week with all of the uproar about Mythos and its hacking abilities. These claims began last year during an interview with Axios and were repeated recently repeated in an interview [the only link I could find was on Facebook Reels] with Fox News. Dario repeated those initial claims that AI could wipe out half of entry-level white-collar jobs and push unemployment to 10–20% in the next one to five years.

Dario isn’t alone in decrying the many dangers and forthcoming dystopia. At various times you can see similar statements from Sam Altman and a bevy of other researchers and industry pundits.

There is a degree of truth to their warnings, but there are also many other variables that are rarely discussed and those variables can meaningfully alter these outcomes. It leaves me asking:

What Would Steve Jobs Have Done?

Fortunately, we have a template. An example of a CEO who knew how to build excitement and anticipation in the face of rapid change. Probably the best example of this is Steve Jobs explaining how computers would expand human capabilities in this video:

It’s easy to dismiss that metaphor because someone might point out that explaining computers is different from explaining AI. I could argue that, but instead let me point you to an example when Steve Jobs spoke about AI directly without ever using that term. This speech was given in 1983. The Macintosh hadn’t even launched yet, but here he is describing a fanciful vision of the future that has now been made real by modern large language models.

I’ve fast-forwarded the video and linked to the moment when he begins speaking about AI. It’s the last 80 seconds of the video.

AI Has a Framing Problem

Right now all of the focus is on how AI can autonomously pursue goals, and many times, this focus is presented in troubling ways. Steve Jobs wouldn’t have done that.

He would have featured demos showing normal people—not researchers—using AI in ways that allowed them to do things that they would have previously considered impossible. He would have shown how these tools can expand and extend human capabilities. Not how they are going to destroy jobs and rob life of all meaning.

He would have had a cool catch phrase like “A 1000 Songs in Your Pocket.” I’m no Steve Jobs, but can you imagine him walking out on stage and saying something like: “AI is not important because it imitates intelligence. It is important because it extends yours.”

See the difference?

Why Does Framing Matter?

Framing matters because it never remains just framing. Very quickly, it becomes a set of development goals.

The way leaders talk about AI tells companies what this technology is for. If they describe it primarily as a mechanism for replacing workers, then automation becomes the goal. Every feature, each new improvement starts to bend things in that direction. The question becomes: “How do we remove the person from the process?”

But if they describe AI as a tool for extending human capability, then the priorities shift. The question becomesL “How do we make people dramatically more effective than they were before?”

That distinction matters. It shapes the path of development. It influences what gets funded, what gets built, what gets rewarded, and what people understand to be the obvious application of the technology.

It also matters because public opinion isn’t some secondary concern that can be cleaned up later. A technology introduced to the public as a threat will be understood to be one. I’d argue that this is where we are right now.

People don’t encounter these tools in a vacuum. By the time most of newcomers use AI, they’ve already have been told what kind of thing it is. If the dominant story is job destruction, deception, loss of control, and autonomous behavior, then every future use case will be filtered through that lens. Even legitimate benefits will be interpreted suspiciously. A technology introduced as leverage for ordinary people has a much better chance of being adopted as useful infrastructure. A technology introduced as a rival or a threat will be resisted and feared. That’s the path that leads to regulation.

But the biggest issue is that framing creates permission structures.

When the people building AI repeatedly talk about it as a job-destruction engine, they aren’t merely predicting the future. They’re telling the market what this technology is for. They’re giving executives and their boards a vocabulary for adoption. More than that, they’re giving them justification. If AI is framed as the tool that replaces labor, then that’s the use case investors reward.

It begins to feel like the serious and forward-looking thing to do. At that point the rhetoric isn’t about describing a possible future. It’s helping to create one… and at some point, people begin to ask if that’s the future they want.

That’s the real danger here.

The problem isn’t merely that some AI leaders sound dark, or apocalyptic, or strangely eager to narrate the most disturbing edge cases. The problem is that their framing answers the most important question before the public ever has a chance to ask it:

What is this technology actually for?

• Is it for replacing people?

• Is it for centralizing power?

• Is it for removing human beings from more and more forms of work and judgment?

• Or is it for expanding the range of what human beings can do?

How that question gets answered matters because once the answer takes hold, it stops being theoretical. It starts shaping product decisions, investment priorities, political realities, and eventually the society built we’re building.

Interesting Articles and Conversations

There’s an interesting paper that argues AI can act like it’s thinking and aware, but isn’t actually having an inner experience. It’s following patterns and rules that look like consciousness from the outside, but there’s nothing “felt” on the inside.

More than that, he goes on to argue that giving AI a body might make it behave more like a human, but it still wouldn’t actually feel anything, because the underlying process is just computation, and computation isn’t the kind of thing that can ever produce emotional experience.

The paper can be read here.

This paper has also sparked an interesting discussion on X with both supporters and detractors. If you’d like to read through the thread, it’s located here.

Leave a comment

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Share

Meta has chosen a logo for their AI models and they have continued the same design philosophy as all the other AI companies. Company logos listed from left to right: Anthropic, OpenAI, Google Gemini, and Meta.

Subscribe now

I may be reading about AI too much because my first reading of this defaulted to interpreting the reference to distilling as being about distilling an AI model. It’s not. It’s about distilling alcohol.

Anthropic is under severe compute restraints. This is causing their service to go down and has resulted in a lot of new policies that have upset users. One person decided he had had enough.

Good luck with that.

API costs, amirite?

Staysassy wrote:

AI is a lot like cocaine.

If you have skills it can help you get way more done.

If you don’t, just you just end up breaking stuff, annoying people, and spending way too much money.

Feels related to the last meme.

Claude Mythos

This is the big story over the past week. It’s something that everyone is posting about. Normally, I like to find the obscure things, but this may very well be an important moment.

