WTF.

My favorite so far is the "Iff Specs Disk", with technical documentation on an ancient container and data format called IFF (Interchange File Format).

Like in the file ea.iff.85 [0], and this section explaining why common data file formats are useful the first place:

"The problem with expedient file formats - typically memory dumps - is that they're too provincial.

By designing data for one particular use (e.g. a screen snapshot), they preclude future expansion (would you like a full page picture? a multi-page document?).

In neglecting the possibility that other programs might read their data, they fail to save contextual information (how many bit planes? what resolution?). Ignoring that other programs might create such files, they're intolerant of extra data (texture palette for a picture editor), missing data (no color map), or minor variations (smaller image).

In practice, a filed representation should rarely mirror an in-memory representation. The former should be designed for longevity; the latter to optimize the manipulations of a particular program. The same filed data will be read into different memory formats by different programs."

Imagine having to explain to a professional developer today why having something like JSON is valuable. Most of us find it obvious.

But there was a time when this kind of thing was not obvious at all; the need for it had to be discovered the hard way, and then solutions invented from first principles.

We really are standing on the shoulders of those who came before us, in more ways than we realize.

[0] https://amigafreeware.downer.tech/17bit/17bit/61/contents/if...

"As people gravitate toward firsthand perspectives..."

That implies Google is seeing a shift away from people relying on just AI-generated summaries, and checking the cited sources more.

I have certainly found that when I ask a chat tool something, and then go to the human-written source webpage, it's not uncommon I get a different insight than what the AI implied. Not always of course, but often enough that I have noticed it.

[0] https://developers.google.com/search/blog/2026/07/search-con...

What a generous euphemism. Depending on the topic, it's not unusual to see Google AI search referencing links that indicate the exact opposite of what it presents in its prose.

So many of these tools are presented as if they're doing something you'd intuitively expect of a human operator, like collating search results and then summarizing them in this case, but the actual operation of them is so alien to us that our intuitions don't apply and these presentations are all but fraudulent.

Because it's presentation cites references, and because those references sometimes reinforce the expression of the AI prose, we grant it trust, but it doesn't use those references in the way a human would and so the relevance of them being cited is radically different (and weaker) than we're accustomed to.

The closest example in human behavior might be the rushed, naive student who just pastes citations into an already written paper at the last minute, but even that's an anthropomorphism that misrepresents the alien ways in which the tool works.

I've replaced Google almost wholesale with ChatGPT and Claude.

[1] If you use Claude Code to assess a Netlify website (even your own), they'll block your IP address from the entire netlify.app IP range.

I mean, just stop to think about it. You have a Youtube account, you post videos. Analytics shows traffic from Google but can't show you the keywords.

At one point, Google merged Youtube with Google+. Just did it outright without asking anybody.

Youtubers link their Youtube accounts with Google AdSense.

You can link your Youtube account with your Google Ads account if you want to advertise.

One of the latest features added to the Search Console was... an AI chatbot.

So Google showed us they can link anything with Youtube when it wants, and they can add new features to GSC if it's AI, but for some reason showing Google search terms for Youtube channels took 20 years.

I wish I knew a word like enshittification but for when something improves but at a rate so slow you don't even feel like celebrating it anymore. I think I'd use such word a lot...

Do you have a source for this? So far every single LLM-like does a lot of hallucinating, often just small things like wording that implies stronger correlations than exist, or wording that implies relationships that don't exist, etc. but sometimes it's also just wrong facts.

What’s taking them so long? If OpenAI was going to do it, why didn’t Anthropic do it first, or vice versa? Or if we assume collusion: shouldn’t DeepSeek have released a hallucination-free LLM to steal the US’s thunder?

(Good points on AMP and walled garden)

It can sadly not hold any concept of truth or reality as we humans understand it

Boy, was it controversial. I could not believe how hard some people were pushing back in the comments.

Quoting from myself there:

"When you write your own words, you are forging your own voice. It is distinctive, conveys your unique world view, and connects with others in a way that is specific to you alone.

If you use an AI tool to write for you instead, you lose all of that."

That seems blindingly self-evident to me, but apparently a lot of folks disagree.

Something else I said:

"Writing is hard because thinking is hard. When you write, you forge your thoughts, distinctions, mental models and even feelings into the clarity of precision that the written word demands. When you outsource your writing to an AI tool, you lose more than you know."

I guess a lot of people don't want to bother with all that.

"ok

Sent from my iPhone."

emails.

Many people in fact don't like doing. They like shutting off their brain. Sitting still and not using their body and letting muscles atrophy and fat pile up. AI is perfectly aligned with this disease inherent in our post survival civilization. These are the people who would have died off in the hunter gatherer era. Now we go against the forces of natural selection and what do you know, lazy nonthinking people everywhere.

(Not AI, I couldn’t resist!)

But If I send a message with more than one question, there is what feels like a 10% change they will answer all my questions and a 90% chance they will either answer one or none and I’ll just get an “ok”. And I am talking about 5 lines messages not 50 lines.

