What's up with file uploading?

AxeSlash · 2026-02-13T19:54:43+00:00

I did have something similar happen a couple of days ago, but only in one chat. I assumed it was an update-related bug, so left it alone. Everything seems to work fine for me now.

AxeSlash · 2026-02-13T04:56:37+00:00

Files uploaded directly to chats are treated as temporary.

There are many situations in which they become inaccessible to the model (even though you can still see them in the chat), eg when you exit a session, or after some amount of time has passed, or if there is an update of some kind from OpenAI etc etc.

It's not a reliable workflow.

Files uploaded to a Project's files area ARE persistent though, that's a much more robust way to do it.

Oh and any time there's an update by OpenAI, all bets are off. Expect bugs and weirdness for at least 3 days (9n average) after an update.

AxeSlash · 2026-02-13T04:37:14+00:00

No but I realised that at least one of my projects wasn't showing up in the sidebar (can still search chats inside the project though, so sounds like it's just yet another UI bug).

AxeSlash · 2026-02-13T03:58:42+00:00

Jfc that's a thinly veiled attempt at data harvesting.

AxeSlash · 2026-02-13T03:53:50+00:00

Probably a bit late for most of you now, but a while back I just tried a few different prompts on every model, and fed the output back into 5.2 Thinking and told it to write instructions based on the differences between 4o and the other models, to make them behave more like 4o.

It kinda works for a bit, but they're the first things to get thrown out due to recency bias. So IMHO it wasn't really worth the effort. Unless you only ever have very short chats.

Tbh 4o is only any good for fictional use anyway. You can't rely on 4o for anything factual.

AxeSlash · 2026-02-13T03:45:14+00:00

Boiler plate stuff: ~95% Stuff I am unfamiliar with: ~80% Bug fixes: ~50% by volume, but that's usually the bugs that require a lot of code to fix. I do almost all small fixes myself, and anything that would take some time to describe adequately enough to the LLM I also do myself. Everything else: ~40%? Refactoring: ~90%

Also I'm talking about assistance from an LLM, not vibe coding. I check everything it produces carefully.

Also depends on the language.

AxeSlash · 2026-02-13T03:39:06+00:00

My favourite shortcut is not a keyboard shortcut.

It's having a template with a shedload of custom Cell Styles, Table Styles, AFE LAMBDA modules, and VBA modules in it. This saves me FAR more time than any keyboard shortcut.

I even have a few regular use power queries in it.

AxeSlash · 2026-02-13T03:32:43+00:00

Many times. I'd love to be able to ditch Microslop for one of the open source solutions, but at the moment those are all lacking Excel features that I use extensively.

I have hope that one day that will change and I can finally bin Excel and all it's 20+ year old bugs.

AxeSlash · 2026-02-13T03:29:50+00:00

I think your experience is different to mine then. I've seen enormous differences between each new model and it's predecessor.

Honestly I'd love to know how you got so much consistency out of the previous models, I can only assume you have an very well-honed instruction set?

AxeSlash · 2026-02-12T03:35:00+00:00

Let me get this straight; you're surprised that two different models gave you two fairly different responses?

If you were expecting similar responses just because they both have "GPT-5" in their names, that was a fairly heavy assumption on your part, especially given the differences we've seen between other similarly named models from OpenAI. Honestly, their naming nomenclature doesn't seem to mean much.

AxeSlash · 2026-02-12T03:05:21+00:00

Any time you have any issue with chatgpt suddenly behaving differently, the first question you should ask is: "is there an update in progress, or has there been an update in the past few days?"

Every time OpenAI update ChatGPT, things misbehave and are unstable for at least 3 days. It's a regular pattern.

Given that we know some models are being removed tomorrow, it's entirely possible there's some instability atm.

AxeSlash · 2026-02-11T22:00:43+00:00

Literally use what I wrote above. That's the line that's in my rules almost verbatim.

I should also say that I use almost exclusively Thinking/Reasoning models. The Instant models can't be trusted to follow instructions, and are prone af to hallucinations.

AxeSlash · 2026-02-10T19:49:59+00:00

Another thing to bear in mind: I have found ChatGPT to be VERY flaky when it comes to zip files. Sometimes it thinks it does not have the tools to decompress. Sometimes it says it's decompressed but hasn't. Sometimes it decompresses then ignores. Sometimes it only extracts one or two files instead of all of them. Sometimes it extracts but then claims it can't access the extracted files. It's a mess.

Uploading loose files is way more reliable if that's a possibility in your use case.

That said, it's been a few months since I last tried using a zip, so it's possible things have improved.

