The Five Levels: from Spicy Autocomplete to the Dark Factory

The Five Levels: from Spicy Autocomplete to the Dark Factory

Dan Shapiro proposes a five level model of AI-assisted programming, inspired by the five (or rather six, it's zero-indexed) levels of driving automation.

1. Spicy autocomplete, aka original GitHub Copilot or copying and pasting snippets from ChatGPT.


2. The coding intern, writing unimportant snippets and boilerplate with full human review.


3. The junior developer, pair programming with the model but still reviewing every line.


4. The developer. Most code is generated by AI, and you take on the role of full-time code reviewer.


5. The engineering team. You're more of an engineering manager or product/program/project manager. You collaborate on specs and plans, the agents do the work.


6. The dark software factory, like a factory run by robots where the lights are out because robots don't need to see.

Dan says about that last category:

At level 5, it's not really a car any more. You're not really running anybody else's software any more. And your software process isn't really a software process any more. It's a black box that turns specs into software.

Why Dark? Maybe you've heard of the Fanuc Dark Factory, the robot factory staffed by robots. It's dark, because it's a place where humans are neither needed nor welcome.

I know a handful of people who are doing this. They're small teams, less than five people. And what they're doing is nearly unbelievable -- and it will likely be our future.

I've talked to one team that's doing the pattern hinted at here. It was fascinating. The key characteristics:

• Nobody reviews AI-produced code, ever. They don't even look at it.


• The goal of the system is to prove that the system works. A huge amount of the coding agent work goes into testing and tooling and simulating related systems and running demos.


• The role of the humans is to design that system - to find new patterns that can help the agents work more effectively and demonstrate that the software they are building is robust and effective.

It was a tiny team and they stuff they had built in just a few months looked very convincing to me. Some of them had 20+ years of experience as software developers working on systems with high reliability requirements, so they were not approaching this from a naive perspective.

I'm hoping they come out of stealth soon because I can't really share more details than this.

Tags: ai, generative-ai, llms, ai-assisted-programming, coding-agents