idopmstuff

At this point, I mostly ask Claude to use Claude in Chrome to use ChatGPT to create lifestyle images (because I am cheap and I don't want to pay for API usage when I could get them free) based on whatever product shots I have. Sometimes I give it some more specific direction about what I want, but usually for the first pass I just tell it to make 10 or 20 or whatever and see what it gives me.

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-...

> How do you inspect the quality of the products you're selling?

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?

> Very cool! What's been the hardest part? Have you successfully automated non-trivial communications? (for example with prospects, customers, vendors, partners, etc.)

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.

Of course I do. No one buying a business would do it without that information. I get their P&L before I even get on a call with them, and during the due diligence period I get access to Shopify, Amazon, etc. to get first-party data to validate their claims.

So let's say we make up a new word, machilligence to serve as a parallel term to intelligence but strictly for machines. How is the world different in that case vs. if we call it intelligence?

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

I suspect you mean this as an insult, but it's not too far off. That was one of the main points of the business - each one is simple to run, so I can manage a lot of them. And that was before AI got really good.

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.

Blind seems too far here - Claude's increasingly able to diagnose visual issues on its own. I used to have to check every single image it generated, but now it's at the point where it'll catch most bad ones and regenerate them before it gets to the review step. Still misses some, though.

Well that's not 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.

Mostly Claude Code and a lot of internal tools that it's built. I've honestly still not had a chance to play with those kinds of harnesses yet, but my impression is they're just a better way for you to instruct an assistant to take care of things in order to get them done. My goal isn't to be managing an assistant, it's to get things automated without my input (and where my input is needed, have the assistant escalate to me).

That's a fair criticism for some of it, but in a lot of cases I try to automate things that don't have alternatives because they're unique to me (e.g. all the brands I own in my fund have one bank account but need to be tracked separately for investor payback purposes, so I have a Claude skill that takes all of my transactions and assigns them to the various Google Sheets ledgers I have).

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.

> They have no intelligence. These are very very very refined prediction engines.

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.

I am in the process of attempting to have AI run my business. I'm actually making very good progress, but it's happening in pieces - I document some task and have it take over, or I give it something to handle while staying in the loop and providing feedback until it's in good shape. At this point it's handling large swathes of my operations, marketing and finance.

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.

Flippa, Empire Flippers and to a lesser degree Quiet Light Brokerage

One-man show here - I own a dozen small e-commerce brands. I'll assume you're just taking away AI, but not the tools I've built with AI.

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.

Entirely factual. It's "Someone from <city> bought <product> <period of time since purchase> ago!" with a picture of the product. All purchases are real.

Yeah, I mean at the end of the day there is clearly a spectrum of conversion rate optimizing stuff you can do, some of which is fine and some of which is unethical. A/B testing the color of your add to cart button and using the one that converts best? I think it'd be a little crazy to argue that's unethical manipulation. Lying to customers about the product to get them to buy? Obviously bad.

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 started an e-commerce brand on a Shopify site. I swore to myself I would never put up one of those stupid things that pops up "Someone bought X product an hour ago!" messages in the corner of the screen.

I ended up trying it. Boosted conversion rate meaningfully. Worth the price I pay in mild self-loathing.

Chesterton's popup, I guess.

Thanks! There are actually five year charts for most of the data, but you have to click into the page for a specific dataset (e.g. https://the-dwell.com/anchored/east-coast).

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.

The last time somebody made this thread, I posted about https://the-waterline.com/, a site I launched as a side project/eval to see how well Claude can do a decent-sized project (mostly) independently. It pulls public government data about water levels in the western US, updates the website and sends out a newsletter.

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.

"The study, authored by Capraro with Chiara Marcoccia of École Normale Supérieure and Walter Quattrociocchi of Sapienza University of Rome, deliberately used questions where AI models typically fail: visual details from films, such as the colour of a team’s uniform in Bend It Like Beckham."

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.

Yeah good god OP please start writing a Substack about this! Engineer who buys a run-down bowling alley and cleverly fixes problems is exactly what the internet needs more of.