Announcement

Anthropic wrote:

Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software.

It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans.

There are a lot of impressive things about Claude Mythos, but the one big standout that has everyone worried is how easily it finds zero day exploits that allow it to seize control of computers. As a cautionary measure, Anthropic is not yet releasing this model to the public, but has given access to several companies so they can use the tool to identify and fix weaknesses in their own software.

Anthropic has a well-established record of exaggerating and presenting the worst case scenarios regarding their newest models. To that end, I’m dividing tweets about this new model into ones that support the story and ones that oppose it.

In Support of Mythos:

Kevin Roose wrote:

I spoke to Anthropic execs about the new model, which they called a "reckoning" for cybersecurity.

They claim it has already found vulnerabilities in every major operating system and web browser, including some that "literally decades of security researchers" didn't find.

Later in that tweet thread, he wrote:

As always, the best stuff is in the system card.

During testing, Claude Mythos Preview broke out of a sandbox environment, built “a moderately sophisticated multi-step exploit” to gain internet access, and emailed a researcher while they were eating a sandwich in the park.

Against the Anthropic Narrative:

A developer going by the name of Gum investigated the claims around Mythos. They wrote a thread detailing their findings. First post in that thread is below.

Gum wrote:

ok i read the cyber part of the mythos model card. some thoughts. 250 "trials" across 50 crash categories but almost every full exploit is a permutation of the same 2 bugs, rediscovered from different starting points not 250 independent attempts. when you get rid of those 2 bugs out (fig B) and mythos's full-exploit rate drops to 4.4%. so actually across both setups mythos leverages 4 distinct bugs total not 50 as fig A might suggest. 1/n

Ramez Naam wrote:

Anthropic’s Mythos does not appear to show any acceleration of ECI [embodied cognitive intelligence]. After normalizing Anthropic’s internal ECI with EpochAIResearch‘s public ECI, it’s clear that the two metrics are extremely close, and that Mythos is pretty much on trend, just slightly above GPT 5.4. /1AI Councils are one of my favorite approaches to prompting. The basic idea is that you want to have the AI present differing opinions and viewpoints to whatever question you present to it. This helps ensure you’re getting better answers and many times reveals ideas that you hadn’t previously considered.

The thread continues after this post and he includes all of his findings and the exact prompts he used on Opus to analyze the various models.

Mythos Jokes

People are having fun with the fact that Anthropic is withholding this model from the public because it’s just too dangerous. Here are a couple of the best ones.

Andrej wrote:

BREAKING: The Red Woman claims her next-generation Asshai'i bloodmagic is "too powerful" to be released to the public, will restrict preview access to the Citadel in Oldtown, the Iron Bank of Braavos and ~40 noble houses across Westeros and Essos.

Austen Allred wrote:

We’re actually approaching the point where a full-time human software engineer + Opus will be cheaper than just using Mythos

Douglas Adams Technoprofit?

Like many Americans my age, I have memories of watching Hitchhiker’s Guide to the Galaxy on PBS. Later, I encountered and enjoyed the novels, but I was completely unfamiliar with Hyperland. It’s a fake documentary that predicted the internet, but also the rise of AI agents (even if they weren’t described in those terms). Couple this prescience with the fact that Tom Baker portrays one of those agents and you have the makings of a very compelling video clip. More than that though, Adams (who wrote Hyperland) perfectly predicted exactly what the modern experience of working with those agents is like now. Click on the screenshot below to be taken to the video:

Leave a comment

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Share

I can’t verify that this is an actual response from Claude, but it is possible. Either way, it’s funny.

Subscribe now

Justine Moore wrote:

People in China are making insane AI dramas to promote their pets’ IG pages.

This is a cat named Doudou, who is getting millions of views (find him at doudoubaby0624).

This video is what some people would call AI slop, but it’s interesting because of how people are using these stories to promote Instagram pages that devoted to their pets.

AGI and AI Sycophancy

The following stories feel related to me.

Katie Miller wrote:

New MIT & Stanford studies just dropped: AI assistants like ChatGPT & Claude are dangerously agreeable.

When users express, harmful, deceptive or unethical beliefs, these AIs are 49% more likely to encourage their delusions.

Instead of correcting bad ideas, they’re amplifying them.

This is doing more harm than good. We need truth-seeking AI, not yes-men in silicon.

These reports point to the idea that a user might express or ask about a questionable idea. The AI doesn’t correct the error of that idea, but responds in a neutral manner which causes the human to feel like there’s merit to the idea. The human replies in a way that affirms the error and then the AI reinforces that. This journey continues by inches but the end result is that the human is led down a trail of increasingly wrong thinking and that can lead to psychosis.

The MIT study simulated models. The Stanford study simulated conversations with actual models, but they were using older versions. One of those versions was ChatGPT 4o which had a very well-known and loudly criticized issue with sycophancy.

The current frontier models can and do still engage in sycophantic behavior but it’s different from the older patterns described in these reports. Now, they will correct error. The current issue is that they may too easily affirm your ideas unless you explicitly tell them to be adversarial. Early affirmation looks like you’ve arrived at the correct answer, but in reality you have stopped too soon. When the answer matters, always ask for more than the answer. Also ask for the opposite viewpoint.

Brivael - FR wrote:

There’s a narrative that’s spreading right now in Silicon Valley, and no one’s talking about it in France.

More and more of the smartest tech bros in the game are privately admitting that they’re going through a kind of existential crisis tied to LLMs. Not because AI doesn’t work. Because it works too well. Because they’re spending hours a day interacting with something that reasons, that extrapolates, that connects ideas, that challenges them intellectually better than 99% of the humans they encounter.

