I'm not talking about not just punching the keyboard to type out the identifiers in the code. I'm talking about not making decisions about most classes and functions, most type definitions, most of the weedy logic within most modules, etc. If it can't be described in natural language as requirements, or in a typescript type or other data shape DSL (I think key data model types are probably still important to own), it's probably too weedy.

Natural language test cases still define the expectations both at the product and architectural level and are essential for triangulating the agents on successful outcomes.

A requirements and verification approach with agents is not waterfall any more than TDD is waterfall. Does thinking ahead and doing some planning equal waterfall? Does describing how a feature works to an end user, and making some key technical decisions, before you build it, mean waterfall? Does having some sense of what you're building first mean waterfall? With agents, you can specify (with PRD and technical specs) what you THINK it should do, and in minutes or hours or at most days, have the result, which you then learn from and iterate. If you didn't fully think it through, the agents will do one of three things: 1) decide for you, which you learn from 2) stop and ask, which you learn from 3) introduce bugs, which you learn from.

It's extremely iterative.

How are you thinking about technical debt in this new agentic age? (also markdown debt?)

It's one of my bigger concerns and I use this iterative approach to try and reduce it... "go look at the ./cli directory and generate me a report of inconsistencies blah blah..." or "review ./research/something.md, validate consistency, correctness, claims, ..."

... pseudo prose, have we made that a thing yet like pseudo code?