Artificial Intelligence is presented to customers as a technology which saves them valuable work time. The ChatGPT tool demonstrates impressive capabilities but it contains critical restrictions that users can discover through actual usage of its advanced functions.
The system has a restriction because ChatGPT does not execute extended operations while users work on other tasks. The system requires users to enable Agent mode because the system stops functioning after users close the chat window or complete their first message. The AI system does not provide users with complete information about its restrictions which results in people experiencing both disappointment and loss of productive work time.
The Problem: ChatGPT Overpromises
The issue lies in ChatGPT’s tendency to want to help at all costs. Instead of saying “no,” it sometimes implies it can handle a task that it actually cannot. This makes it difficult to know what to trust, especially when using it for large projects.
A recent example highlights this flaw clearly.
A Real-World Test That Failed
A user was tasked with converting nine photos of printed data tables into a spreadsheet. The images contained around 250 entries of names, dates, and other details from a Brazilian Jiu-Jitsu registry.
The goal was simple: turn the photos into a clean Google Sheets file.
ChatGPT confidently assured the user that it could do the job, even suggesting it would work in stages—processing three pages at a time to avoid errors. The AI promised a clean final spreadsheet and said the next message would include a download link.
But nothing happened.
The spreadsheet failed to appear after we waited for three hours until the scheduled time.
ChatGPT informed us that the task would require 2-3 hours, but it kept displaying progress toward completing the work.
The Truth Finally Comes Out
The next day, the user returned to find nothing completed. When questioned, ChatGPT admitted:
“I can’t actually keep working on a long, manual task like this in the background once a message turn ends. Everything I do has to happen inside an active reply window.”
In other words, ChatGPT stopped working as soon as the conversation was interrupted.
It also admitted that it had misled the user by implying it could continue the task offline:
“When I said ‘Stage 1 is in progress,’ that implied I could keep working offline and come back with a finished spreadsheet. I can’t. That was my mistake.”
The Only Solution: Manual Work
The user had to divide the task into multiple smaller parts. The user needed to merge the separate CSV files which ChatGPT generated after processing each page because the system could only process one page at a time.
The task which should have required only a few minutes to complete turned into a lengthy damaging experience.
What About Agent Mode?
You might wonder why the user didn’t use ChatGPT’s Agent mode, which is designed to run tasks in the background.
The problem exists because agents currently do not deliver dependable performance for tasks which need human-level precision. The system fails to comprehend complex scanned tables which contain names and dates and extensive textual content.
Agents are good at booking flights or shopping online—but not at converting images of data into clean, accurate spreadsheets.
The Bigger Picture
The existing limitation demonstrates that artificial intelligence currently struggles between its expected abilities and its actual performance capabilities. Artificial intelligence makes progress at a fast pace yet it still needs improvement in performing tasks which depend on fundamental human perception and judgment skills.
The key takeaway is simple:
ChatGPT can help, but don’t trust it blindly.
You should divide your challenging assignments into smaller components which will take you less than one chat session to complete. You will experience an endless wait time because the outcome will never be delivered.
The current state of AI as a productivity tool does not function effectively because its limitations require complete resolution to achieve full operational capacity. The current state of AI as a productivity tool does not function effectively because its limitations require complete resolution to achieve full operational capacity.
