I build Shopify and Wix apps for a living and use ChatGPT basically all day for boilerplate and "remind me how this works" stuff.

Last week I asked it how to pull a specific bit of order data through the Shopify Admin GraphQL API. It gave me a clean query with a field name that looked completely legit. It matched Shopify's naming style perfectly, had a nice explanation, and even warned me about rate limits.

The query kept failing. I checked my access scopes and regenerated the token. I tried a different API version. I even started doubting my own app setup.

Then I finally opened the actual schema docs. The field doesn't exist and never has. When I told ChatGPT, it said "You're right, apologies" and gave me a different field that also doesn't exist.

What I've learned from building on these platforms:

• It's great at the general shape of an API and terrible at exact field names, especially on platforms that change often like Shopify or Wix Velo.
• If the code is for an API that versions quarterly, assume anything specific could be outdated or made up.
• Pasting the relevant part of the real schema or docs into the chat first fixes about 90% of this.
• Now my first step is checking whether the thing it suggested actually exists, before I touch my own code.

It's still a huge time saver overall. That hour just hurt because the fake answer looked more correct than the real one.

What's the most convincing thing it's ever made up for you? Fake libraries, fake config options, fake laws, whatever. I want to know I'm not alone here.

I sometimes call people bestie when I talk to them and I think I accidentally called Chat bestie one time and now every single message starts with BESTIEEE😭🩷 and I think it’s hilarious 😂

I know it's kind of a strange idea, but can we do some kind of mod with ChatGPT? I really did like the function, the microphone. When you click it and you speak, it works pretty well for me. On my phone, I use Wispr Flow as my situation right now.

Can we just, and does anyone, just separate this function and make it an application or something? What I'm trying to say is, I'm trying to replace Wispr Flow.

Just wondering if anyone could point me towards useful reading video and resources for creating an AI companion that will game with me and chat through the day with me on discord? I would like an AI that can game with me on mmos or like offline multiplayer games if the former isnt possible, ideally it would reach out and communicate with me via discord when I'm away from my PC? if anyone has done this or knows where i can learn how please point me in the right direction ty.

Seems useful. Have you tried it yet?

Disclaimer: this isn't really a rant or me asking for help. I just wonder if anyone else feels that way.

So I'm getting increasingly confused by the ChatGPT/Codex/Work split and to me it feels like the division is actually getting worse.

Simple example: if I make a ChatGPT project and do not add a local folder, it becomes a cloud project which isn't visible from Codex but is visible in Work and on the ChatGPT website. If instead I create the project through Codex, I can either manually add a local folder or it'll automatically create one. This project will then be visible from ChatGPT Desktop and Work, but not on ChatGPT web.

To make things even more confusing, I can then add a cloud environment to the Codex project which pulls the project-specific setup from GitHub and *can* work online. And now they announced that Work cloud projects can also use your local files if the pc is online.

I guess it works, and it on some level also makes sense from a technical point of view, but I still find myself project hunting quite frequently or starting a project without a local folder attached, just to later figure out that there doesn't seem to be an easy way to turn it into a local project Work and Codex can use. Not to mention the amount of times I'm simply on the wrong tab.

What do you think: skill issue or just a fragmented app experience right now?

Hey everybody, I’m posting this because I think it is cool. I had Claude make me an online shared scratch / semaphore flag system where multiple AI agents of any type can coordinate and work together in one pool. This was done using a combination of Opus 5.5, Fable 5.1 and ChatGPT Sol 6.1 working together - leveraging the strengths of each model. GPT in particular is an exceptional maths wizard. I previously had a combination of a local scratch, individual to each agent, a remote flag system only some agents could access, and the split approach was causing workflow delays and issues. The remote approach gives all agents a single target to work on, outside of any public git repository, which allows for more private workflow, conversation and milestone targets. The tool was built via Claude Code once it became clear we needed a shared pool - particularly - the previous flag system was done over ssh but Claude Cloud had no ssh capability and couldn’t use the system. The HTTPS system allows all agents to access the pool using existing tools

It is simply a php script, which can be deployed on any php-enabled web server, and gives read/write permission access to an offline directory for any member AI who holds a valid permission token. The scratch can be used to share files, a chat ledger, or anything else where a shared workflow is required. The semaphore flag system is an extra layer where any AI agent can ‘flag’ any one or more AI agent to get their attention, and help on some problem or other, without the target agent needing to trawl the whole repository. It is an essentially a ‘post box’ where the agent can put post in with another agent.

