100%, it makes engineering faster, not more real. the critical step outside of that is that AI makes the flow of ideation to execution more feasible if the cost of engineering is prohibitive enough to have made that flow infeasible in the past. this applies to RFCs as well. it's like the difference of having connected rooms in virtual reality because the environment suddenly upgraded to doors and opposable thumbs.

it doesn't take much for a layperson to hallucinate bad code via prompt right now, whereas the barrier for layperson to manifest any code used to be binary in the past. it's going to be even easier to subdivide an LLM prompt into chains of prompts. if one can load the respective codebase/docs as context (GPT-4 goes up to 32k tokens), the cost of hallucinating bad, but very relevant code, gets progressively cheaper.

right now, I expect any OSS community to progressively gain the ability to dogfood on whatever natural language the testers and powerusers are outputting. I think that major platforms, like social media, are quickly going to figure out that they can offer an experimental branch and not twiddle their thumbs around an unanswered user survey because of how easy it will be to transcribe sentiment & nuanced feedback from the comments.

point being, software doesn't impact the world because of how self-involved the team of a monolith is. software impacts the world when the modularity spikes (between many teams/firms and the larger market).