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The Coherence Trap: Why LLMs Feel Smart (But Aren't Thinking) - Travis Frisinger
Original: The Coherence Trap: Why LLMs Feel Smart (But Aren’t Thinking) - Travis Frisinger
Takeaway
LLMs feel intelligent because of coherence, not understanding — engineers should design and evaluate around that illusion rather than be fooled by it.
Summary
- Travis Frisinger argues GPT-3.5 felt brittle, but GPT-4's coherence triggered an 'uncanny' sense of understanding — pulling in Microsoft's 'Sparks of AGI' paper and Ethan Mollick's writing.
- Coins 'the coherence trap' to describe how surface fluency creates an illusion of comprehension without intent or desire.
- Documents experiments and livestreams probing where coherence collapses — prompt sensitivity, edge cases, and out-of-distribution reasoning.
- Proposes a theoretical frame: LLMs operate in a middle space between dumb chatbots and AGI that better engineering practice should respect.
llm-appsprompt-engineeringcognition
Original description
Why AI engineers must rethink what intelligence means in the age of large language models. LLMs aren’t thinking. No awareness. No reasoning. No plan. And yet—they feel smart. Shockingly so. This talk introduces coherence reconstruction, a mental model that explains why LLMs are so useful despite their lack of true understanding. You’ll learn how they generate meaning through latent coherence—a kind of internal gravity that pulls language into alignment with context. We’ll break down: + Why hallucinations happen—and why you can’t fully eliminate them. + How prompts act like force vectors, shaping behavior in structured ways. + What this all means for reasoning tasks, evaluation practices, and agent design. If you’re building tools, agents, or workflows with LLMs, this talk will reframe how you think about reliability, cognition, and what "understanding" even means. 🔗 Additional resources: Blog: https://aibuddy.software/ AI Decision Loop Paper: https://aibuddy.software/papers/2500_chatgpt_conversations_case_study.pdf AI Decision Loop Git Repo: https://github.com/T-rav/gpt-chat-analysis AI Coherence Paper: https://aibuddy.software/papers/AI_Coherence_A_Theory_of_Utility_in_Large_Language_Models.pdf Cat Metal Album: https://www.youtube.com/watch?v=gdV5l0JvdNo&list=PL0X82GOpevvYfPLM-JibRJEizHqCJ6U4H&index=7