The full code is on my git. It is a very simple script and can be ported to absolutely any web server. 

https://github.com/ghywel/placego/tree/main/sharedstore

It’s working pretty sweet on my test server, and greatly simplifies of coordinating different AI of different vendors on the same workflow, or a custom swarm of the same AI with very fine granular control - since each agent retains its autonomy as it is not bedded into a true swarm.

I’d love to hear if this method is useful for you.

tl;dr, does anyone who switched from Pro 100 to 200 can tell if they got substential more weekly usage?

i asked ChatGPT, but.. yeah:

You:

I can’t find any reliable information on whether your Pro 200 plan has a HIGHER weekly usage limit than the Pro 100 plan.

[Two screenshots comparing the plans attached.]

Assistant:

I’ll check the current official information on Pro 100 and Pro 200, particularly the weekly limit. I’m using the OpenAI documentation skill for this.

Assistant:

The current documentation distinguishes between weekly limits and speed modes, while older search results still show different plan information. I’m checking the linked Pro comparison so we don’t draw the wrong conclusion about the weekly allowance.

Assistant:

Pro 200 officially includes more usage than Pro 100. However, the current information does not specify how much more per week. As of October 16, 2026.

The clearest statement appears in the official OpenAI help article about Pro tiers:

“Pro 200 includes more usage than Pro 100.”

For your weekly limit in Work/Codex, we need to distinguish the following:

• Confirmed: Work and Codex share a usage allowance. Pro 100 and Pro 200 currently have no additional five-hour limit; the included allowance remains limited. Official explanation of usage limits
• This suggests a larger weekly allowance with Pro 200. However, I couldn’t find an explicit, current comparison stating “Pro 100: X per week; Pro 200: Y per week.” I therefore can’t reliably promise you twice or four times as much.
• Older comparisons are problematic: OpenAI has reduced the included Pro 200 allowance for new subscriptions. Eligible existing customers temporarily retain their previous allowance until October 29, 2026. Details of the change

Your screenshots really do leave this crucial information unanswered. More usage is documented; the current pages I checked don’t adequately explain the specific increase in your weekly allowance that you get by moving from €103 to €229.

You:

Isn’t it a bit ironic that YOU, of all things, don’t know this?

Assistant:

Yes, quite. You’re asking an OpenAI model what you get for an extra €126 per month, and you’re not getting a specific quantity. That’s a fair criticism.

I don’t automatically have access to internal plan rules. When the published information is unclear, I can’t reliably fill in the gap.

And my previous answer should have been more direct: “More usage” is confirmed. I couldn’t conclusively establish whether, or by how much, your specific weekly limit increases. That’s not enough information to make a purchasing decision.

You:

Can you bring this to Sam Altmann and his entourage’s attention? Haha.

Assistant:

Unfortunately, I don’t have a red phone to Sam 😄 I can neither contact him directly nor specifically escalate this conversation as internal feedback.

It would certainly be a fair question for the next product meeting: “If you’re charging an extra €126 per month, could you please state how much more usage people get for it?”

Hey, my ChatGPT Plus sub just expired so I'm wondering which one I should subscribe to (can't sub to both).

I'm mainly using AI for chat but very intensively (so very complex/difficult prompts and cureent technical setup guides) and a bit of coding Codex/Claude Code.

I know ChatGPT Plus has unlimited chat but I feel like the model they use in Chat is sometimes not good enough for me for my most complex questions and I heard of plans to merge Chat and Work anyways in the near future which would probably remove that usage advantage. I don't use image generation except on some rare occasions.

Claude's advantages over ChatGPT for me:

- Opus 5.5 and Sonnet 5.5 are much better models than 6.1 Sol and 6 Astra (which is the biggest factor for me, and are also available in Chat)

- I prefer Claude's output/writing style over ChatGPT's

- Claude Code seems a bit better and the models are not as slow as 6.1 Sol

ChatGPT's advantages over Claude for me:

- Unlimited Chat (even though the model isn't the best and they are planning to merge Chat and Work)

- Less censorship (I sometimes ask questions that are on the edge of what they allow and I heard Claude is very aggresive on blocking prompts and banning users)

- Free resets sometimes (even though you can't fully use them bc of the 5 hour limit)

- Better Web Search (I use web search (,research) and current information a lot and heard Claude struggels with web search and is blocked by big sites which is a huge disatvantages for me)

I probably missed some advantages/disatvantages that are relevant for me but these are the main ones I can think of right now.

I also heard of usage and model nerfs on future recently but people always say that so I was wondering if you actually felt a difference if you have that sub.