Ah, that is a fantastic idea, it's on my to do list.

Thanks! I am definitely not an expert in either, and I've run the content by both Fable and GPT-5.6 with instructions to make sure it's written in such a way that it would read normally to people in the industry. They assure me the wording makes sense in that context, but we'll see if the sites actually get traction or not.

I heard an episode of the Odd Lots podcast about HayWire (haywireag.com), a site that pulls public data from government PDFs + APIs, uses LLMs to parse it and turns it into an easily readable website that has all of the latest info on hay prices.

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.

I assume you're referring to this:

> 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.

The Limitations section at the bottom certainly has a lot of limitations:

> 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.

I own a dozen Amazon brands that are probably largely of the kind that OP would want this to get rid of (sourced from China, not name brands by any stretch, only sell on Amazon). For the most part I would say this extension is not a great idea (obviously very biased!), since I purchase brands that have high quality products that typically have pretty poor branding/online presence that I can improve. My stuff is very frequently of the same quality (and sometimes from the same factories) as much pricier stuff but at a lower cost. To some of those suggesting you can get this stuff on Aliexpress, in some cases that is true, though of course the big benefit of buying from Amazon is that there's no risk to buying no-name stuff because if it's junk you can return it.

In any case, I gave this a try to see which of my brands it would filter out. It's weirdly inconsistent.

One of my brands was filtered out because there's no brand name at the beginning of the listing. That's just an outright bad rule, because Amazon generally decides whether or not the brand name appears first. This brand is trademarked and has Brand Registry, so it qualifies for that treatment, just not getting it right now. Also, a number of other brands without brand names did not get the same treatment (and these are very much the type of products this is designed to filter out).

On another one, it misunderstood the product model, which is at the beginning of the product name, as the brand and hid it based on that. That one was a bad one because the model is only three characters, which is extremely unlikely for a brand name.

One product I sell is a hunting accessory, so I did some searches there. It hid everything by the brand KUIU, which is a well-known and very high end hunting brand. Definitely wrong there.

So yeah, sort of an interesting idea, but the execution is pretty sloppy and the creator clearly doesn't have a full understanding of how Amazon listings work.

> It might seem obvious to coders, but the difference between Claude Code and Claude.ai's chat is enormous, even if those two run the same model.

In my experience, Claude Code is vastly better for doing tasks, writing code, etc., but Claude.ai is better for analysis and high-level planning. When I'm working on a new project, I've started using the latter to do the initial planning, get feedback and draw up a spec, which then goes to Claude Code.

For this project, I probably would've done something similar - use CC to get whatever you need out of the image files, but have Claude.ai do the actual review/diagnosing.

Either way, I often think about how far behind most of the world is in really understanding AI. The overwhelming majority of people would never guess that you get vastly different outcomes from the exact same model in a different harness (tbf most people don't know what a harness is). I spend hours every day using AI for a broad range of tasks and still feel like I know a fraction of what there is to know. I haven't even tried the new GLM model (or really any of the open source Chinese ones of the most recent generation). With so many people thinking that the free version of ChatGPT is SOTA AI, a lot of folks are in for a very rude awakening at some point soon.

How is AI involved in this? None of the features seem like they would need to use it at all. So presumably AI means it's just vibe coded?

Also, the comparison chart is just dishonest. People didn't e-sign proposals before your product? Come on.

Not worthwhile feels a bit strong (a good FAQ is definitely worthwhile!), but I definitely agree that there is a big difference between any kind of art (writing, playing music, creation of images/videos/etc.) for its own sake and for commercial purposes. AI is terrible for the former but perfectly fine for the latter.

There will always be value in a human writing fiction or a memoir or even a Substack. The human perspective is inherently valuable there. Much less so with ad copy that's just going to get A/B tested ad infinitum until a winner is picked out based entirely on data.

Same with visual art. Art painters aren't going to lose their jobs to AI, but once you've got a robot that can paint a house reliably, house painters are done for.