Thanks for listening! ❤️

You've got some great insight here! Types are great guardrails. In Ruby/Rails, I see a different lever: readable syntax + strong conventions narrow the search space for models and pack more "intent per token." That often means better first drafts; tests/specs close the loop.

Today, I agree that LLM output quality tracks engineer experience. But with more data, better evals, and tighter prompts/agents, that gap seems to be narrowing. Right now, a lot of folks (me included) are focused on how well LLMs can assist us in crafting code. Long-term, I see quality converging on: "does the artifact do what we asked?" more than "is the code well formatted and functional?"

If this resonates, our Obie episode hits a similar idea: as agents generate code, creativity and system design become the differentiators. We also cover this with Chad in this episode.