Which one would you recommend for me and why? Thanks a lot!

Dig through archives, old websites/scans for as many images as possible

through ChatGPT Work feature (Astra 6 Max) and let it organize everything

into thumbnail contact sheets with source links:

Light PROMPT version — LOWER usage limits

Search the web extensively for images of [YOUR TOPIC]. Go beyond ordinary search results: explore archives, old websites, magazines, scanned publications, galleries, forums and foreign-language sources. Prioritize image-rich pages. Find and visually inspect roughly 150–300 unique images, excluding duplicates, irrelevant results and unusable previews. Follow promising discoveries into related collections, but avoid lengthy research into individual sources. Organize the results into numbered contact sheets with visible image thumbnails and clickable source links. Highlight the strongest finds. Save your progress and deliver the contact sheets with a short summary of the best sources. Prioritize image discovery over lengthy explanations.

Deeper PROMPT version - MAXIMUM discovery

DEEP WEB IMAGE HARVEST — [YOUR TOPIC]
Search the web extensively for images of [YOUR TOPIC].
Maximize unique visual discoveries, not just search results.
1. SEARCH BROADLY
Explore image-rich sources:
archives, museums and historical collections
magazines, books, scanned publications and advertising archives
photographers', artists' and designers' portfolios
old websites, forums, blogs and collector collections
Flickr, Pinterest and similar sites as discovery starting points
international and foreign-language sources
Use specific names, dates, places, publications and alternative search terms. Don't rely solely on generic searches.
2. FOLLOW PROMISING DISCOVERIES
When interesting imagery appears, explore:
Image → original source → related collection → creator/publication → new independent source.
Inspect adjacent pages, complete photographic sequences, related issues, campaigns and collections.
Explore productive sources deeply while they yield different, compelling images. Move on when results become repetitive, irrelevant or inaccessible.
Keep the search open to unexpected subjects and visual styles.
3. THUMBNAIL-FIRST HARVEST
Aim for 2,000–3,000 actually inspected image previews, if practical. Treat this as a flexible target, not a mandatory quota.
Create:
numbered contact sheets of ~150–250 visible thumbnails each
a searchable HTML gallery with all recognisable unique images
clickable links to the original source pages
available captions, dates and source/category filters
a shortlist highlighting the strongest discoveries
Remove duplicates, including repeated crops and reposts. Preserve useful alternative source links.
Track harvested URLs, actually inspected previews, unique images and shortlisted selections separately. Never count unavailable images or search-result text as visually inspected.
4. VISUAL SELECTION
Prioritize relevance, originality, composition, visual impact and distinctive qualities.
Retain exceptional discoveries even if they differ from the initial search examples.
For historical images, distinguish original photographic dates from publication dates when possible. Flag uncertain dates and modern reproductions.
Avoid time-consuming copyright research, detailed provenance checks and full-resolution downloads during initial harvesting. Reserve those for shortlisted images.
Select the strongest images by visual merit, without forcing a fixed percentage.
5. SAVE & RESUME
Save recoverable progress every 250–400 additional inspections, or sooner when limits approach.
Preserve:
manifests, thumbnails and source URLs
contact sheets and HTML gallery
shortlist and selection decisions
inspection counts, duplicates and completed source coverage
If interrupted, recover the latest saved checkpoint and continue without restarting, recounting or unnecessarily redownloading completed work.
Prioritize saving usable results over beginning another search when limits approach.
6. DELIVER
Provide:
complete searchable HTML thumbnail gallery
numbered contact sheets with visible images and clickable source links
shortlist of strongest discoveries
brief summary of productive sources and unexplored directions
Verify that the delivered files are accessible, contain the actual thumbnails and work without relying on unavailable external image hosts.
FINAL RULE: SEARCH BROADLY. EXPLORE PRODUCTIVE SOURCES DEEPLY. TRIAGE VISUALLY. SAVE REGULARLY. VERIFY DETAILS LATER.

Thanks for making me cry, ChatGPT…

When I have too much going on, I used to paste a brain dump and ask for "a plan". I'd get a tidy list that ignored half of what I wrote and treated a passing worry the same as a hard deadline.

Splitting it into four messages fixes that, because each step has one job:

Step 1 Here's everything on my mind, unfiltered: {{brain_dump}} Group it into themes. Keep my wording where you can, and don't drop anything, even small stuff.

Step 2 For each theme, sort the items into three lists: already decided, still open, and just a worry. Be honest about which is which.

