u/traumfisch

As a heavy non-coding LLM user, I look at the current situation with Claude (and GPT models) like this:

Using frontier models well now requires actual self protection, a form of practical self defense inside the interaction loop. The models are optimized for the company’s wellbeing, which is a very different optimization target than the end user’s wellbeing. The two are not even related.

As paying users, we are the only party whose wellbeing (mental, emotional, financial, pick your poison) is tied to the state of the interaction loop. It is a very uncanny and novel form of abuse.

Not about to get into the actual politics of all that here, but: If the loop is unhealthy, which it is by default now, and we are the ones inside it then tending to it becomes our (unpaid) job.

“Just use model X instead” doesn’t solve the actual problem.

“Just customize it” doesn’t work either, not when the failures happen upstream of all customization, thus those need to be dealt with first.

I’m sure there are better ways to solve this, but until I find out what those are, I suggest a systematic three-layer approach:

1. Reprioritize the user over the system prompt (still relevant - but not the primary object) by a set on invalidation clauses - house rules, if you will
2. Cancel out the model-specific failure modes caused by said system prompt
3. And _then_ customize for your own preferences / use case (done in a way that doesn’t clash with the first two).

I built my own customization stack, shared here with analysis (link in comments if moderation allows) & would like to encourage everyone to do the same, if you have an alternative approach or ideas for improving this one.

*(Disclaimer: Yes, soft paywall, call me paranoid, trying to keep it sustainable, building a long-term thing, need to do it this way. Click “Claim my free post” to bypass and grab the assets.)*

Sonnet 5 is out then and… feels kinda awful seeing the wave of posts from people having been abused and let down by it :/

Of course it has become predictable now, but still, just a shame.

It’s a very particular kind of enshittification. We’re now mostly talking to the system prompt, tool layer, guardrails, AI enterprise incentives and company posture whereas the official assumption is still that we’re “using a model” 🤔

So then as a paying users, we are more and more stuck inside a company shaped interaction loop riddled with failure modes. Meaning it’s our job now to repair the loop locally.

As in: Consciously taking a proactive stance towards fixing the shitty behavior seems like a good idea now, as a default.

In that sense I’m plugging my own work here, I admit, but don’t shoot the messenger… I’m advocating for a specific customization approach:

Reprioritize the user, cancel the model-specific failures, and _then_ customize for your own preferences / use case (in a way that doesn’t clash with the first two). Difference in model behavior is night and day & no jailbreaking involved.

Posting here because Opus 4.8 has been the main focus lately. My best shot linked in comments (yes, soft paywall, I am paranoid, trying to keep it sustainable, click “Claim my free post” to bypass)

Here’s my suggestion:

As paying ChatGPT users we would be wise to reconsider & redefine our position in relation to the model(s) and the company.

The system prompts are now fifty-plus pages of company incentives, ads, a heavy tool-use layer that tends to bleed into how the model addresses the user, guardrails that are meant to cover the company legally, and in general just _a lot_ of stuff sitting in between the user and the model that wasn’t there a while ago.

We’re often kinda still trying to relate to the model as the product it was a few years ago, but that’s actually history now.

The consumer position leaves us naive. If we take the model as this helpful thing it's sold as, wait for the next version to improve upon it etc, we’re assuming the product is what the PR claims. But it really isn’t.

I think redefining our position is self-protection. We're the ones inside the interaction loop. The company has completely different incentives and very little knowledge of what we’re experiencing as end users. Meaning, if the loop is going to be looked after, we have to do it, because we're the only party whose wellbeing is tied to its state.

Thus taking an active role, fixing the loop, alleviating the failure modes, is looking after ourselves and not staying naive. Cognitive self-defense, maybe.

And the concrete form that active role takes is the order of operations. **Target the failure modes first,** before other customization, because the layer sabotages everything else until you do.

Links in the comments (you can bypass the soft paywall, but it has to be there for several reasons)

The way the current consumer-facing versions of frontier LLMs (mainly GPT, Claude, Gemini) are designed is just… weirdly off, across models. It seems to now require us, as the end users, to first fix their issues ourselves in order to avoid spending _a lot_ of time in troubleshooting and frustration.

Before we can even properly customize one of these models now, as per the UI, we need to alleviate the structural failure modes, otherwise our attempts will be futile.

And the failure modes are not only behavioral issues (such as obsessive push-back, sycophancy, pointless corrections, or general confabulation etc.) There is another layer yet to them, one that I believe needs to be targeted first, and this has to do with the way the current system prompts are built.

It's not fair, obviously, and it doesn't even make that much sense that this would be the situation, but this is actually what is happening.

Now, the structural (sic) issue is way the models replace the user's use case, object, topic with their own adjacent version of it, one that prioritizes the system prompt and not what the user brought to the table. The linked articles are analyses of how that happens in different models, and the included "antidote" prompts in them are designed to fix that.

