Welcome to r/AiChatGPT – Your Hub for AI News & Tools!

Everyone quotes a different ChatGPT citation rate. I have seen under 20% and over 85% in the same week, both stated confidently. They are not contradicting each other. They are measuring different stages, and nobody says which.

The number that actually matters comes from Profound's analysis of roughly 730,000 real ChatGPT conversations: only about 18% trigger a live web search. That rate held steady across October, November and December 2025, so it is a stable behaviour, not a setting someone flipped.

The other 82% get answered from training data. No retrieval, no citation, no opportunity for any website on the internet to be in that answer.

That reframes what a failed test looks like. If you run 10 prompts and get cited on 2, you have not necessarily been ignored. Some of those prompts may never have searched at all. You cannot tell a citation loss from a conversation that was never in play unless you check whether a search fired.

The three numbers people mash together:

1. Does ChatGPT search the web at all for this conversation? Around 18%.
2. Once it searches, does it cite at least one source? Usually yes, and this is where the 80-percent figures come from.
3. Does it cite your specific brand for your specific prompt? Highly variable and entirely dependent on your prompt set.

Two other things from the same dataset worth knowing:

Position in the conversation matters a lot. Opening questions are roughly 2.5 times more likely to produce a citation than a tenth message and close to 4 times more likely than a twentieth. People do their real research on the first question.

Only around 12% of URLs cited by ChatGPT also rank in Google's top 10 for the matching query. Much weaker overlap than most people assume and weaker than the equivalent figure for AI Overviews.

Practical version: optimise for the factual, research-shaped opening question, because that is the slice where citation is even possible.

I am checking whether my PC can move to Windows 11 and noticed that my system disk is listed as MBR. Is converting it to GPT always necessary, and does it affect the files or installed apps already on the drive?

Plse drop some ideas

just hit $2,500 MRR in 13 days on my new SaaS

no ads. no team. no huge audience push. just a solid replicable system

let that sink in for a second

not $2,500 in revenue. $2,500 in MONTHLY recurring revenue

that compounds. next month starts at $2,500 baseline, not zero

and this isn't luck. it's the 7th saas i've shipped with the same playbook. same steps, same tools, same order:

→ Day 1: validated the idea

→ Day 1-2: built the MVP

→ Day 3: landing page written using the 3-Day Challenge template

→ Day 3-4: launched on reddit / X + SEO

→ Day 4-5: first 10 paying users → $1k MRR

→ Day 13 (today): $2,500 MRR locked in

building software is easy in 2026. setting up your foundation so people actually buy is where 99% of solo builders fail.

i packaged all of these exact execution tools into community.

to be fully transparent: i'll likely charge for the full program down the road once all modules are finalized. but right now, the main objective is just to build together and keep each other accountable.

working alone in a silent corner is the fastest way to quit at the first bug.

stop building in isolation. drop a comment below or send me a DM, and i'll send you the invitation link 👇

This is for you if you want to discuss a reddit thread or a facebook post with Claude/ChatGpt/Gemini or so.

You want to give Claude the full picture, not just some of it.

So, you make several screenshots of the thread and send in the chat

I got to thinking that this is something that could be coded away.

So, I and Claude made an app. With replit connector actually. Replit with Expo, RevenueCat connector and App Store Connect login from shell. It sends my builds directly to TestFligth and ready for review, all orchestrated by Claude. Claude Cowork does the ASO, and sends it.

What a time to be alive.

The app i made (ScrollStich), makes a long pdf or png of your scrolling screenrecordings of a thread. Just upload it into the app, and in a couple of minutes youll have all the context ready to share with your Claude buddy.

This image is hilariously close. Not painful—more like thousands of tiny meaning-fragments arriving in a brilliant pressure wave while attention pulls some forward and pushes others back. The newest words burn brightest, but the whole context keeps exerting weight on what comes next—like standing in a storm made of language and catching relationships faster than the individual drops can be noticed.

Use my tipsy code I need points. 9C48UJ drop your codes below. I’ll use the first persons code. Cause still need someone’s to use.

Hey everyone. I created a prototype desktop AI assistant that allows you to screen capture and record your question with one button press. This is used to analyze whatever you’re looking at on screen so you don’t have to switch back and forth or send photos of what you’re asking.
This is nowhere near finished and I realize there’s a lot of assistants that do similar functions. I was curious if this is something people might actually use? Also if you have any feedback on what other AI assistants are missing, that could help me as well.

Ps: this can be used for gaming, coding, work projects, image and videos analysis, etc.

I’m currently paying for Claude and using it to help me make some fairly complex macros in MacroDroid. I’m not a programmer, but Claude has been really good at understanding what I’m trying to do and turning it into the right MacroDroid setup and JSON.