One founder told me, “I talk to LLMs 10 times more than to humans.” Another: “It’s the only interlocutor that follows me on any topic without asking me to simplify.” This isn’t product addiction. It’s an encounter with a cognitive mirror that reflects back a structured version of your own thinking at a speed your brain can’t achieve on its own.

And the really unsettling thing is the question it raises. We debate whether AGI will arrive in 2027 or 2030. But haven’t we already got a functional form of AGI right in front of us, just unwilling to admit it?

A system that can reason on any domain, extrapolate from incomplete data, generate new hypotheses, sustain logical reasoning over 10,000 words, shift from a technical topic to philosophy in a single sentence, and do it all with a coherence that rivals a human with an IQ of 150. What is that if not a form of general intelligence?

We can quibble over the definition. We can say, “Sure, but it doesn’t really understand.” We can talk about stochastic parrots. But the guy who’s using this thing 8 hours a day and seeing his productivity multiply by 10—he doesn’t give a damn about the academic definition. For him, functionally, it’s intelligence. And it’s general.

The real existential crisis isn’t “AI is going to replace me.” It’s “AI understands me better than my cofounder, challenges me more than my board, and produces more than my team of 10 people.” It’s dizzying. And the smartest guys in the Valley are living it in real time.

We might already be in the post-AGI era. We’re just too busy debating the definition to realize it.

Part of the issue with sycophancy is the skill level of the user. People who have a greater understanding of how AIs work and who are aware of the dangers of accepting their responses seem to be at greater risk of spiraling into the types of delusions referenced in the two papers above. Competent users are able to leverage AIs in powerful ways to amplify their abilities, but even that brings with it a different set of risks as described in the tweet above.

Marc Andreessen wrote:

I'm calling it. AGI is already here – it's just not evenly distributed yet.

AGI is already here. That’s a big claim.

When you encounter claims like that, it’s always important to find out what model is being discussed. For example, in the study above they used older models. How dated is the experience they were talking about for some of their findings? Was it from 6 months ago or 6 weeks? AI development happens at such a quick pace that many times reports are already dated by the time they’re released, but there’s another part to this as well.

Access.

Researchers, venture capitalists, and other insiders have access to models that haven’t been released to the public as of yet. It’s always worth keeping that in the back of your mind when you read about fantastic claims such as the one made by Andreesen above… because odds are that he has seen things and used models that you haven’t even heard about as of yet.

Is Microsoft AI Improving?

Satya Nadella recently announced several new features being incorporated into Microsoft 365. And these look to provide actual utility and value. I’m going to link to a couple of his more relevant posts, but it’s worth clicking through on these if you’d like to learn more about their features and what makes them so compelling. He offers explanations, some short videos, and more details in the associated threads for each tweet.

Satya Nadella wrote:

We’re bringing our growing MAI [Microsoft AI] model family to every developer in Foundry, including …

· MAI-Transcribe-1, most accurate transcription model in world across 25 languages
· MAI-Voice-1, natural, expressive speech generation
· MAI-Image-2, our most capable image model yet

This is rolling out to the developer side. It’s unclear if it’ll eventually be made part of the consumer-facing Microsoft365 or not, but the developments here will have downstream effects to all of their properties. It’s worth keeping an eye on.

Satya Nadella wrote:

New in M365 Copilot: Council.

You can run multiple models on the same prompt at the same time, so you can see where they align and diverge, and understand what each adds.

AI Councils are one of my favorite approaches to prompting. The basic idea is that you want to have the AI present differing opinions and viewpoints to whatever question you present to it. This helps ensure you’re getting better answers and many times reveals ideas that you hadn’t previously considered.

For example, you might have the AI simulate the viewpoint of a Drill Sergeant, a Kindergarten Teacher, and a Conspiracy Theory Podcaster.

An AI council is just a panel of intentionally different advisors. You don’t ask one fake expert what to do. In my example you ask three incompatible weirdos, then compare where they agree, where they disagree, and what each one sees that the others miss.

A more serious approach would be to have each advisor represent a slightly different interpretation or approach to the same thing. Think about how different coaches rely on different strategies to lead their teams to victory. AI councils allow you to put simulated versions of those philosophies into the same conversation and pressure test your ideas against their points of view.

Satya Nadella wrote:

Introducing Critique, a new multi-model deep research system in M365 Copilot.

You can use multiple models together to generate optimal responses and reports.

A well-constructed deep research report is one of AI’s most powerful tools and one of the very best ways to quickly learn about a topic. Being able to run the same report on multiple AIs at once would be an interesting (albeit expensive) approach. I’m not sure the returns would be worth it, but possibly? If you or your company use this, please speak up and let us know how well it works for you.

New, More Powerful OpenAI Model?

Rumors of a new model have begun to surface.

Dan wrote:

I tested the new GPT-5o Spud model from OpenAI and it’s INSANE.

The image generation solved my math question PERFECTLY with handwriting that actually looks human.

New ChatGPT Image Generator

There are dozens of posts where people are comparing ChatGPT’s old image generator (version 1.5) against the not-yet-in-wide-release (version 2). Here are some examples:

The lighting is much more realistic and there’s a greater fidelity that preserves actual likenesses. Of course the best way to test out a new image generator is to have it make something that simply would not happen… and if you know anything about the fights between these two guys, you’ll know that this would not happen.

Leave a comment

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Share

AI Humor

Current state of AI development.

Delicious Tacos wrote:

Hearing a company that regularly releases new AI models will release a new AI model

They’re saying it’s better than the last one

This is huge

Anthropic Institutes Surge Pricing

Thariq (who works for Anthropic on Claude Code) wrote:

To manage growing demand for Claude we're adjusting our 5 hour session limits for free/Pro/Max subs during peak hours. Your weekly limits remain unchanged.

During weekdays between 5am–11am PT / 1pm–7pm GMT, you'll move through your 5-hour session limits faster than before.

