Yes I fired him, and I offered him the option to take 50% off his bill or chase me for payment. He chose the former.
3,472 karma · joined January 7, 2023
He amortized the goodwill of businesses I acquired over 5 years instead of 15 (incredibly basic stuff, which Claude flagged with *CRITICAL ERROR*). When I asked about it, he said he had caught the error in his review but forgot to save after he fixed it. I don't know if there's a good response to making that kind of a mistake, but if there is, it's definitely not that one.
It will always remain weird to me that a publication called Futurism is so outright negative towards our newest technologies.
People love to complain about Amazon fees, but when I read things like "In 2014, this was about 19% of sales. But today, many sellers hand close to half of every sale to Amazon. Half!" I wonder why people who are so lacking in subject matter expertise decide to write these articles.
The main reason that Amazon charges so many fees is that they provide a truly mind-boggling amount of infrastructure for you. The main reason the percent you pay to Amazon has gone up is because they've added more services. The author of the post notes that only the referral fee is mandatory, but doesn't manage to quite put together why going from only referral fee to a bunch of extra services means that Amazon now takes more of every dollar.
Once upon a time, you'd list your stuff on Amazon, and when someone ordered a product, you'd ship it yourself. Then Amazon decided to allow third party sellers to use Amazon's storage and fulfillment. Now suddenly the percentage of each sale's revenue that went to Amazon doubled! And yet, this was 100% positive for merchants, because Amazon's storage and fulfillment prices are cheaper than almost any alternative. When you move from a 3PL to Amazon's fulfillment, you pay Amazon more, but your profit margins increase. (There are exceptions for some product types, but the overwhelming majority of the time you save money.)
Of course, Amazon's fulfillment centers started running out of storage, so they'd limit how many units people could store there. That meant larger sellers would still have to maintain their own storage solution for anything that wouldn't fit at Amazon. But then Amazon introduced AWD, an upstream storage solution where you can store basically an infinite amount of stuff still packed by the case, and it ships to FBA warehouses when needed. More money for Amazon! But AWD is cheaper than basically any 3PL's storage, so more money for me too.
Amazon then introduced a service that let you book freight in the US with them to get things to their warehouses. Then they introduced freight to get things into the US from overseas. Then they introduced even cheaper AWD warehouses in China. You're not required to use these things, but Amazon wins a lot of business with them because they're cheaper than competitors.
This is not to say that everything Amazon does is great or that all of their fee increases have been net positive. First they introduced a fee if your products sit in FBA warehouses more than six months, then they introduced a fee if your inventory gets too low relative to demand. These are annoying! (Though also I have almost never been affected by them, because the amount of inventory Amazon wants you to have is basically the optimal amount from a planning perspective anyway.)
There's advertising, which, yes, is very annoying to have to pay for, but y'know what? You have to pay for that on your own site too! I have one brand where I do a healthy business on my own Shopify site, but I keep less of every dollar on there than on Amazon because I have to spend more on Meta ads to get a sale than I do on Amazon ads.
People love to hate on Amazon (and, again, lots of valid reasons for this!), but at the end of the day they collect an enormous amount of money because they provide an enormous amount of value.
When it's done, it generates a web page with the images and a simple UI for feedback, then uses the feedback I give it to iterate.
It has always been very good at styling things well (i.e. if I'm making infographic-style images, I give it an example of one and it's good at copying the style/fonts/colors/etc.), but I suspect I get better-than-average results in terms of the content just because it has built up so much context from doing this and taking my feedback across so many different brands and images.
The product dimension thing really stopped being an issue for me with ChatGPT Images 2, and the new 2.5 is better. If you're running into trouble, there are some cases where Gemini is better, but they're rare. But I will say if you're prompting yourself and running into issues, you should get Claude/ChatGPT to help you write the prompt that goes to the image model. They're very good at it.
A little more on my process here: https://theautomatedoperator.substack.com/p/the-dumbest-way-...
I buy them off of Amazon. But that doesn't really matter that much compared to the history of reviews.
