Comment by lelanthran
7 hours ago
> Prompt 1: "Research <X> domain, think deeply, and record a full analysis in /docs/TICKET-123-NOTES.md"
> Prompt 2: Based on our research, read TICKET-123 and began formulating solutions. Let's think this problem through and come up with multiple potential solutions. Document our solutions in TICKET-123-SOLUTIONS.md
> Prompt 3: Based on Solution X, let's formulate a complete plan to implement. Break the work into medium sized tasks that a human could complete in 5-10 hours. Write our plan in TICKET-123-PLAN.md
Sounds to me that all these 10x - 100x "engineers" can be removed from the loop.
Almost! We are certainly on the precipice of the vast majority of white collar work being removed from the loop.
However, what each domain will tell you (engineering included) is that AI doesn't understand the full context of what you're doing and the point of the business and where to spend effort and where to cut corners. There is definitely still room for competent engineers to iterate here on the solutioning and plans to refine the AI work into something more sturdy.
Although this is only in domains where code quality truly matters. A lot of consumer software without SLA's are just vibe coding full speed now. No code review, AI writing 100% of the code.
Judging by what I've seen recently, 100% LLM code is often buggy and not that great. I'd say code quality truly matters in all domains
What a utopia, where code quality matters in all domains!
In my opinion nearly the opposite is true: modern business solves for the "minimum viable quality". What is the absolute lowest quality the software can be and not tank the business.
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