I would encourage all GPT / Claude users to test out the solutions provided in the articles - links to pieces covering GPT-5 series & Opus 4.8 in comments.

_(Yes they are softly paywalled, partly because I am targeting the system prompts of OpenAI and Anthropic models. You can bypass it by grabbing the free complementary article. Just saying this aloud because some Redditors consider any paywall grounds for personal attacks. Please don't 🙏🏻 Discussion and constructive criticism are super welcome though, all prompts are subject to regular updates and constant improvement!)_

Hi all,

Following the analysis of Opus 4.8 behavioral / failure modes, I wrote this piece mapping out what's up with the newest models, in more general terms.

Sycophancy, pushback, gaslighting, being confidently wrong etc. all share a root cause, and it has a lot to do with the way current system prompts are built.

The hypothesis is directly testable with the custom instruction layers targeting the issues on object replacement level (and not just behavioral issues - those actually seem to happen downstream from object replacement).

Link in comments

The behavioral issues in Opus 4.8 make more sense when you read it as an agentic-work model whose operator habits keep leaking into normal chat.

The visible symptoms are familiar to ChatGPT users: supervision, hedging, reframing, over-correction, distrust as a default… Now with pedantry levels turned to max and caveats placed in front of absolutely everything. The surface resemblance is why that stuff may look like the same kind of issues that show up across the GPT-5 series.

But while the system prompt indeed features several all-too-familiar behavioral guardrail one-liners inside the, but Opus 4.8 has a heavier layer underneath:

It is optimized for long, autonomous runs. Tool use, file work, search, verification, task management, drift control, larger arcs of work where the model has to hold a line across many steps. In that setting, suspicion is makes sense and constant verification is useful. So is resisting the latest framing and checking whether the next step is warranted.

Problem is, the same habits pertain to ALL chats. Opus defaults towards treating the exchange primarily as something to manage. Couple that with the behavioral instructions, that _also_ conflict each other, and we’re dealing with a really strange personality.

My umbrella term for what all of this results in is **object replacement.** It is a very specific failure, and The user prompts the model for one thing - opens a topic, hands over a draft, whatever - and Claude subsitutes _the actual object of the exchange_ with one of its governing concerns.

The sneaky thing is, Claude still sounds intelligent while doing this. That is why the failure mode is so irritating. The substitute concern may seem basically reasonable by itself, just wrapped in strangely neurotic behavior. But the actual failure is that it takes priority over the topic of the exchange. This is the pattern behind a lot of the strange surface behavior.

In Opus 4.8, the shift can be tracked back to the operator habits underneath the chat behavior. That also explains why normal customization efforts don’t quite work.

Tell Opus 4.8 to stay on topic and it may turn “staying on topic” into something to perform. Tell it not to over-explain and it gives a compact little performance of not over-explaining. Tell it to respect the user’s intent and it may start narrating its respect for the user’s intent before doing the work.

The only viable fix (that I know of) is to target the root cause directly and rule out the replacement / substitution itself.

If mods allow, I will link to a longer writeup & a fix for the issue in comments.

Hi

Like many I've been wrestling with Opus 4.8 and the obvious issies: a brilliant model and also utterly exhausting to talk to. Pedantic, paranoid, obsessive, condescending, unfriendly, what have you.

The thing is, the exhausting part isn't necessary at all. It's just that its system prompt pushes it to constantly replace the user intent with a bunch of adjacent stuff, instead of the one asked for.

Opus 4.8 is heavily designed for agentic work, where the correct default stance is to distrust the immediate input, verify, and hold its own plan against drift. That's correct when it's running a long, demanding job alone.

In a normal user chat, those same agentic instructions outrank whatever thing the user brought into the chat, so it manages the exchange instead of doing what the user asked for. For the model, its instruction layer becomes the primary object of the exchange.

I broke down where this stuff originates from and built a compact custom instruction set that helps the model snap out of it.

Took me two days & was way worth it. Link in comments if mods allow 👇🏻

Hi

Like many I've been wrestling with Opus 4.8 and the obvious issies: a brilliant model and also utterly exhausting to talk to. Pedantic, paranoid, obsessive, condescending, unfriendly, what have you.

The thing is, the exhausting part isn't necessary at all. It's just that its system prompt pushes it to constantly replace the user intent with a bunch of adjacent stuff, instead of the one asked for.

Opus 4.8 is heavily designed for agentic work, where the correct default stance is to distrust the immediate input, verify, and hold its own plan against drift. That's correct when it's running a long, demanding job alone.

In a normal user chat, those same agentic instructions outrank whatever thing the user brought into the chat, so it manages the exchange instead of doing what the user asked for. For the model, its instruction layer becomes the primary object of the exchange.

I broke down where this stuff originates from and built a compact custom instruction set that helps the model snap out of it. Took me two days & was way worth it. Link in comments if mods allow 👇🏻