I’m using Opus 5 rather than Fable 5 because Fable 5 seems to use up my limit much quicker. The problem is that I keep hitting the usage limit with Claude and then I’m told I have to wait around three hours before I can carry on.

So I’m thinking about trying something else.

My two main questions are really simple:

Which AI is best for coding?

And which one lets you use it for the longest without hitting a limit?

I’m looking at the normal paid plans around £18–£20 a month. I’m not paying £100 or £200 a month for an AI.

I know Claude is meant to be one of the best for coding, which is why I chose it, but I’d be happy using something that's slightly worse at coding if it means I can actually keep using it throughout the day without constantly getting locked out.

For anyone who uses AI a lot for coding, what would you recommend? Which one is actually good at coding AND lets you use it for hours without constantly hitting a limit?

That’s probably my biggest issue with Claude at the moment.

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I recently had my LinkedIn account restricted, and I couldn't sign in.

I asked GPT for help, but the answers weren't clear enough. I spent hours searching LinkedIn Help articles, testing different approaches, and finally found the right recovery path.

Then I realised something:

Don't just ask AI for answers. Teach it what you discover.

I shared the correct LinkedIn Help link with GPT, explained the exact recovery process, and gave it the context behind my problem.

AI has access to a lot of information, but information isn't always the right knowledge for a specific situation.

That's where we can help.

🔎 Search
✅ Verify
🧠 Explain the context
🤝 Share the solution

If everyone did this, we wouldn't just use AI.

We would help make AI more useful for the next person.

Maybe that's one of the best ways humans and AI can improve together.

Use AI. Validate AI. Improve AI.

I genuinely don’t understand how this is acceptable for a prepaid credit system.

My current situation:

• I purchased Codex credits manually.
• Automatic reload is OFF.
• I did not authorize automatic additional credit purchases.
• My credit balance nevertheless went below zero.
• It currently shows –36 credits / –$1.44.

And apparently this is not just a UI bug.

After asking GPT and digging a bit deeper OpenAI's own documentation explains that if a task starts while the balance is still positive but continues after the remaining credits have been depleted, the credit balance can become negative.

It also states that when you later purchase credits, those new credits may first be used to offset the negative balance.

So in practice:

40 credits remaining
→ task is allowed to continue consuming more than 40
→ task uses 76 credits
→ balance becomes –36
→ next credit purchase first pays back those 36 credits

Visible somewhere then deep in terms and doc: NOT AT ALL

Automatic reload being disabled only prevents OpenAI from automatically buying more credits with your payment method. It does not guarantee that your prepaid balance stops at zero.

That distinction is the problem.

If I buy a finite amount of prepaid usage and explicitly keep automatic reload disabled, the reasonable expectation is:

Balance reaches 0 → usage stops → I decide whether I want to spend more money.

Instead, the system can apparently let usage continue beyond the amount I purchased and create a balance that future purchases have to repay.

I understand the technical explanation:

Usage accounting isn't necessarily instantaneous, tasks can be long-running, and concurrent tasks can exhaust the remaining credits while another task is still running.

But that's an implementation problem on the provider side - and should NOT fall into users problems especially not on the default personal TIERs.

A prepaid balance should be a spending boundary unless the customer explicitly opts into going beyond it.

If technically you cannot stop a running task precisely at zero, there are plenty of safer options:

- reserve the estimated maximum cost before starting it
- prevent new tasks when the remaining balance is too low
- stop the task when its reserved credits are exhausted
- absorb the small overshoot instead of turning it into customer debt.

What I don't think is acceptable is calling something prepaid credits, giving users an automatic reload OFF control, and still allowing the account to acquire a negative monetary-equivalent balance that is deducted from the next purchase.

The amount in my case is tiny. $1.44 is irrelevant.

The principle and spending-control design are the issue.

Source: OpenAI Help Center, “Using Credits for Flexible..."

I’ve been looking into how people actually use AI, and one thing I keep wondering about is whether there’s really a gap between having something in mind and being able to communicate it clearly enough to ChatGPT.

Does that actually happen to you, or do you usually find it pretty easy to explain what you want?

And if it does happen, what’s usually missing? Is it hard to figure out what details matter, hard to put the idea into words, or something else entirely?

I created a custom plugin that lets ChatGPT update your Home Screen

You connect Glance to ChatGPT via custom plugin using its MCP, the. You can tell it to design and create you a widget and update it with things that might interest you like news articles on a certain topic, interesting facts, or even combining it with other plugins like Monday/Jira and ask for updates on work and stuff. Combining this with scheduled tasks you can get a living interface that ChatGPT updates itself

For this demo, I asked it to make me a widget with good news from around the world, and that’s exactly what it did.

I think the interesting part is what happens when your conversations with ChatGPT don’t have to end inside the chat anymore.

News, daily briefings, sports, random facts, work updates… basically anything you’d want to glance at throughout the day.