> And yet we all know Amazon sellers juice their sales metrics and ratings with scammy practices, and now I see selling their brand is part of the incentive.
You just read that online and have the most superficial understanding possible. I know what I'm doing, and it's trivial to avoid this kind of thing.
> And more, you are AI-generating listings and images for your acquired brands. You're filling Amazon with slop, and automating the process.
Bad criticism. There's nothing wrong with an AI-generated listing if the content accurately represents the product. I have purchased brands that had horrendous images because the seller tried to Photoshop them but wasn't good at it. Replaced those with high-quality AI images, and everyone wins - the customer better understands what the product is, and I get more sales. It's only slop if you just think everything AI-generated is slop regardless of what it is or how it's used, and if so that's too intellectually lazy of a position for me to try to disabuse you of.
> You should seriously reflect on your role in polluting these marketplaces.
Help me out with that. What's my role? I buy brands that sell high-quality products, increase the quality of the content and marketing, and make money selling them. The sellers of these brands are frequently people who started them on the side but don't have the time to continue, and I get them a fair price in exchange for their businesses.
So what is the pollution that I'm causing?
Yeah, the most recent brand I acquired had enough customer contacts via FB/IG comments and messages, plus email, that I had Claude build out an application for me where it pulls those in as they come, drafts a response including any actions that need to be taken, and lets me edit or send. It takes any edits as feedback to refine its playbook, so its gotten pretty good now. Handles things like warranty claims (get picture of the damage plus order number, create replacement order, send email confirming replacement order) plus most common questions. Still entirely human in the loop, but I'm going to let it start handling common cases autonomously soon.
On the topic of starting an autonomous agent-run business from scratch, I had Claude set up a bunch of websites that pull publicly available (but somewhat annoying to access) government data, display it in easy to read format and send weekly emails. It's now running on its own with a couple levels of management - first, it does a weekly review of Google Search Console/GA4 and updates or creates new content to try to improve things from an SEO perspective. Then second, once a day it tracks all of the problems that have arisen over the past day (usually issues pulling the data or issues with the prose the models write), corrects them, and then tries to improve the system to stop them from recurring.
I'm not really keeping tracking of it at the moment - too much other stuff to do right now - but it's getting a trickle of subscribers and is slowly rising the SEO ranks, so for now I'm content to let it sit and see if it ever gets to the point of being monetizable.
Or I guess to put it another way, if we want to coin a new term for the intelligence-esque thing that AI has, but the key differentiator is that it's an AI thing and not a human thing, then what linguistic value does the new word have? If I said "Claude is intelligent" then the fact that we're talking about AI "intelligence" is already captured in the sentence anyway; no new word needed
Anyway, I'm sure the app you makes that lets you get a phone number that can send image messages is very complex, and I think that's very nice.
And for the record, I only buy brands that sell high-quality products. Marketing and operations I can fix, but if the stuff they sell is no good, there's no point.
In other cases I'm doing stuff that's complex enough that there's no real "alternative" at this point that doesn't involve hiring one or more people and working with them for an extended period. My next set of posts is going to be about my latest acquisition and how AI redesigned a Shopify store then designed and launched Meta ads, all of which only took a couple of days but is going to easily push revenue up by something like 40% this year. The money made is great, as is the money saved on people I would've hired to do this sort of thing, but the real cherry on top is that even hiring someone would've required me to spend waaaaay more time than I did here. So big ROI on the money but also the time, which is arguably more important, since time savings permit me to acquire more brands.
Silly and pointless criticism. Why do the semantics of the word intelligence matter?
Also, you need to understand that language evolves over time, and people often use a word to describe a thing that is newly discovered or invented that's similar to the word being used, because it's a helpful way of describing it that the listener will understand better than a longwinded technical description. The purpose of language is to communicate thoughts, not engage in pedantry.
> But things like this slip by a frontier model in the same way AI from a few years ago would generate an image with seven fingers.
