Interpreting Is Giving Meaning to Data

Raw data has no intrinsic meaning: it’s merely a sequence of 1s and 0s, an inert structure, an arrangement of symbols. It’s interpretation that confers meaning.

The sequence 01000001 can be:

• The letter ‘A’ in ASCII
• The number 65 as an unsigned integer
• A shade of red in a color channel
• A machine instruction

depending on the context in which it’s read.

The data itself doesn’t say what it is; it’s the interpreter, whether program, machine, or human mind, that projects a reading grid and extracts meaning. Without interpretation, there’s only noise, raw data.

Formats and Protocols

This observation illuminates the notion of format and protocol.

A JSON file is just a string of characters; it’s the JSON parser that gives it a tree structure. A network packet is just a sequence of bytes; it’s the TCP/IP stack that extracts addresses, ports, and payloads.

Each layer of interpretation transforms opaque data into meaningful data for the next layer. The same binary stream passing through different interpreters, such as a hex editor, an audio player, or a decompressor, will produce entirely different “realities.”

The interpreter is the creator of meaning.

Program as Value

In functional programming, this idea takes a particularly explicit form with the program as value pattern.

An Effect<A> or IO<A> is data: an inert description of what a program could do. Without an interpreter, this description remains a dead letter, a data structure that can be manipulated, combined, transformed, but does nothing.

The interpreter (unsafeRunSync, runPromise, or a test runtime) traverses this structure and brings it to life, translating the description into real effects.

The same description submitted to different interpreters will produce different behaviors: real execution, simulation, logging, dry-run, etc.

DSLs as Description/Interpretation Duality

DSLs embody this duality with elegance.

A DSL produces data: an AST in initial encoding, polymorphic functions in final encoding; all of this representing only intentions, without executing them.

The interpreter is what transforms “add 10 to account X” into:

• A real banking transaction
• A log line
• A test update

The value of the DSL lies precisely in this separation: we can reason about descriptions, validate them, optimize them, before choosing how to give them meaning. Interpretation becomes an extension point where we decide what each language operation “means.”

The Developer as Interpreter Designer

This perspective has profound implications for software design.

If interpreting is giving meaning, then designing a system is deciding what interpretations will be possible:

• A well-designed type constrains valid interpretations; too broad a type allows false ones
• A module boundary defines where interpretation changes, where domain data becomes infrastructure data, where business intentions become technical effects

The developer, ultimately, is a designer of interpreters: they define how data (user inputs, events, commands, configurations, etc.) will be read, understood, and transformed into behavior by the software.

The code they write is nothing other than the formalization of this reading grid.