Technical Context
I love topics like this because they hit right at the practical core: people argue about manners, and I immediately think about AI automation, latency, and pipeline stability. The reason for this discussion was a thread on X about a simple idea: it's better to be polite with AI. It sounds nice, but in engineering, I only care about one thing: does it actually improve the output or not?
I dug into recent research, and the picture that emerged wasn't romantic but uneven. On older models like GPT-3.5, moderate politeness often did help: the answers were neater, clearer, and sometimes less biased. But with newer systems, including ChatGPT-4o, results have appeared where a direct or even blunt tone showed higher accuracy in tests.
That's where I paused. This means it's not about "politeness" as such, but about which response mode a specific model is triggered into. One stack reads polite phrasing as a signal for a more thorough answer, while another, on the contrary, becomes overly verbose and loses accuracy.
Another important detail: excessive politeness almost always bloats the response. If I'm building an AI integration for support, sales, or internal search, I don't need a stream of "please kindly." I need a predictable format, fewer junk tokens, and proper style control.
So my conclusion is simple: politeness is not a universal hack. It's a prompt framing parameter that needs to be tested just like temperature, system prompt, and output schema. Without measurement, it's just folklore.
What This Means for Business and Automation
If you're having a one-off chat, the difference might be almost unnoticeable. But when I'm putting AI automation into production, small details like the tone of a prompt turn into cost, speed, and error rates.
The winning teams are those who run A/B tests on their prompts, not those who believe advice from social media. The losers are those who hardcode "be as polite and friendly as possible" into their workflow and then wonder about bloated responses, extra tokens, and a drop in accuracy.
At Nahornyi AI Lab, we solve these kinds of issues at a system level, not based on memes about talking to robots. If your AI solution development is hitting a wall with response quality or unstable automation, we can quickly check where the prompt tone is causing problems and build a more reliable system together with Vadym Nahornyi and Nahornyi AI Lab.