So I have to send my questions one at a time, wait sometimes minutes to hours for an answer, then send the next one.

Of course I can also call, but often can’t reach them. Or can reach the front desk that doesn’t have the answers. I understand people are busy but it turns something that should be one message into a cat and mouse game

If I peppered someone with a series of questions or worse, bundled unrelated issues into one message, they would all probably be mishandled. I think it was a mismatch of expectations and/or how corporate workers use email apps.

So if I held every message to one topic, one question, things tended to work as expected.

That's what i learned in a big company.

Some were low IQ but had power and money. Some were busy. Some did not want to put any additional effort because the relationship permitted them to be informal, lazy, brief.

In person and with contracts they were extremely diligent with their words.

When I get ready to send an E-mail to a SVP or other VIP at work, I agonize over the wording, get others' feedback on it, write a draft, get it reviewed, write another one, make sure all my facts are straight, make sure there's a TLDR up front, make sure it's formal enough but not stuffy, then clench my butt and hit send...

Then you look at the Epstein files, and these E-mails are going to CEOs and heads of state! And they're like:

    "yo, wasssup retards!! we doin some kiddy diddling FRIDAY. who in???????? peace out bitch4es"

I've spent very little time on LinkedIn, but what I have read struck like individuals writing in the voice of a corporate communications department giving a TED talk.

So, given the kind of metrics many corporations are putting in front of employees, I bet there are a lot of people on LinkedIn who strongly believe writing with AI is the company-approved RIGHT THING TO DO(tm).

In what bizarro world would I want to follow a rando, who has absolutely nothing to do with my career, on a platform purportedly designed for like minded people to advance their career/business?

Might as well consider the dog with the most fleas as the “Alpha”!

The irony is, if one can't ideate or write novels, then why are they writing novels at all?

Also there are so many folks, especially on LI, who don't even have fluent English, or decent grammar, and therefore behind the filter of an erudite LLM is an excellent place to stay, pull some levers, and plop out some really compelling word-salad.

That is just the way of the world today. Whether people are doing minimal processing, through SpellCheck or Grammarly, or just prompting an LLM to generate walls of text, they're using assistance to actually find their voice, or filter their own weak voice through something that will win friends and influence more people than they ever could on their own.

And that is 99.9% of HR, accounting, and every social media related company.

I would never use AI to write in my native language though

Now, AI has given all these Linkedin psychopaths who did not have a voice because of their affliction a rare kind of superpower to endlessly spew their meaningless dribble.

I cringe every time I have to go on the cesspool that is Linkedin, but forced to since am job hunting.

To the extent that LLMs help this where otherwise people would simply have not spoken up, I think it's OK. Of course, the slopisms are an instant turn-off and limit the reach of those ideas, but at least they're out there now.

Personally I've developed a knack of quickly skimming through the bland language to get a sense of whether there is anything interesting enough to re-read more closely. It's become so ingrained that I don't mind wading through all the noise from all the other lazy, content-free slop to get to that little bit of signal.

You know, why should i think for myself when someone else does it for me ? /s

In my case, I self-published and sold a book for several years, and then published an updated version with O'Reilly.

I decided to do that because I came to realize people judge self-publish books as less vetted and lower quality.

That may be often true. But in many cases, a self-published book can be much better than those released by a former publisher. I certainly believe it was true in my case.

But in the end, I decided my highest best opportunity was to go with a well-regarded publisher, for the authority that would bring.

And it changed things. People treat me differently now, like they consider me more of an authority. Even though it's essentially the same book; it just has an O'Reilly logo on the cover now.

Whether that should be the case is up for debate...

But it absolutely made people listen more seriously to my message. and I believe it has massively increased the positive impact of that book on the world.

Financially, I think it's been about even. For me it was worth the tradeoff for other reasons, but I don't think that is always the case for every author and every book.

The whole experience was wonderful. I had basically none of the problems that this fellow experienced with his publisher, and I am delighted about how it went.

I did some things differently. For one, I had already been selling the book on my own for a few years, and was essentially on the 3rd self-published edition. Because of this, they were able to see what the almost-finished product was.

I told them I would not make massive changes to the book, nor would I contort it to the AI trend (the book barely mentions AI at all), and they never pressured me once.

Their biggest contribution was their team of editors. This book has code on just about every page. I had 3 technical editors go through it, finding many bugs. How many? Let's just say "plenty".

And the feedback from the non-technical editors was, to my surprise, even more valuable. Holy crap, I cannot express to you how much they improved the book. There were several of these folks (I had no idea there were so many different specialties for editors), and all of them were great.

(They also accepted my viewpoint when I disagreed with them, immediately, every time. The final published version of the book was 100% my own words.)

From all of that, I made improvements on what must have been almost every page, and rewrote two chapters from scratch. I also added a new chapter (I volunteered for it, no one at any point pressured me to do that). The result was making a book that IMO is at least twice as good as what I was able to accomplish on my own.

I do not resonate with the article author's comments about compensation. He negotiated a pretty good deal, I think; it's not realistic to get much better than what he did, since the publisher is a business with their own expenses to pay, etc.

