>GPT‑5.1 Thinking’s responses are also clearer, with less jargon and fewer undefined terms
Oh yeah that's what I want when asking a technical question! Please talk down to me, call a spade an earth-pokey-stick and don't ever use a phrase or concept I don't know because when I come face-to-face with something I don't know yet I feel deep insecurity and dread instead of seeing an opportunity to learn!
But I assume their data shows that this is exactly how their core target audience works.
In defense of OpenAI in this particular situation, GPT 5 can be incredibly jargon-y at times, making it much worse of a learning tool than other LLMs. Here's some response snippets from me asking a question about dual-stack networking:
> Get an IPv6 allocation from your RIR and IPv6 transit/peering. Run IPv6 BGP with upstreams and in your core (OSPFv3/IS-IS + iBGP).
> Enable IPv6 on your access/BNG/BRAS/CMTS and aggregation. Support PPPoE or IPoE for IPv6 just like IPv4.
> Security and ops: permit ICMPv6, implement BCP38/uRPF, RA/DHCPv6 Guard on access ports, filter IPv6 bogons, update monitoring/flow logs for IPv6.
Speaking like a networking pro makes sense if you're talking to another pro, but it wasn't offering any explanations with this stuff, just diving deep right away. Other LLMs conveyed the same info in a more digestible way.
Probably not as much as people who heavily lean on their tribes lingo want to believe, but yes. I think we would prefer an AI that is fantastic as understanding what we know. If it's not, it costs time either way — which is not great, either way.
I always wonder how useful such explanations could be. If you don’t know (or can’t guess) what ICMPv6 is (and how much would knowing it stands for “Internet Control Message Protocol version 6” help?), perhaps you asked the wrong question or, yes, you’re dangerously out of your depth and shouldn’t be trying to implement a networking stack without doing some more research.
I have added a ”language-and-tone.md” in my coding agents docs to make them use less unnecessary jargon and filler words. For me this change sounds good, I like my token count low and my agents language short and succinct. I get what you mean, but I think ai text is often overfilled with filler jargon.
Example from my file:
### Mistake: Using industry jargon unnecessarily
*Bad:*
> Leverages containerization technology to facilitate isolated execution environments
Oh yeah that's what I want when asking a technical question! Please talk down to me, call a spade an earth-pokey-stick and don't ever use a phrase or concept I don't know because when I come face-to-face with something I don't know yet I feel deep insecurity and dread instead of seeing an opportunity to learn!
But I assume their data shows that this is exactly how their core target audience works.
Better instruction-following sounds lovely though.