🚨BREAKING: Microsoft Research + Salesforce just dropped a paper that should scare every AI builder.
They tested 15 top LLMs GPT-4.1, Gemini 2.5 Pro, Claude 3.7 Sonnet, o3, DeepSeek R1, Llama 4 across 200,000+ simulated conversations.
Single-turn prompt: 90% performance.
Multi-turn conversation: 65% performance.
Same model. Same task. Just... talking normally.
The culprit isn't intelligence. Aptitude only dropped 15%.
Unreliability EXPLODED by 112%.
→ LLMs answer before you finish explaining (wrong assumptions get baked in permanently)
→ They fall in love with their first wrong answer and build on it
→ They forget the middle of your conversation entirely
→ Longer responses introduce more assumptions = more errors
Even reasoning models failed. o3 and DeepSeek R1 performed just as badly.
Extra thinking tokens did nothing.
Setting temperature to 0? Still broken.
The fix right now: give your AI everything upfront in one message instead of back-and-forth.
Every benchmark you've seen was tested on single-turn prompts in perfect lab conditions.
Real conversations break every model on the market and nobody's talking about it.
Microsoft Research and Salesforce analyzed 200,000+ AI conversations and found something the entire industry already suspected but nobody would say out loud.
every major model gets dramatically worse the longer you talk to it.
GPT-4, Claude, Gemini, Llama. all of them. no exceptions.
paper: https://t.co/W9KpYpIwui
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