So you’ve heard of TDD. Maybe BDD. But have you heard of RDD?

REPL-driven development. I think most programmers these days don’t work this way. The closest equivalent most people are familiar with is something like Python notebooks—Jupyter or Colab.

But RDD is actually pretty old. Back in the 70s and 80s, Lisp and Smalltalk were basically built around the REPL. You’d write code, run it immediately, see the result, and iterate. The feedback loop was instant.

Then the modern era of software happened. We moved to a file-based workflow, probably stemming from Unix, C, and Java. You write source code in files. There’s often a compilation step. You run the whole thing.

The feedback loop got slower, more disconnected. Some languages we use today like Python, Ruby, JavaScript, PHP include a REPL, but that’s not usually how we develop. We write files, run tests, refresh browsers.

Here’s what’s interesting: AI coding assistants are making these interactive loops relevant again.

The new RDD is natural language as a REPL.

Think about it. The traditional REPL loop was:

1. Type code
2. System evaluates it
3. See the result
4. Iterate

The AI-assisted loop is almost identical:

1. Type (or speak) your intent in natural language
2. AI interprets and generates code
3. AI runs it and shows you the result
4. Iterate

You describe what you want. The AI writes the code. It executes. You see what happened. If it’s not right, you clarify, and the loop continues.

This feels fundamentally different from the file-based workflow most of us grew up with. You’re not thinking about which file to open, You’re thinking about what you want to happen, and you’re having a conversation until it does.

Of course, this isn’t a perfect analogy. With a traditional REPL, you have more control. You understood exactly what was being evaluated because you wrote it.

 >>> while True:
  ...     history.repeat()