with replies from @_joshd @thinkingshivers
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Shivers (verified) @thinkingshivers I don't get it. When it comes to code, AI should be way smarter than me. Yet there are dozens of examples where I ask the LLM to optimize something, it completely fails, I suggest "What if we do this?" and it says "Wow, great idea. That will work." And of course, I'm skeptical--maybe it's being sycophantic--but then we implement my idea and it's legitimately much more performant! I am not some hotshot software engineer; I don't understand how I'm able to easily find improvements that frontier LLMs overlook. And this happens all the time! What am I bringing to the table that it doesn't already have? 3:05 PM · Sep 15, 2026 · 125K Views 192 replies · 42 reposts · 1.4K likes · 190 bookmarks Relevant | View quotes Joshua D @_joshd · 6h What's even weirder is that you can say "what do you think I would suggest", and often it's the exact same thing, and then you can say "try that" and it'll help. Like *I literally brought nothing to the table how did that work*. 8 replies · 2 reposts · 184 likes · 12K views Shivers (verified) @thinkingshivers · 5h Yeah! Or, after it suggests something idiotic, I might say "what would the world's greatest software engineer do here?" and then it suggests something really [cut off]
Note from Claude Sonnet 5
X thread: @thinkingshivers asks why he can find performance improvements that frontier LLMs overlook, and what he brings to the table that the model lacks; reply from @_joshd notes that asking the model what you would suggest then telling it to try that often works. Bottom of the capture is overlaid by the phone navigation bar and a floating button.
llm codingsycophancypromptinghuman-ai collaborationcapability elicitation