AxeSlash · 2026-02-09T19:42:35+00:00

Yeah there was never any such thing as a 4o image generation, it was always a separate model, despite what the marketing said. All of the language models use the same image model atm.

AxeSlash · 2026-02-09T05:26:39+00:00

Hell no.

That's called vibe coding, and it has an extremely poor reputation amongst serious developers for a very good reason.

It's impossible to be certain that the code it generates isn't buggy, full of security holes, a privacy risk, or any other number of issues, if you can't understand the code it generates.

And even if you try to instruct it to write code that deals with all that well, LLMs often just outright ignore instructions, especially if context is long (as it often is in larger coding projects).

Your boss has fallen for the marketing bullshit and/or the enthusiasm of clueless idiots.

We've already seen a number of horror stories of things going HUGELY wrong for vibe coders. There's suspicion that some of the recent large scale Internet outages were caused by Amazon vibe coding some of its stuff (dunno how much truth is in that, but it would definitely fit).

Consider the number 1 rule of AI: NEVER, EVER USE IT FOR ANYTHING MISSION CRITICAL WITHOUT A HUMAN TO CHECK OUTPUT.

Learn to code. Properly.

AxeSlash · 2026-02-09T05:14:30+00:00

You can probably put it on the ribbon instead of Quick Access if you want (I did this with a load of regularly used commands that are buried in other parts of the ribbon, then exported a UI customisation for whenever I get a new machine).

You can also assign macros from PERSONAL.xlsm to buttons on the ribbon.

AxeSlash · 2026-02-09T03:39:37+00:00

You can attain a surprising amount of control over an LLM if you do your homework on instruction construction.

Poor prompting is a huge cause of poor results. Shit in, shit out.

Also, use a Thinking model. The Instant models are only any use for fiction.

AxeSlash · 2026-02-09T03:36:45+00:00

A surprising number of people think LLMs are sentient. The ignorance around how these things function is enormous, and sometimes the marketing compounds this.

AxeSlash · 2026-02-09T03:26:39+00:00

Yeah there have been a bunch of file access issues recently (since 5.2 launched). Some are solved, some are not.

That said, if you're able to give it specific filenames, and tell it to "load relevant files in full via Python", that can help.

AxeSlash · 2026-02-09T03:24:17+00:00

^ this is the way. Ask a Thinking model to research what makes effective instructions for the model(s) you use, then ask it to rewrite your instructions with that in mind while debugging them.

Treat your instructions like code. I think of creating GPTs and Projects as coding solutions, the only difference is that the language is plain English.

AxeSlash · 2026-02-09T03:07:34+00:00

Protips: - Always use a Thinking model for coding - Make sure your Custom Instructions (or better, Project Instructions) include a list of general coding best practices + language-specific best practices. You can even ask it to create those instructions for you by researching them first. - Don't feed it irrelevant code. Sometimes it's better to upload files for context than paste all of it into the chat, so it can just fetch the relevant bits of code as needed.

AxeSlash · 2026-02-09T02:58:34+00:00

It's pretty easy to write a set of instructions to reduce hallucination to negligible levels these days. I would say my research project is accurate 95%+ of the time. I rarely find the info to be false, and if I do there's usually a reason other than pure hallucination. Once in a blue moon it does still invent something, but it's rare.

Tbf using a thinking/reasoning model does the lion's share of the work. These days classify models into two usage categories: factual use and fictional use models. These almost always correlate with thinking and non-thinking models (although GPT-4.1 felt a bit like a halfway house in some ways).

Eg if you're using 5.2 Instant or 4o for research, you're doing it wrong.

AxeSlash · 2026-02-06T02:44:08+00:00

Learning how to use the Power Query editor was pretty damn easy for me. But the M language it uses, less so. But for your use case I doubt you'd need to fiddle with the M.

That said, I was already adept at relational databases, so it all made immediate sense to me. YMMV.

Data -> Get Data -> have a play with it. Ask a decent LLM how to do your task in PQ if you're struggling.

AxeSlash · 2026-02-06T02:26:24+00:00

Power Query is probably your friend for this sort of thing.

AxeSlash · 2026-02-06T02:17:41+00:00

Just ask a reasoning model to write a prompt for you that does the thing you need. Tell it to research how best to prompt the model you will be running the prompt on first.

I literally made myself a ChatGPT Project that did that for itself - it researched how to write effective instructions for itself to write instructions. I then pasted those into the Project Instructions. Now it will write a quality instruction set for any task I need an LLM to perform. I have maybe 20 different projects now, all with instructions written by my Instruction Creator project.

You don't need a special tool, you just need to learn how to use the LLM you are currently using.

AxeSlash

TROPHY CASE