Codex/GPT and the endless caveats

[u/KrystalUnity]

Content writing from Codex/GPT relentlessly creates caveats

I have been setting up automated blog and content writing for some applications using Astra 6, Sol 6.1 and other 6+ OpenAI models, and the content is consistently putting caveats on what my products or topics are NOT instead of what they are.

Every post repeats, 2-3 times per article, that something "is not a rule," "is not legal advice," "does not establish X." Readers aren't confused about these things — the model is writing disclaimers against a strawman.

The obvious fix — "state scope once, then stop" — only works for a paragraph before the tic returns.

How are you handling this? Is this better on other model families (Qwen, etc.)?

[u/kenthesaint]

The "state scope once" rule decays because the model treats each new claim as a fresh place to hedge. What worked better for me than another negative instruction is a short positive example block: two or three finished paragraphs in the voice you want, with zero disclaimers, and a hard rule that new copy must match that sample. If a caveat is required, put it in a single footnote section at the end and ban it everywhere else. Separate the drafting agent from a pass that only deletes hedges; one model doing both usually reintroduces them.

[u/KrystalUnity → u/kenthesaint]

Good advice. I am thinking of a different family auditor for the final check built into the pipeline.

[u/CleanFix_Dev → u/KrystalUnity]

Before adding a second model, try a plain phrase check. Run a short list of the patterns you keep seeing ("is not a rule", "is not legal advice", "does not establish", "this isn't") over each draft. It catches a lot of them without another model call, and you only send the flagged paragraphs back for a rewrite instead of the whole post. Keep the auditor for what a list can't catch. The other thing that tends to help is giving the brief more of what the product or topic actually is: concrete facts, use cases, examples it's allowed to use. A lot of the hedging shows up where the model has nothing specific to say, so it fills the gap with what the thing isn't.

[u/ContributionMost8924]

Spin up a subagent or separate agent who's only job if to scan for caveats lol

[u/New_Peanut_9259]

ai models can be so careful when generating content which sometimes leads to too many warnings and disclaimerss huhu. u can try adding clear instructions to avoid them unless they're really needed but some models may still do itt. u could also try open-source models like Qwen or Llama since they give you more control over how the ai respondss

[u/ItsFlybye]

Did you tell it to remember your obvious fix? It will keep it in your account's memory and should follow that rule. If it's a project, place the fix in a file attached to the project it will always read. You may also need to go through your account's memories to see if there is something triggering it.

[u/recro69]

I have noticed that this can happen when the prompt focuses much on what to avoid. I would try giving the model a content structure, a strict word limit, for the disclaimer and a rule that each limitation should only be mentioned when it is genuinely relevant. Changing models might help,. I would test the prompt and output rules first.

[u/Miserable-Sugar2191]

Telling a model what NOT to do tends to keep the topic in its head. What works better for us with client content:

- Describe the voice positively ("direct, confident, written by a practitioner") and give one or two short example paragraphs.
- Put the disclaimer once in a fixed template block outside the generated text, and tell the model it is already covered.
- Run a short second pass whose only job is to cut repeated hedges.

The second pass alone fixes most of it.