Siddharth Saoji 
A: Remember vibe coding?
B: Yes. The methodology was “paste everything in and believe.”
A: Somehow it worked.
B: Which was unfortunate. It gave people confidence.
A: Then we upgraded to context engineering.
B: Right. The groundbreaking idea that the model does not need your tax returns, product roadmap, childhood memories, and three Slack threads to write one SQL query.
A: Give only the relevant context, in stages.
B: A shocking departure from “attach the whole company.”
A: Then came harness engineering.
B: My favorite phase. The part where we admitted the prompt was not the product.
A: Because now you need retrieval, memory, ranking, tools, filters—
B: A small support team for the model, yes.
A: And next is loop engineering.
B: Which means the model keeps taking shots at the problem, updating its context, and trying again.
A: So instead of one smart answer, it builds judgment over multiple attempts.
B: Like an employee, except faster and with worse sleep habits.
A: Here’s the weird part: if the model manages the context better than the user, should the model own it?
B: Dangerous question.
A: Because then the model decides what matters, what to ignore, and what to do next.
B: Yes. At that point, “assistant” starts sounding legally cautious.
A: So the end state is not a chatbot?
B: No. The end state is a coworker.
A: A digital coworker?
B: Correct.
A: That asks fewer questions over time?
B: Ideally.
A: And if it gets really good?
B: Then one day it says, “I’ve handled it.”
A: Comforting.
B: “Deeply.”