[OutOfHere]

Engineers do not need management. Investors do.

As I understand it, the purpose of management is to match financial resources with material+human resources to perform feasible tasks. There is nothing here I see that can't be done by an experienced token generator. If anything, automating management seems easier than automating engineering.

As for leadership, it can be done by the investors.

[pillefitz]

This is such a simplistic view I have difficulties deciding where to even start. Think of a manager as someone who engineers the fabric of the organization. Most of my time is spent debugging, communicating, finding the right abstractions, configuring processes - all very similar to the engineering work I previously did.

[OutOfHere]

How would an investor see it? If an investor had access to a top-ranked management model, would s/he willingly spend 100x more on a person instead?

Or if you're saying you still do engineering/product work, then perhaps it shouldn't come with a management title. Whispering task allocation ideas to the AI is for everyone to do.

[aabdi]

The art of management - beyond the day to day operations - is largely organization of abstraction and incentives.

As we’ve collapsed the cost of the operations then largely the point of such an llm is constructing above.

If you’re an engineer why wouldn’t you pay more for better abstractions in an llm? That’s half the work anyways.

To put some more context into this: a manager defines the shape of a group of people. They own amorphous blob of responsibilities and various services. This leads to context confusion and lack of ownership and diffuse ability to operate services.

To fix the manager goes: Team a is responsible for say the device platform. Team b is for the applications platform. Each is responsible for their domain and the abstraction of team. Each is then responsible for their own ops, roi, quality, else. This attempts to maximize consistency of context, incentives, and scaling. Whether it works or not is frankly up in the air.

But notice this is basically the same as deciding in your intra service modularization and how you define the interfaces. Can you objectively say that whatever abstraction you usually write is correct? No. You just hope with experience and pragmatism.

[visarga]

You can automate work but never owning the consequences. AI tasks emerge from human contexts, they perform work in the context and finally the outcomes collect in the context - gains, losses, risks, costs. So AI is great but it needs our skin for the start, middle and end of a task.

[OutOfHere]

It's not as if management owns any consequences. At best they adapt, but so can AI. Management tasks are not like engineering tasks.

[pillefitz]

As stated in the sibling comment, management is very similar to engineering.

[OutOfHere]

Of course management would like to make that claim, but I don't see it substantiated. In what way is management "owning the consequences" -- are they losing their equity or risking an unpaid suspension?