You might think that a conversation with ChatGPT is just like a normal human conversation--after all, they're both in plain English (or of course the language you speak to it).

Don't be fooled: talking to ChatGPT is really more like programming.

Introducing: the Ladder of Language

There is a widespread idea that computer code is complex and mysterious, full of inscrutable symbols and abstractions, but that's discounting human language's richness.

Programming requires everything to be stated explicitly: IF A THEN B ELSE C. It does not care much about vocabulary, and is thus replete with unnatural sounding words like networkTokenManager, ctxRef or retVal. By contrast, human language has many shades of grey: context can be implied; a sentence might mean its opposite; choice of words convey information, emotion and intent.

I like to think of this as the "Ladder of Language:"

• at the top, we have the rich and dense language that humans speak,

• at the bottom, the rigid and structured code that computers understand.

ChatGPT's Language: Neither Human nor Machine

ChatGPT understands language differently than most computer programs.

For example, it is not very good at working within the rigid formal logic required by programming languages: it often makes bugs or calls functions that don't exist. Similarly, it will often misunderstand something that any child would think is obvious (it often misunderstands negation, for example).

ChatGPT sits at the middle of the ladder. It is king in the land of meeting notes and TPS reports; lord in the fief of resumes and social media articles; conqueror of the steppes of domain-specific languages and structured data.

ChatGPT is Best at Moving Text Up and Down the Ladder

Because large language models are decent at parsing the complex semantics of human language (something normal programs can't do well at all), yet also able to deftly generate mostly correct computer gobbledigook (something humans are neither great at nor very fond of), ChatGPT's main strength is pushing words up and down the ladder.

It excels at tasks like:

• transforming natural language into JSON (moving down the ladder)

• writing comments for existing code (moving up the ladder)

• transform a voice memo into meeting slides (moving down the ladder)

• explain a bug based on a stacktrace (moving up the ladder)

• explain how to solve a problem step by step (moving down the ladder)

Moving down the ladder keeps ChatGPT on track by constraining the meaning of words.

Moving up or down the ladder makes things easier for humans to understand: converting cryptic computer code into something more fluid; summarizing long, or just badly written human language into something more structured and clear.

When prompting, always think about how you want to move around the ladder.