Talking to LLMs has improved my thinking (philipotoole.com)

An intriguing perspective has emerged on the relationship between using large language models (LLMs) and cognitive clarity. A developer noted that interacting with LLMs has helped articulate tacit knowledge—insights that professionals often grasp internally but struggle to express. This recognition occurs when LLMs transform vague ideas into precise language, creating "yes, that’s it" moments that enhance the user's cognitive process. Such moments are significant as they reflect the model's ability to map latent structures to clear expressions, allowing users to better inspect and improve their thoughts. The implications of this phenomenon are substantial for the AI/ML community. It highlights a unique utility of LLMs, not just as tools for generating content but as facilitators of cognitive development. By providing a platform where half-formed ideas can be explored rapidly, users can refine their thoughts and develop a clearer internal dialogue over time. This evolving feedback loop improves the interface between thought and language, suggesting that LLMs could play a pivotal role in enhancing reasoning and clarity in various domains, ultimately transforming how individuals articulate and challenge their own intellectual processes.