I was pretty disciplined about meeting deadlines that we agreed to for certain milestones. That helped my relationship with the publisher, obviously.

All in all, it was a great experience, and I am glad I did it this way.

Reading the article, it sounds like my publisher (oreilly) was better to work with than his, but I think he could have done some things differently also. In the end, though, I agree with him that it was best to walk away in his situation.

I will say I was very happy with the animal they came up with! If I was not, I would have asked them to change it, and I bet they would have. They showed me a preview version early on, so there would have been plenty of time to do so.

The publisher he worked with will push you but also make a better book in the end. You have to be willing to do your part.

(Not naming the publisher because I don't want to out myself.)

As someone who buys ads on IG: this is almost certainly because the advertiser has misconfigured their settings for that ad campaign.

My experience:

For most ad campaign types, YES, Meta works far better than any alternative.

In my view, this is because its underlying machine-learning algorithms are better. Not the generative AI mentioned in the article, but the core ML-based learning strategy that every modern ad platform has been based on for over a decade now, allowing it to learn to find buyers for whatever you are selling. Meta is just better at that than anyone else - far better. And has been for years.

Linkedin is quite interesting and can reach audiences no other ad platform can. The problem with LI is that it is tremendously expensive. Think $50-200 per qualified lead, so it only makes sense for very high ticket offers. I've never been able to make LI ads work for lowticket offers (i.e. under $500 gross margin per sale).

I have attempted to run ads on X/twitter several times in the past 5 years, and each time gave up because of how terribly it performed. Literally zero sales from the ad spend, using the exact same ads which worked great on Meta. X is kind of infamous among media buyers for how bad it is. But I haven't tried it in over 8 months, so maybe it has gotten better now. Grok/xAI is quite good, so I am not sure why they haven't made the X ad platform a priority. If they did, I bet they could eat Meta's lunch.

Google is really 3 ad platforms: Youtube, Google Display Network (GDN), and keyword search. These are all radically different in many dimensions; the only thing they have in common is that Google lets you set them all up through the same web interface.

Mostly I run ads selling mid to high-ticket stuff to sophisticated buyers, and I think most of those people have Youtube Premium, which makes YT ad-free. So I haven't tried running ads on Youtube much. My media buyer colleagues who are into it are mostly selling mass-market offers that most people on HN would consider kind of scummy. They tell me it can work well, but requires a lot of ad spend over weeks to start working. In contrast, I can often get a Meta ad campaign profitable within 48 hours.

Keyword search works great, but only for "bottom of funnel" buyers (i.e. people who are actively looking for a solution they can pay for right now). There are only so many of those, so generally you cannot scale up ad spend (and thus absolute profit) very high. In contrast, Meta can create new "top of funnel" buyers, which is a larger audience by many orders of magnitude, which allows you to ramp up some Meta campaigns to a very high level of profitable ad spend.

GDN has been tricky for me. I think it has a lot of potential, but it has a very different model, and so far I have not been able to make it profitable for my offers. It certainly seems easier to set up a successful campaign with Meta.

Short answer to your question: Yes, even with the things the article is justifiably griping about, Meta is just way, way better than any alternative right now.

Is it possible to start small with Meta and then ramp up? Any principles to adhere to increase probability of success?

It depends. What kind of offer are you selling?

Generally the learning curve is massive, long, stressful and expensive. I lost tens of thousands of dollars before I could consistently make ads which were profitable.

It's not like learning coding. Imagine if every time you saw a stack trace, $250 was deducted from your bank account. Learning media buying is kind of like that.

Another path is to get hired by an ad agency. They will train you and give you a budget to manage; if you lose that budget, the worst that can happen is they'll fire you (rather than losing all your stuff).

But that would be a switch in career path, which I do not think you are asking about.

what is the source for that uphill curve is that because its not clear what your user wants or optimizing ad copies ?

im definitely not looking to spend thousands of dollars, figured starting out small hmmm

getting hired by ad agency seems interesting reminds me of trading desks a bit

There is also the investment in learning, which would require 5-10 hours per week that whole time.

I say this because anything short of that is likely to lose money and accomplish little.

Not trying to gatekeep, so feel free to try it however you like. Maybe it is worth you trying to set up one ad just to see if you like the process enough to continue.

do you have any recommendation for an alternative? seems like for now i am going to defer the Meta ad experiment , was thinking of targeting TikTok videos

If are worried about the significant expense and high risk of paid ads, which is very reasonable, I recommend you do not do paid ads at all.

I think a better alternative for you is to learn to create organic content, e.g. videos for IG and tiktok, or text posts for platforms like X. And learn to stimulate sales of your app that way.

This also has a long learning curve, but dodges the financial risk of paid ads. Once your organic content is dialed in enough to make consistent profit, you'll be much better positioned to start with ads and be successful.

Good luck!

The only defense is to have checklists and continually go over running campaigns to make sure everything is configured properly, which as you note is really hard to turn off. Very easy to miss a detail in ad manager's complex UI.

...not if the Republicans stay in office.