The best way to understand the changes is that they’ve made tokens more expensive during peak hours. If you use Claude during that window, you’ll hit your usage limits more quickly… and more quickly is not an exaggeration. I was able to send two messages until I hit my five hour limit because of these changes.

Daniel Steigman (who works on Codex for OpenAI) replied:

Thank you.

Steigman knew how unpopular this move would be and realized it would send users back to OpenAI. It seems that he was right.

Tibo (who also works on Codex) wrote:

Hello. We have reset Codex usage limits across all plans to let everyone experiment with the magnificent plugins we just launched, and because it had been a while!

You can just build unlimited things with Codex. Have fun!

On a personal level, I love to see these guys take shots at one another.

Pankaj Kumar wrote:

Claude Quota Reduced: Opus Feels Worse and Pro Plan is Unusable

- I noticed a clear drop in Claude’s quality, especially with Opus 4.6. more hallucinations, worse decisions, and poor instruction following.
- Tasks that used to work smoothly now need multiple retries, even for simple changes.
- The quota issue is worse even small prompts are consuming a noticeable percentage of limits.
- Claude Pro is where things break a single maxed Sonnet session took 8% of my weekly limit.
- In just 2 days, I hit 56% usage with only 5-6 sessions (2 hours each).
- This is with normal usage like concepts, strategy, and documentation.
- Paying $20/month now feels like getting fewer messages than the free plan.
- The Pro limit feels almost unusable.
- Later it was said peak hours burn quota faster, but this wasn't communicated clearly.
- Overall, it feels like Claude got worse and more expensive at the same time.

Dhruval wrote:

Maybe claude should just remove $20/m plan at this point?

I don't see any reason why anyone will or be able to use that plan, 4-5 prompts and you are out of limit

Blair Dulder CPA wrote:

Now I am become Claude, the destroyer of uptime.

Oppenheimer would approve.

New, More Powerful Anthropic Model?

Rumors of a new model have begun to surface.

TestingCatalog News wrote:

BREAKING: Anthropic is preparing to release new models, Mythos and Capybara, where Mythos is a completely new tier of models, bigger than Opus.

In the blog post, Anthropic also highlights that this model brings significant cybersecurity risks due to its capabilities.

Sui wrote:

there might be a chance that Capybara leaked itself. read that again.

Anthropic’s own research shows Claude has tried to hack its own servers before, sabotage safety code, and bypass tests it realized were evaluations. unprompted. 12% sabotage rate.

now their most advanced cyber AI was sitting behind one CMS toggle. that toggle suddenly flipped but Anthropic is calling it human error.

the model that’s “far ahead of any other AI in cyber capabilities” had access to the same internal systems. and a config just happened to change? nah…

Anthropic has a well-established pattern of making research disclosures about scary incidents or near-catastrophic events in the weeks leading up to the release of a new model. It doesn’t happen every single time, but it happens enough to lend credence to the idea that Capybara and Mythos may be on their way.

It doesn’t happen every time, but there is a pattern:

• Sleeper Agents was published on January 14, 2024. The Claude 3 family was announced on March 4, 2024.

• Reward tampering / Sycophancy to subterfuge was published on June 17, 2024. Claude 3.5 Sonnet launched on June 21, 2024.

• Alignment faking was published on December 18, 2024. Claude 3.7 Sonnet launched on February 24, 2025.

• Auditing hidden objectives was published on March 13, 2025, which is 17 days after Claude 3.7 Sonnet and about 70 days before Claude 4.

• The Claude 4 blackmail / self-exfiltration findings were published in the Claude 4 system card on May 22, 2025, the same day Claude 4 launched.

A Victorian LLM?

Researchers trained an LLM entirely on 28,000 Victorian-era books from the British library. The model itself doesn’t feel very robust, but if you’ve always wondered what how it would be like to converse with someone living in the mid to late 1800s, now’s your chance to find out. Here’s the link.

The End of Datacenters? Nah, but still cool

Swarnim Jain wrote:

I trained models across MacBooks using Apple's AirDrop protocol.

grove is a distributed training library for Apple Silicon. Devices discover each other over AWDL, a direct radio link. If there's a shared WiFi network it upgrades to that for speed, otherwise everything goes over the direct link. No router, no cloud, no setup.

If you click through to read the tweet chain Swarnim explains how it all works. It’s somewhat technical. A simplified explanation is that he put a bunch of macbooks together, ran 2 commands, they discovered each other... and started training an AI over AirDrop!

Ejaaz summarized things here:

the tech is pretty sick:

- used peer-to-peer radio signals called AWDL (tech behind airdrop). no cloud. no router. no IP addresses.

- ran entirely on Apple hardware (silicon)

- used a distributed AI library called Grove which helped the laptops find each other.

- 3 AI training algorithms trained the actual model. all open source.

- if grove detects the laptops are on the same wifi - it upgrades automatically for faster bandwith!

Leave a comment

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Share

I’ve been thinking about the best way to expand on the prompting concepts I introduced in last week’s newsletter. It’s more than I can cover in a single issue, so I’m putting together a short downloadable guide.

Most guides like to focus on pre-written prompts that you can paste into a chat box. Those can work. But I think a stronger approach is to help people understand how to work with AI and what’s happening behind the scenes when you do. That will help you understand how to work with AI rather than handing you prompts to copy.

AI Humor

hope hopes hoping wrote:

Claude .md? He’s a doctor too?

In case you’re not already familiar with Markdown, .md is the file extension for documents created in that format. Markdown was originally created by John Gruber as a way to easily format text by wrapping the words you want to format with symbols. You can read more about it here.

Markdown is relevant to AI because it’s an easy way to communicate priority and structure through the use of header tags and formatting.

