BBS:      TELESC.NET.BR
Assunto:  AI LLM Artificial intelligence infrastructure
De:       bbsing
Data:     Wed, 11 Mar 2026 21:41:55 -0700
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  hbRenb: hcAI LLM Artificial intelligence infrastructure
  bBynb: hcArelor bto cbbsing bon cWed Mar 11 2026 14:23:49n

 > I think the people asking to get AI integrated with workflows and selecting
 > employees according to their suitability for AI work are typically
 > management types rather than people doing the actual work. In the end you
 > get AI pushed into both things that benefit from it and things that don't.

Management's dream is have no employees.

In the mind of those who don't do the work, it really seems these tools can do whatever anyone asks. They don't think about the quality and accuracy as a significant differentiator for sucess with competitors in the market. A lot of time management is focused on speed and efficency for protoctivity/cost reduction. Make widgets faster = more money. When mamagement recieves negative feedback from the markets, its usually too late for the employees they've let go.

 >
 > You can get some LLMs to write good boilerplate for your
 > Terraform/OpenTofu/Ansible/Whatever deployments. However, at this point you
 > would be crazy to let an AI agent act as an orchrestrator for you.

I used to hear a lot about infrastructure as code, not as much over the past 3 years.

Probablistic determinates are a problem that doesn't seem to be going away.


But the media and hype machine is saying all jobs done on a screen will be targets for AI/LLMs to take over.

Whats a person to do?
Learn these new tools?
Stick with traditional methods?
A bit of both?

Cost is such an issue these days in the LLM space.
n
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