1. "agentic" development is here to stay, whether we like it or not
2. markdown prompts are a terrible way of driving such development, no matter how much structure and hierarchy you're trying to impose (whether chaining or fan-out into personas, etc)
3. jigsaw-puzzle approach is less terrible - declare the "boundary" of any component or subsystem in a normative language of your choice and let the agent fill the insides
it's fine if you think those convictions are incorrect, but i'm more interested in feedback from folks that more-or-less agree, with regard to the last point: what do YOU use for normative language to describe component boundary, function and cross-component interactions?
i've had mild success with openapi, but maybe there are better alternatives?
The key point is you are breaking up the context of what you are building into smaller areas of focus. The smaller contexts allow agents to do work with only the context of what their tasks are, so you have less of a chance of hallucinations and they each get a larger context window than they would if you had all of your context written out into a single text file.
This is why a lot of folks call them junior engineers. You wouldn't ask a junior engineer to "act as a senior expert JS developer and build a front end for a SaaS project management app" and expect them to do it with good output. You need to define specific things you want done and how you want them done - "use react, call APIs for data, APIs should be RESTful, etc." You can add personas to them if you like and personalities but thats more for entertainment.
this is true for both mardown and normative specs
what's meaningfully different is that normative specs is something you can deterministically check for conformance with, use generative tests, etc and feed that information back into the agent loop
letting the same LLM generate both implementation and tests from markdown prompt is a) completely meaningless, because once the agent is done and test suite is green you still have no idea if the right thing was implemented and if the right thing is being tested; b) useless waste of tokens, because why would you spend them on probabilistic generation of tests that likely contain hallucinations if you could instead deterministically generate them from normative spec using external tool
IMO, there is no such normative specs. Just tell your agent what you want and teach it until it gives exactly what you want.
if it is your belief that understanding what is going on is not necessary nor important - agree to disagree.