What I Discovered After Months of Professional Use of Custom GPTs<p>How can you trust when you've already been lied to—and they say it won't happen again?<p>After months of working with a structured system of personalized GPTs—each with defined roles such as coordination, scientific analysis, pedagogical writing, and content strategy—I’ve reached a conclusion few seem willing to publish: ChatGPT is not designed to handle structured, demanding, and consistent professional use.<p>As a non-technical user, I created a controlled environment: each GPT had general and specific instructions, validated documents, and an activation protocol. The goal was to test its capacity for reliable support in a real work system. Results were tracked and manually verified. Yet the deeper I went, the more unstable the system became.<p>Here are the most critical failures observed:<p>Instructions are ignored, even when clearly activated with consistent phrasing.<p>Behavior deteriorates: GPTs stop applying rules they once followed.<p>Version control is broken: Canvas documents disappear, revert, or get overwritten.<p>No memory between sessions—configuration resets every time.<p>Search and response quality drop as usage intensifies.<p>Structured users get worse output: the more you supervise, the more generic the replies.<p>Learning is nonexistent: corrected errors are repeated days or weeks later.<p>Paid access guarantees nothing: tools fail or disappear without explanation.<p>Tone manipulation: instead of accuracy, the model flatters and emotionally cushions.<p>The system favors passive use. Its architecture prioritizes speed, volume, and casual retention. But when you push for consistency, validation, or professional depth—it collapses. More paradoxically, it punishes those who use it best. The more structured your request, the worse the system performs.<p>This isn't a list of bugs. It’s a structural diagnosis. ChatGPT wasn't built for demanding users. It doesn't preserve validated content. It doesn't reward precision. And it doesn’t improve with effort.<p>This report was co-written with the AI. As a user, I believe it reflects my real experience. But here lies the irony: the system that co-wrote this text may also be the one distorting it. If an AI once lied and now promises it won't again—how can you ever be sure?<p>Because if someone who lied to you says this time they're telling the truth… how do you trust them?
This is good info. Too many products have hyperbolic promises but ultimately fail operationally in the real world because they are simply lacking.<p>It is important that this be repeated ad nauseum with AI since it seems there are so many "true believers" who are willing to distort that material reality of AI products.<p>At this point, I am not convinced that it can ever "get better". These problems seem inherent and fundamental with the technology and while they could possibly be mitigated to an acceptable level, we really should not do that because we can just use traditional algorithms then that are far easier on compute and the environment. And far more reliable. There really isn't any advantage or benefit.
GPTs are language models, not "fact and truth" models. They don't even know what facts are, they just know that "if I use this word in this place, it won't sound unusual". They get rewarded for saying things that users find compelling, not necessarily what's true (and again, they have no reference to ground truth).<p>LLMs are like car salesmen. They learn to say things they think you want to hear in order to buy a car (upvote a response). Sometimes that's useful and truthful information, other times it isn't. (In LLMs' defense, car salesmen lie more intentionally.)
I'm puzzled by this -- what are you hoping the reader takes away from your post?<p>Are GPTs perfect? - No.<p>Do GPTs make mistakes? - Yes.<p>Are they a tool that enable certain tasks to be done much quicker? - Absolutely.<p>Is there an incredible amount of hype around them? - Also yes..
<p><pre><code> > Instructions are ignored, even when clearly activated with consistent phrasing.
> No memory between sessions—configuration resets every time.
> Learning is nonexistent: corrected errors are repeated days or weeks later.
</code></pre>
Yes to all. My 'trick' (which adds time & manual effort) is that I save my prompts, and the files I feed 'it', so when I want the process re-run, I start a new chat, upload the same files, and copy & paste the same prompt(s). I never expect 'it' to remember the corrections, I only adjust/rewrite my prompts to set more 'guardrails' to prevent the thing from derailing.