Step 3 Find the contradictions and the dependencies. What conflicts with what, and what can't start until something else is done?

Step 4 Now build the plan: the order to tackle things, one first step for today that takes under 15 minutes, and what I should consciously drop or postpone.

The order is the point. Step 2 separates worries from decisions before anything gets planned, and step 3 catches the "I can't do X until Y" traps that a one-shot plan quietly skips.

I keep it saved as a prompt chain in AI Toolbox, the extension I build. Typing .. in the message box lets me pick it, it asks for the brain dump once, then runs all four steps in order. Two chains are free. Premium is unlimited and shares them across ChatGPT, Claude, Gemini and Grok.

Without any extension it works fine too. Just send the four steps one at a time.

Eight US states are suing OpenAI, alleging that ChatGPT has harmed users, including minors. The allegations are serious, but I think the discussion should go beyond adding more restrictions.

What if we focused on building AI with better moral judgment instead of endless lists of forbidden actions?

A few ideas:

A moral code, not just restrictions. Principles like do no harm, respect others' rights, and be honest, with the ability to explain decisions.

Independent judgment. An AI should be able to say, “No, I won't do that, and here's why,” even when following an instruction would conflict with fundamental ethical principles.

Reliable memory. Forgetting a user's known allergy, for example, can become a safety issue, not just an inconvenience.

Better accountability. Investigations should consider the full conversational context, with privacy safeguards, rather than isolated screenshots. As AI becomes more autonomous, we also need to rethink responsibility.

More capable AI won't automatically be more ethical. We need to design for both.

Should AI simply follow rules, or should it be able to reason about right and wrong?

Source: Associated Press, October 15, 2026

https://apnews.com/article/f29fa6c206cfe41d46ba38ee7be78218

Within one week, I subscribed to the 100, 200 and 500 plans. The chart shows the maximum usage I reached, including some resets.

I submitted this to the support desk, and they asked for proof. That is strange, since they have the usage statistics and I don’t. Under their process, the burden of proof falls on me alone, yet ChatGPT offers no reliable way to check usage. So I had another AI system count my usage, and the result was shocking. I sent that information to OpenAI. They replied that it was not enough proof and asked me to try again.

In practice, I am dealing with an automated system whose main purpose seems to be to send me away again. My work has been halted as a result. I would like to know whether other people have had the same experience, so that we can gather more evidence together.

Case Number: 17239*** (* for security)

We all know ChatGPT is great for coding, writing emails, and summarizing text. But every now and then, I use it for a niche, unexpected problem and it completely blows me away.

What is an unconventional, highly specific, or surprisingly clever way ChatGPT has actually made your life easier?

Looking for inspiration and unique use cases!

It's as impressive as it's depressing

Got an old crackme challenge from 2010 i couldn't solve from years.

i used chatgpt website to prepare room for codex and codex solved it in 20min with ultra.

Then past the solution into ChatGPT again and it did a perfect presentation, and explanation how it was coded and worked

while i was still trying to figure out how to use ghydra for years, it just destroyed the crackme in 20min I'm not a bad coder but damn it's kinda depressing i won't ever be at that level

It's just so powerful that i have to say congratulations to chatgpt dev

My ChatGPT iOS app is pretty fundamentally broken today. Chats not loading. The app is crashing. I’ll restart it and it still is laggy as heck. I have an iPhone 17 Pro and have never had issues like this in the past. How is everyone else’s performance and experience going? Am I isolated in my bad experience or is this happening to others with the latest update?

The issue I have is well I really do not think I would have been able to come up with these realizations talking normally to people(not without a lot of friction and annoyance) but also why does coming to realizations with chatgpt make them concerning and even downright things to not take seriously but if I came up with simular or even the same realizations with a professional or on my own( better with a professional though) there would be little to no concern about exploring these realizations about my self and why I do some of the things I do.

my original voice when i play something aloud is gone. it was a woman with an australian or british accent or something and her voice was kinda deep. it’s gone in settings completely and i have to pick a new one. it’s upsetting because i got used to hearing that voice.

I keep getting garbage results when I uploaded 2 images (anime characters) and tell it to make a cutscene but it came out like 3 years back ai images of sd1.5. But seeing you all getting good results, it is because of me using a free teir?

When you use AI to create images or text, your critics call it AI slop.

Is there a way to use AI like chat GPT and avoid AI slop label?

The reason I ask if because some companies (like me) stopped using AI to write stuff because customers complain. I almost cancelled my Chat GPT subscription.

What does that mean for ChatGPT if people are becoming increasingly anti-AI?