Five Levels of AI Coding and how to migrate existing codebase up this pyramid

Dan Shapiro (Serial entrepreneur, CEO of Photobucket and Senior Research Fellow in Wharton's Generative AI Lab) has determined that there are Five Levels of the Use of AI in Code Development (mirroring the Five Levels of Driving Automation)

Level	Summary	Description
0	Spicy Auto-complete	The Engineer writes all the code, but uses AI for auto complete of the next variable_name or guessing the next couple of lines of code. Tab to accept.
1	Coding Intern	AI writes boilerplate code for standard procedures with well-documented instructions
2	Junior Developer	Human writes detailed specifications for requirements that may span with multiple modules. You don't specify how it should do it, but what it should do. The AI cranks it out. You still review it.
3	Developer	Human manages agents. Human feeds in specs, agents push code back to Human for review and approval.
4	Engineering Team	Human writes product requirements and test thresholds and Human only spots check output when system tests have passed. Human doesn't care too much about what the underlying code does - as long as it works AND doesn't fail.
5	Dark Software factory	No human writes the code or tests it - indeed it would be suicidal if they did. Nate Jones (see below) makes the point that the code generation doesn't know the test criteria during development (so not like XProgramming): the AI has to develop its own unit and system tests. Code-Gen submits it to a separate testing entity - a scenario that I envisaged this time last year. No-one is here yet (really).

How to apply to existing software

Here is Nate Jones on the migration path for existing software houses. This is an excellent video (and you should view the rest of it), but I jump to his commentary on how existing software providers need to implement this on their existing code base and development practices.

1. First use you use AI Level 1 & 2 to refactor existing code.
2. Use AI to reverse engineer your code to product specs that should have been written first time around (and maintained - haha - product managers know that specs are never maintained once the code gets into the hands of the engineer!)
3. Then re-engineer your development process to be AI first: new testing workflow (testing definition up front - how about that?!?) and different review processes. 
4. Next, new development uses autonomous agent development (and maintain the old code base using the former methodology).
5. Finally, cast off the old way of doing thing, restructure your organisation to solely adopt these new techniques.

I think organisational behaviour of existing software houses will be a HUGE barrier to adoption and there will be pitched battles when AI-gen and human-gen which may well rip apart companies.

Does this mean that only start-ups can get to Level 4 and Level 5? Yes, I think so.