Yes, you make an excellent point here that over time, the capabilities of these models to recognize certain categories of problems have increased dramatically. I expect this will continue!
> it's foolish to give them "a company" to run, because they cannot understand when they've made a mistake the way even the least competent human can.
The words of someone who has not spent time with the least competent human, or anything close to it.
The experience of getting it there makes me pretty skeptical of the idea of a general business agent like this. First, because I still find myself having to review some categories of work for errors. These are decreasing over time, but they're still there. I fully believe that as models get better, errors will decline, but I am somewhat surprised to see some of the errors current models make given their intelligence. A common set is having Claude take some product photos and turn them into lifestyle ones using ChatGPT via Claude in Chrome. It's a pretty well-honed workflow at this point, but it'll still return images where the product is obviously not correct and seemingly not notice them.
Anyway, even if the agents are "perfect" in terms of their ability to execute tasks, there's still just an enormous amount of nuance and context in each business that takes a ton of time to convey. I've been at this for a couple of years now, and I'm still clarifying things. Now maybe an agent starting a business from scratch would have a better time since it's not inheriting all of this, but to have one run an existing business requires a very extended handoff, even if the agent is objectively amazing at all aspects of running a business.
I've got all kinds of useful tools that do helpful things, like check to make sure Amazon hasn't lost a bunch of my inventory or suddenly deindexed my product from search. These sorts of things happen without warning from time to time and are trivially fixable if you catch them, but you have to be constantly monitoring 10 different things to catch anything that could go wrong in a timely fashion.
I've similarly got an inventory/cashflow management system that's deterministic that would be fine, but some of my other tools, like one that scrapes my Alibaba/WeChat/Whatsapp/Gmail supplier convos to keep my order status board updated, is finicky. I wouldn't be able to repair that once it broke.
For some tasks, I'd have to go back to freelancers. At this point, when I take over a new brand and want to refresh images or want to A/B test new ones with an existing brand, I can do that entirely with image gen. No AI would just send me back to Upwork.
For other tasks, I'd just have to do them myself. Right now when I acquire a brand, I have a Claude skill that runs through all of the Amazon search and ads reports to find the key search terms, analyzes the text of the listing and proposes updates to make sure we're hitting the ones that matter. I used to do that myself, but it takes somewhere between 2-10 hours depending how many products we're talking about.
The biggest loss would be the inability to expand. I started out just buying Amazon-only brands because Amazon provides a crazy amount of infrastructure that enables me to run a lot of them by myself. My most recent acquisition came with a Shopify site that had minimal sales plus a Meta ad account the guy who sold me the brand had done a little experimentation with. A year ago, I would've just discarded those, since my time is the biggest bottleneck. It takes a lot of time to run your own site and Meta ads, so it makes more sense for me not to bother and instead just make more Amazon-only acquisitions.
But now I'm having a great time really pushing Claude and ChatGPT to do most of the work. I redesigned the site more or less by just having ChatGPT do research on competitors and best practices, then having Claude run with that. That took maybe eight total hours of work.
I'm spinning up an enormous amount of creative to test on Meta, and I had ChatGPT research and spec all of the kinds of landing pages that are worth trying. Claude implemented them and set up the ads using Meta's ads APIs. I got all of that done yesterday.
So yeah, basically if I couldn't use AI any more, I'd get back to the original thesis of my business, which is buying small brands at reasonable prices and operating them as leanly as possible. It still works, but it'd be a lot less fun and profitable.
Silly obnoxious social proof popup is clearly on the ethical side in my view (my issue was never ethics, just that I personally find them very annoying). I'm not misleading anyone (it does in fact show real purchases) or forcing anyone to do anything. If that's the difference between you buying or not, I still feel perfectly comfortable that you made the choice of your own free will.
I ended up trying it. Boosted conversion rate meaningfully. Worth the price I pay in mild self-loathing.
Chesterton's popup, I guess.
But you're right that it'd make sense to have an aggregate view on the level above (e.g. https://the-dwell.com/anchored). I shall go command Fable to figure out all the places where this would be appropriate and add it.
