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How Talking to LLMs Can Improve Your Thinking
Technology

How Talking to LLMs Can Improve Your Thinking

Hacker News1d ago
3 min read
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Key Facts

  • ✓ Developer Philip O'Toole has documented his personal experience of using Large Language Models to enhance his own cognitive processes.
  • ✓ The practice involves iterative, conversational dialogue with AI rather than simple query-and-response interactions.
  • ✓ This method has proven effective in breaking through mental blocks and solving complex technical problems.
  • ✓ The approach has also yielded benefits in creative endeavors by providing novel perspectives and ideas.
  • ✓ The experience suggests a shift in how AI can be used as a tool for intellectual augmentation rather than mere task automation.

In This Article

  1. A Surprising Cognitive Partner
  2. The Art of AI Conversation
  3. Enhanced Problem-Solving
  4. A New Dimension for Creativity
  5. The Human-AI Synergy
  6. Key Takeaways

A Surprising Cognitive Partner#

In an era where artificial intelligence is often viewed through the lens of automation and job displacement, one developer has uncovered a more personal and profound benefit. Philip O'Toole has found that his regular interactions with Large Language Models (LLMs) have done more than just streamline his workflow—they have actively improved his own thinking.

This revelation emerged not from a formal study, but from his personal experience as a technologist. By treating LLMs as conversational partners rather than mere query engines, he discovered a new dynamic in how he processes information, solves problems, and generates ideas. The result is a compelling case for viewing AI as a tool for cognitive augmentation.

The Art of AI Conversation#

The core of this transformative practice lies in the method of engagement. Instead of asking a single, definitive question and accepting the first answer, the process involves a continuous, iterative dialogue. This approach turns a simple query into a structured exploration of a topic.

By articulating his thoughts to an LLM, he is forced to structure his own reasoning. The model's responses, in turn, provide new angles, challenge assumptions, or fill in knowledge gaps. This creates a feedback loop that refines the original idea.

The key elements of this conversational method include:

  • Using the LLM as a sounding board for half-formed ideas
  • Asking for multiple perspectives on a single problem
  • Requesting explanations of complex concepts in different ways
  • Iteratively refining questions based on previous answers

This active, engaged style of interaction stands in stark contrast to passive information consumption. It requires the user to be a co-pilot in the thinking process, not just a passenger.

"It forces me to articulate the problem with a clarity that I might not have achieved on my own."

— Philip O'Toole, Developer

Enhanced Problem-Solving#

The most tangible benefit observed is a marked improvement in problem-solving capabilities. Complex technical challenges, which might have previously led to prolonged periods of stagnation, now have a new pathway for resolution. The LLM acts as a catalyst for breaking through mental blocks.

For instance, when faced with a difficult coding problem, the conversation can shift from a direct search for a solution to a deeper discussion about the underlying principles. This often reveals more elegant or efficient approaches that would not have been immediately obvious.

It forces me to articulate the problem with a clarity that I might not have achieved on my own.

The process of explaining a problem to an LLM often illuminates the fuzzy parts of one's own understanding. This act of externalization is a powerful tool for identifying the true root of a challenge, leading to more robust and well-considered solutions.

A New Dimension for Creativity#

Beyond logic and code, this conversational method has also unlocked new avenues for creative thinking. The LLM's ability to synthesize vast amounts of information and generate novel combinations provides a unique source of inspiration. It can suggest connections between disparate fields or propose unconventional angles for a project.

This is not about the AI generating creative work independently. Instead, it serves as a creative partner that can suggest a starting point, a different metaphor, or an alternative structure. The human remains the ultimate arbiter of taste and direction, but the creative process is enriched by the AI's contributions.

The experience demonstrates that creativity can be a collaborative process, even with a non-human partner. The LLM's suggestions can push a person's thinking beyond its habitual patterns, leading to more innovative and original outcomes.

The Human-AI Synergy#

This personal account highlights a broader potential for human-AI collaboration. The narrative often focuses on what AI can do for us, but this experience shows what it can help us do with ourselves. It is a partnership that enhances human intellect rather than replacing it.

The value is not in the AI's intelligence alone, but in the way it is used to provoke and refine human thought. The process is inherently human-driven; the AI is a tool, and its effectiveness depends entirely on the skill and intention of the user.

This perspective shifts the conversation from one of competition to one of augmentation. It suggests a future where our most significant advancements may come from how we integrate these tools into our daily cognitive routines, making us better thinkers, creators, and problem-solvers.

Key Takeaways#

The journey of Philip O'Toole offers a valuable lesson in the evolving relationship between humans and artificial intelligence. It moves the discussion beyond automation and into the realm of personal and professional growth.

By engaging with LLMs in a conversational manner, individuals can unlock new levels of clarity, creativity, and problem-solving ability. This practice transforms AI from a simple utility into a powerful cognitive partner, capable of helping us think better, not just faster.

As these technologies continue to develop, the most successful users may not be those who simply ask the right questions, but those who learn to have the most productive conversations.

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