The AI Daily Brief: Artificial Intelligence News and Analysis
5 Prompting Tricks to Make Your AI Less Average
19 Oct 2025
AI is trained on the sum total of human output—which means it often produces the average of averages. That’s fine for passable results, but not for unique, high-quality work. In this weekend big think episode, NLW explores what he calls AI’s tyranny of the average and shares five techniques to break through it: using negative style guides, forcing divergence and choice, burning down clichés, prompting self-critique, and leveraging examples that defy consensus. Based on an essay by Alex Kantrowitz, this is a practical guide for anyone who wants their AI outputs to stand out rather than blend in.AI Sameness Essay: https://www.bigtechnology.com/p/ais-sameness-problemBrought to you by:Is your enterprise ready for the future of agentic AI?Visit AGNTCY.orgVisit Outshift Internet of AgentsGoogle Gemini - Try NotebookLM today https://notebooklm.google.com/KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. https://www.kpmg.us/AIpodcastsBlitzy.com - Go to https://blitzy.com/ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? [email protected]
Full Episode
Today on the AI Daily Brief, how to make your LLM not average. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, Super Intelligent, Robots and Pencils, Notion and Blitzy.
To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe on Apple Podcasts. And to learn about sponsorship opportunities, shoot us a note at sponsors at ai-dailybrief.ai. All right, so today's episode is something I've been thinking about for a while. In my head, I've always called it AI's tyranny of the average.
And the simple notion here is that because AI has been trained across the entire corpus of everything that humans have output, almost by definition, it is optimized around average conventional wisdom. Sometimes that's fine. What that does is that it ensures that the output of an LLM has a fairly high floor.
If it produces passable content, passable writing, passable imagery, based on how you prompted it, that's good, right? At least it gets you in the zone. The problem is that increasingly, when it comes to production use cases and using AI for things that really matters, average isn't good enough. We want more than average. We want unique. We want distinct. We want really high quality.
And for this, we have to turn to some prompting strategies, five of which I'm going to share today, that I have found help me in the ways that I use LLMs to make them excel ahead of that average output.
Now, one of the reasons that I thought this would be a good fit for the Weekend Big Thinks slash Long Reads episode is that technology writer Alex Kantrowitz actually dropped a little quick essay on his blog, BigTechnology.com, this week that's pretty much about this. He called it AI Sameness Problem... And it's short, so we'll read it quickly and this will be me reading, not AI.
For better or worse, you guys have sent the message clearly that as good as AI voice technology is, you prefer me reading it and that's fine. But we'll read Alex's essay and then we'll talk about these five techniques that I have found to work for overcoming the problem of AI's averageness. Again, his essay is called AI's Sameness Problem and it reads...
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