From the outside it always seems laughably circuitious compared to just learning skills ourselves.

Even if it did let me fill out TPS reports 20% faster, who even cares compared to all of this chaos?

the problem is scale. there's a tension between an individual developing technical skills (transfer cost is high, slow, expensive) and developing agent skills (transfer cost is low, instant, free).

so, just like a manager manages employees, or you consult a contractor, agents are a way of getting leverage over a system.

that said, if you want to learn to play saxophone, you're free to do so. just note your personal endeavors may begin to look more like hobbies than marketable skills.

	▲	rustystump 38 minutes ago \| parent [-]
		When the cost for this leverage is more than an employee the math stops mathing. Additionally, for tech work. There is a tension about doing work and not knowing that output is correct or not. I have seen ai spit out thousands of lines of opencv code for a simple color lut. The person doing this had no idea what was going on. If they continued, the token cost and time waiting for agents spinning only goes up. Yes, agents get smarter and cheaper but the above example replays over and over again even on crud apps. You still need to dev the skills and transfer costs for it to be effective.

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wahnfrieden 2 hours ago | parent | prev [-]

Shareholders want the company to figure out how to pay fewer employees, and pay them less by down-skilling them