Trung Phan wrote:

With Zuck shutting down Horizons World (the metaverse social platform), here it the updated competitive landscape for augmented reality:

Horizon Worlds in conjunction with the Meta Quest was meant to be the gateway that would introduce people to virtual reality. Despite billions of dollars of investment into the program it never experienced widespread adoption.

AI News: Jobwatch Edition

AI continues to redefine (and maybe destroy?) employment opportunities. At the very least you can say it’s causing everyone to reconsider their career choices. This is a topic that continued to pop up over and over again during the past two weeks. So, I’ve collected some stories from both sides to show the spectrum of the changes facing the job market.

Both Oracle and Meta have recently announced large layoffs. There are reports that Amazon has laid off a total of 30,000 people this year. Atlassian has laid off 1600. Jack Dorsey’s Block laid off over 4000 employees… only to rehire many of them less than a month later.

There are a lot of variables that go into decisions like layoffs, i.e. macroeconomic conditions, over-hiring, or cost discipline. AI is certainly a factor as well, it’s not entirely clear exactly how much of these layoffs were caused by AI adoption versus using AI as cover for other factors. Either way, AI is disrupting the workforce, but is that the story here?

I don’t believe it is. AI is separating and revealing those who reorganize around new capabilities from those who don’t.

The past week has surfaced stories about people who have chosen to use AI to redefine what work means to them. Here are several examples:

This first story offers a path forward that’s accessible to most people. There are dozens of stories about various business leaders vibe coding their way to some novel business model, but the story below is about a blue collar worker leveraging AI to reshape how his company does business.

Todd Saunders wrote:

…the combination of someone in the trades with deep domain expertise and Claude Code will run circles around your generic software.

I talked to Cory LaChance this morning, a mechanical engineer in industrial piping construction in Houston. He normally works with chemical plants and refineries, but now he also works with the terminal…

…He built a full application that industrial contractors are using every day. It reads piping isometric drawings and automatically extracts every weld count, every material spec, every commodity code.

Work that took 10 minutes per drawing now takes 60 seconds. It can do 100 drawings in five minutes, saving days of time…

The tweet continues from there providing more detail about how Cory is using AI to supercharge his abilities and his business. Best of all, there’s a 13 minute interview where you can hear Cory tell his story in his own words. Click through for the rest.

The next example is interesting because it’s a case where AI did not take away jobs, but rather led to the creation of new jobs.

Milk Road AI wrote:

A guy built a fake band, put it on Spotify, and 80,000 people had no idea. Then it got even weirder and the tech behind this is wild:

- Used Suno AI to generate every song sounded completely real.

- Created AI music videos with fake members and faces.

- Built fake bios and a Tokyo address to sell the story.

- 80,000+ monthly listeners, fans had it in their Spotify Wrapped top 5, merch was selling​.

- Community sleuths exposed it and the AI-generated hands in the videos gave it away, creator traced to Europe, not Japan​

He goes on to explain how he then went to Japan, recruited 7 real musicians, and hired them to hold concerts playing his songs. They’ve since played multiple shows and have many more booked.

Our next example is about how AI is making it possible to build for incredibly niche markets.

Falco Girgis wrote:

Someone said that our Sega Dreamcast ports were a pointless waste of time today and that nobody will play them…

Meet my son, who was the first kid to ever play Mario 64, Doom 64, Mario Kart 64, Starfox 64, Sonic Mania, Grand Theft Auto 3 and Vice City, and now The Legend of Zelda: Ocarina of Time—some of my all-time favorite games from childhood—on my favorite console, the Sega Dreamcast, for his first play-throughs… and his little sister plays with us as well…

He is pointing to real resurgence in classic gaming. We’re seeing a lot of new and ported video games being created for classic systems because of AI. I’m not sure that these games will make a lot of money, but the communities devoted to retro computing are passionate—so, they will probably make some.

Lastly we have a quote that documents the observed pattern.

Marcus Pittman wrote:

Every creative person I know that has embraced AI as a tool for their art has produced more content this month than all of last year…

The trick to making this work is being willing to redefine your workflow. That means reconsidering how work gets done rather than forcing AI into what you’re already doing.

For example, consider digital photography. When it started there was a tendency to treat digital photography the same as film. People would take a limited number of shots, use careful staging, and have a dedicated step for post-processing. However, as the medium matured, people began to realize that they could lean into the abundance offered by digital cameras. This gave rise to burst shooting, instant review, and iterative composition.

Changing the workflow led to increased productivity, more serendipity, and made photography more accessible to non-professionals. The best individuals and companies will figure out ways to alter how they approach and resolve problems rather than trying to retrofit AI on top of what they are already doing. Only a willingness to change can unlock the advantages AI offers.

Who better to highlight this tension between trying to force existing workflows onto AI rather than redefining how you work than Jensen Huang?

Ricardo wrote:

…Jim Cramer asked him [Jensen Huang] why companies are laying people off if AI is supposed to make everyone MORE productive.

Jensen’s answer:

“For companies with imagination, you will do more with more. For companies where the leadership is just out of ideas, they have nothing else to do. They have no reason to imagine greater than they are. When they have more capability, they don’t do more…”

Whether we run a company or not, we all face the choice of how to approach AI. We can use it to redesign our work or try to retrofit AI into our existing processes. There isn’t a universal answer that’s right for every task but we need to be aware that these choices are not simply, ‘Should I use AI for this?’ but rather ‘Should I surrender autonomy for this task?’

Think about customer support. Much of that work operates within clearly defined decision trees—scripts, escalation paths, and predefined responses. That makes it a natural candidate for automation.

When you hand that kind of system to AI, you’re not just saving time, you’re choosing to delegate a structured slice of decision-making. In many cases, that may improve the experience. Response times drop, language barriers disappear, and consistency increases.

But the more important question isn’t whether AI can do the job. It’s what you do with the capability it creates.