It started getting some search impressions and clicks, so I decided to launch the next 9 of the top 10 ideas that ChatGPT came up with for this type of site - won't post all of them here, but https://the-dwell.com/ (data on ship and truck dwell times/port congestion) is doing the best thus far from a traffic perspective.
First I had it send me a weekly analysis of the GA4/GSC data to see what could be improved about the site, but I've since automated that - each week it reviews traffic and search queries, then updates articles or creates new ones to meet demand. So now in theory I have a full engine to launch these sites and have them self-improve over time. Kinda neat to see all of that being done autonomously.
The thing that these sites really need are some backlinks, so I'm thinking through how to get those. I had ChatGPT generate some lists of places that might find real value in linking to these sorts of things, but I'm unwilling to let an AI agent start emailing people. I'm going to try sending some emails to some of the places that seem like a really good fit, see what the response is, and if it's good try to figure out how to do that on a larger scale without AI email spam.
I get why they used questions where AI models fail, but it also really reduces the value of this study. Nobody is really asking AI the color of a team's uniform in a movie, and if they do and confidently get it wrong, it just doesn't matter at all.
Asking trivial questions also feels like it would affect the rate at which people are willing to confidently say things that are wrong. If you ask me some question of pointless trivia and I ask ChatGPT, I'll probably just repeat the answer because who cares. If you ask me something even mildly important and I ask ChatGPT, I'll either verify the information before I repeat it to you, or I'll qualify that I looked it up with ChatGPT and didn't verify. But some things are just so unimportant that they don't even warrant the disclaimer.
The host made an offhand mention that there's probably a bunch of other similar sites that could be created with all the of useful but difficult-to-access government data out there. That sounded interesting, so I thought I'd give it a whirl!
Working on a few of them, including The Waterline (https://the-waterline.com/) for water info for the western US, The Scramble (https://the-scramble.com/) for egg prices, and The Dwell (https://the-dwell.com/) for container ship dwell times.
All pretty fascinating topics to learn about, plus it's been interesting to see how much of the website setup I can fully delegate to Claude. With Cloudflare to buy domains and put the sites up, a Google Service Account with access to Google Search Console and GA4 to create those properties and a Buttondown API key for weekly email sending, it's almost all hands off for me. Though it refuses to take control of the browser and create a new Buttondown account, which I was surprised is a red line.
> And when the brain encounters something it can’t process efficiently, it doesn’t simply adapt. Brain imaging studies cited in the review show it generates stronger neural responses in visual areas, consumes more oxygen, and in some people produces pain, distortion, or worse.
If the studies are of a person's initial exposure to these sorts of conditions, then that doesn't tell us anything about whether people adapt over time (and to be clear I have not read all the studies, but given the limitations listed I'm comfortable assuming they're not incredibly robust until someone tells me otherwise). I suspect the article's use of the word "adapt" is not the same as mine; from the context when they say the brain doesn't adapt they just mean that it shows a response at the time of the particular exposure they're measuring.
> This paper is a review, meaning it synthesizes and interprets existing research rather than presenting new experimental data. The authors themselves note that current visual tests for susceptibility to discomfort are subjective and poorly standardized. They also acknowledge that the proposed mechanism (that discomfort is the brain’s response to overwork) has not been fully tested, particularly the hypothesis that colored tints reduce discomfort by steering visual stimulation away from overactive brain areas. The relationship between the brain’s excitatory and inhibitory chemical signals and visual discomfort also remains, in their words, “unsettled.” Several key research questions are flagged as unresolved, including how to best quantify the real-world impact of visual stress on people’s lives and how to objectively measure susceptibility.
Flickering lights are about the only thing I saw in here that seem like they'd be a problem in the long term. Everything else your brain just adjusts to over time and stops noticing. Maybe the first few days in an office with bright colors would be slightly distracting, but after that you just stop seeing them. I would guess that a lot of the studies they reviewed probably tested people's reactions to these things when they saw them one time, not the hundredth time.