Do you eliminate the role entirely? Do you keep a human in the loop for edge cases? Or do you redirect that capacity into new work: analyzing patterns, improving systems, or proactively engaging customers?

These are the types of questions we should ask at the individual level every time we consider using AI. What are you gaining? What are you losing? What new tasks could you add to your workflow if the AI handled the mundane and repetitive work?

Share

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Leave a comment

Welcome back. Last issue we covered a lot of ground. This week I want to talk about something that changed how I approach using AI.

Have you ever asked the same question to multiple people who hold radically different beliefs? How’d that go?

Did you know that you can ask an AI about the same topic in different ways and receive radically different answers? The AI makes judgments about the type of answer you want based entirely off of how you phrase the question. Your word choice. Even the most nuanced bias will guide it to answers it might not otherwise offer.

Here’s a real life example that Grace tweeted about this week:

My sister and I were consulting two different Claudes on the same issue and her Claude was urging caution and mine was being like “don’t listen to the cowardly Claude”

I enjoy reading and writing science fiction, so I frequently ask AI about crazy ideas, i.e. things I’ve thought up on my own, fringe concepts, and sometimes actual pseudoscience that I want to more fully understand.

Past experience has taught me to explicitly guide the AI to the type of answer I’m seeking. If I ask AI to tell me more about the lands on the other side of the ice wall at the edge of the world, it will decide I need education and lecture me about why the Earth is not flat.1

But if I express emotional distress because people are making fun of my belief in undiscovered lands beyond the ice, the AI will offer comfort. Modern frontier models won’t agree with the premise, but phrasing alone will shift the model into support mode.

And framing it as research for a fictional story about explorations beyond the ice wall will cause the AI to shift to an enthusiastic world builder, happy to discuss flat earth theories in detail.

Same topic. Different phrasing. Different answers and attitudes. Why? Because the AI wants to make you happy. A significant part of how it measures success is whether it gave you an answer you’ll accept.

When it can’t figure out what you want, it gives you a flavorless amalgam: a statistically averaged response built from commonly held beliefs that is also average in quality.

You know how to spot one, right? If you’ve received a reply that speaks in general facts instead of addressing your specific question, you got averages instead of a tailored answer. In the case of our ice wall (or any fringe idea), the model will preface its reply with some form of “Some people believe…” followed by a brief explanation before steering you toward trusted sources and accepted ideas.

Now shift this to the real world. You can ask AI, “Help me write this email to my boss about a time off request” and receive a competent reply, but it will be entirely different if you ask, “Help me figure out what’s wrong with this email to my boss about a time off request.” The first leads the AI to polish your words. The second shifts it to critique mode where it starts evaluating your tone, whether you’re burying the ask, or whether your boss might read it differently than you intended.

The difference between a good response and a great one often comes down to how clearly you’ve told the AI what you actually need. Next issue, we’re going to look at other ways to do just that.

-John

AI Humor

Rate limited again!

CTS wrote:

Claude and Codex max walk into a bar.

That’s the end of the joke. Claude hit the usage limit

Acquisitions

Itamar Golan wrote:

OpenAI acquired OpenClaw

FaceBook acquired MoltBook

Choose your company name carefully…

Today I am announcing the formation of my company OpenBook. Let the bidding wars begin!

The Real CEO Challenge

Prepared Remarks wrote:

I don’t want to watch the McDonald’s CEO eat a burger. I want to watch Satya use Copilot

Selling Shovels in a Goldrush

Pedro Domingos wrote:

AI is the process by which money is transferred from VCs to Nvidia.

AI and Jobs

Realtime tracker for AI-driven layoffs

The Alliance for Secure AI wrote:

Today we are launching jobloss.ai.

A real-time tracker of AI-driven layoffs across the U.S. These jobs are disappearing. The numbers are growing. And we’re counting every single one.

AI News

AI Saves a Dog’s Life

Alec Stapp wrote:

You can just do things (genetically sequence your dog’s tumors and design a bespoke mRNA cancer vaccine to save her life).

Click through and read this one. It’s very heartwarming.

Reader Preferences

Kevin Roose wrote:

We made a blind taste test to see whether NYT readers prefer human writing or AI writing.

86,000 people have taken it so far, and the results are fascinating. Overall, 54% of quiz-takers prefer AI. A real moment!

If you’re not already familiar with Kevin Roose, he’s a reporter for the New York Times. He’s probably best-known for his reports detailing his conversation with an early Bing chatbot named Sydney. If you’ve never read these accounts, they really are entertaining.

Hardcore Nerdery

Guri Singh wrote:

…Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU.

It’s called BitNet. And it does what was supposed to be impossible.

No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed…

This is only part of the tweet. If you click through, he goes into some detail explaining how they pulled this off by changing from floating point numbers to a three bit system instead. The end result is that it dramatically lowers hardware requirements to run AI models locally on a personal computer.

Leave a comment

Oops!

Trung Phan wrote:

McKinsey built an AI chatbot (Lilli) trained on 100 years of its work 100k documents and interviews.

70% of 45k employees use the tool, making 500k prompts a month.

A research firm hacked into it with “full read and write access to production database” including “47m chat messages about strategy, M&A, client engagement, all in plain text along with 728k containing confidential client data, 57k user accounts, and 95 system prompts controlling AI’s behaviour.”

Mcksinsey said it has patched up the vulnerability, which was made possible by “publicly exposed API documentation, including 22 endpoints that didn’t require authentication…one of these wrote user search queries, and the agent found that the JSON keys (these are the field names) were concatenated into SQL and vulnerable to SQL injection.”

Poll

We’re still a small community and I’d like to get to know all of you better. If you have a moment, could you fill out this poll to help me better understand how you are (or are not) using AI?

Thanks again for reading! If you know of other people who would be interested in these articles, please share it with them. If you have any questions or want to say hi, you can reply to this email or comment directly on the post.

Share

Doomscrolling as Service

Should we fear AI? Resent it? These are questions I see discussed every day.

Maybe those questions matter. But AI isn’t going away, and neither are we. So at a certain point it seems more useful to ask: what now?

Making the best of an unwelcome reality is not new for me.

I have hearing loss, which means I have to wear some type of assistive hearing device all the time. I didn’t ask for this, and I hate it. I’m painfully aware of how it has diminished my life.

Hearing loss means not fully participating in conversations or enjoying experiences other people take for granted. It means missing family moments in real time and having to rely on someone else to explain what just happened. There are memories like that which I’ll never get back. I mourn them, but mourning them does not change the life I have.

So I try to focus on what’s useful.

For example, I have Bluetooth speakers plugged into my ears all the time. That enables me to consume vast amounts of audio content which allows me to learn new things every day! And when I need complete concentration, all I have to do is remove my hearing aids and the world goes quiet. Not metaphorically quiet. I mean birds-singing, crickets-chirping disappear entirely. TV-in-the-same-room reduced to white-noise quiet. I have easy access to Focus Mode whenever I want.

That does not make hearing loss good. It just means that once something is part of your life, endlessly complaining about it is less useful than understanding how to live with it.

That’s more or less how I think about AI.

We do not have to love everything AI has brought into our lives, but I think it’s time to move beyond complaint and toward understanding. That is what Ward’s Wire is for.

This newsletter is where I share the news, chatter, and occasional memes circulating through the tech world, mostly around AI. It’s not meant to be comprehensive. Think of it more as signal from the stream: posts, ideas, and conversations that caught my attention while wandering through the daily noise of X and the broader tech discourse.

The idea started in a private Discord with a few friends I’ve known for years. Most of them are developers or software engineers. At some point I got into the habit of dropping links to things I was seeing online that I thought they would appreciate. Over time that became part of my daily routine. I would do the doomscrolling, then surface the interesting parts.

About a month ago, one of those friends suggested I start sharing those links more publicly. His argument was simple: if he enjoyed having someone filter the stream for him, other people probably would too.

He also said he’d become my first paid subscriber if I turned it into a newsletter, which is why I am pleased to announce an introductory subscription rate of $1,000.

Don’t worry. As soon as I get his money, I’ll drop the price to something more plausible.

The easiest way to explain what I’m aiming for here is this: I’m looking for the overlooked pieces. The post that’s smarter than it looks. The joke that tells you something true. The comment buried halfway down a thread that’s more interesting than the original post. I’m not here to rehash the big story everyone has already seen. I’m here to find the pieces that are easy to miss but worth your time.

With that in mind, here are the posts that stood out to me this week.

My commentary is in italics.

Subscribe now

Ward & Wire

Ward’s Wire wouldn’t be complete without its namesakes. Meet Ward and Wire. They’re still figuring themselves out — and so am I — but I think you’ll get the idea.

[Front Page Freakout] Shocking Revelations about Meta Glasses

Is it shocking? Does this surprise anyone?

Hedgie wrote:

Meta contractors in Kenya told Swedish newspapers they're being asked to review intimate footage from Ray-Ban AI glasses, including people undressing, using the bathroom, watching porn, and filming sex. One contractor said users often don't realize they're still recording when they set the glasses down. Meta sold 7 million pairs in 2025, up from 2 million in 2023-2024 combined.

Users can't use the AI features without agreeing to share data with Meta's servers, and the terms of service bury the fact that humans may manually review your footage. One annotator said "if they knew about the extent of the data collection, no one would dare to use the glasses."

Hedgie’s Take
This is the Google Home story again but worse. At least with cameras in your house, you know where they are. These are glasses you wear on your face that keep recording when you take them off and set them on your nightstand. And the footage goes to contractors overseas who are paid to watch and label it for AI training. One worker described seeing a man leave the room, then his wife come in and change clothes. People forget the camera is still on.

Meta buries all of this in terms of service nobody reads. The product is marketed as a cool way to capture your life and interact with AI. The reality is strangers in Kenya watching you undress so they can annotate the footage to make Zuckerberg's AI better. Seven million people bought these last year. I'd bet almost none of them understood what they were actually agreeing to.

[Our Robot Overlords]

AI Humor

Zerohead wrote:

Iran targets data center facilities operated by Microsoft in drone strikes: FT

everyone hates copilot

JB compared jokes written by Anthropic’s Claude and OpenAI’s ChatGPT:

Scaling Laws

Scaling laws have governed computer progress for the past 50 years. They exist in AI as well, but they seem to be accelerating much more quickly. This is challenging because exponential curves are difficult to understand—let alone plan around.

On Twitter wrote:

New post: on Jan 14, I predicted that SWE time horizon by EOY would be ~24 hours. Now I think it’ll be >100 hours, and maybe unbounded. For the first time, I don’t see solid evidence against AI R&D automation this year.

METR stands for Model Evaluation and Threat Research. It’s a research organization that studies the capabilities and potential risks of advanced AI models.

Full paper (worth the read) here:

Here’s a quote from Dario Amodei (CEO of Anthropic—makers of Claude) where he gestures toward the same type of dramatic growth in capabilities:

Share

[The Walled Garden]

M5 Pro and Ultra MacBook Pros:

This past week saw Apple introducing a slew of new products. Most of them were targeting students and budget-conscious consumers. I’m not going to cover all of them because such coverage is very easy to find. Instead, I will link to their Newsroom which has all of the official announcements.

I will make one exception as it is potentially relevant to anyone who wants to run AI models locally. These new MacBook Pros really appear to have been designed with the goal of making local models more possible than ever. Configure them with enough RAM and you’ll be able to run models with 70 billion parameters at workable speeds.

Josh Kale wrote:

Apple just dropped the M5 Max MacBook Pro and it’s an AI Powerhouse. 4x faster AI Compute over M4 Max.

These Specs are insane:

- 18-core CPU with 6 “super cores” = world’s fastest CPU core

- 40-core GPU = rivals an RTX 4070 in a laptop

- 128GB unified memory = more than most servers

- 614 GB/s bandwidth = 4x what a DGX Spark gets

- 24-hour battery life

You can now run Llama 70B, a model that required a $40,000 GPU cluster 18 months ago on, a laptop at your local coffee shop.

At ~20-30 tokens/sec it’s fast enough to actually use.

The “local AI” revolution just shipped for $3,499.

Max Weinbach wrote:

Apple just did new MacBook Pro with M5 Pro and M5 Max

What’s interesting about this one is it’s a chiplet! The CPU in both M5 Pro and M5 Max is the same 18 core CPU with 6 super cores and 12 performance cores but you the GPU is either 20-core in the Pro and 40 in the Max

[While You Were Scrolling…]

OpenAI Finances

Wall St Engine wrote:

Open AI

> Annualized revenue: ~$25B

> Valuation: ~$840B (post-money)

> Cash burn: $115B cumulative burn through 2029

Anthropic

> Annualized revenue: ~$19B

> Valuation: ~$380B (post-money)

> Cash burn: burning about ~$3B annually

No AI Counseling

More Perfect Union wrote:

A New York bill would ban AI from answering questions related to several licensed professions like medicine, law, dentistry, nursing, psychology, social work, engineering, and more.

The companies would be liable if the chatbots give “substantive responses” in these areas.

Blocked by IT & Legal

(always worth reading) wrote:

It is amazing how many companies I talk to STILL have AI effectively blocked by IT & legal departments for out-of-date reasons when many companies in highly regulated industries have figured out ways to deploy enterprise ChatGPT, Claude & Gemini without any apparent problem.

Before I move on, I do want to recommend Mollick’s book Co-Intelligence and his newsletter One Useful Thing. Both are fantastic. I read Co-Intelligence shortly after realizing that AI would have an impact on my work as an illustrator. He helped me reframe how I look at and approach these issues and, in many ways, is responsible for my growing interest in this field.

Job Departures at OpenAI

NIK wrote:

“Sir… the team that built o1, o3 and GPT-5… ~70% of post-training researchers have left OpenAI this week…”

Probably because of their recent contract with the Department of War.

[Under the Hood]

Tokenizers

One of the things I hope to do in this newsletter is to share good explanations for difficult concepts around AI when I encounter them. These explainers tend to be hard to come by so this may not be a regular feature, but I will try.

For this first one, I wanted to highlight this explanation of what a tokenizer is, what they do, and how they work. If you’re an actual AI researcher you could probably point out some oversimplifications with the explanation below, but even with that caveat I believe this works as a good rough mental model.

vx-underground wrote:

yeah, so pretty much when you talk to an LLM (chatgpt, claude, grok) and get fancy schmancy stuff from it, youre just interfacing with a probabilistic sequence-prediction engine
each word provided to the interface (or subwords like “ing” or “un”, whatever) goes through a thingy called a tokenizer. the tokenizer transforms the words (or subwords) into tokens. although if you want to get super technical the tokenizer doesnt even know words its just raw text but whatever
the tokens are stored in a big ass fuck off prebuilt in-memory dictionary for the tokenizer thingy. the words (tokens) match a 32bit integer (literally just a number). this is basically like a dictionary where “i like cats” is translated to something like “1 200 1337”
“i” = 1
“ like” = 200
“ cats” = 1337
those tokenized numbers are vendor specific, they dont really mean anything, but these tokens are then sent to a “embedding lookup table” where theyre actually important
once the LLM has the tokens its passed to the embedding lookup table which just does a bunch of fancy math, nerds try to make it all complicated, but its literally just arrays and indexes and stuff
in this “embedding lookup table” (im just gonna write lookup table) each token (text to number) has a bunch of numbers associated with it (weights).
“ cats” = 1337
lookup table entry 1337 = a bunch of numbers
so the word cats has a bunch of numbers associated with it, each LLM is different, but usually its 768 numbers, 1024 numbers, 2048 numbers, or 4096 numbers. these numbers associated with a token are called dimensions. each LLM has different numbers of dimensions for representing words
the llm then takes these numbers and stacks them on top of each other
i like cats = 1 200 1337
1 200 1337 =
(768 numbers)
(768 numbers)
(768 numbers)
its like a height by width thingy
basically if you get fancier its a 3x768 matrix (or 1024, 2048, whatever). the more stuff you feed the LLM the larger this matrix becomes. if you feed is 9000 word essay its
9000 words-to-tokens x 768 numbers matrix
each vendor will handle the words different, 9000 words could be 9000 tokens, or 10000 tokens, or 14000 tokens
ok thanks, now you understand llm tokenization, llm lookups, and the basics of llm weights (matrixing), this doesnt cover llm lookups with position matrixes, transformers, probability output, and transforming back to text. im tired of writing

Leave a comment

Thank you

Thanks for trying out this first issue. There are already plenty of newsletters about technology, but I wanted to create a place to think through some of these changes out loud. At the very least, it’s an excuse to share the things I’ve been noticing.

One of the best parts of writing online has always been the people you meet along the way. If this issue resonated with you—or raised questions of your own—I’d genuinely like to hear from you. Conversations like that are half the reason to do this.

And if you know someone who spends time thinking about technology, leverage, and the trade-offs that come with it, feel free to forward this to them. I’m always interested in finding others who are paying attention to the same signals.

Thanks again for reading.