AI agents are not as beautiful as the marketing hype. Many companies already slowing down or stopping because token, GPU, cloud and maintenance costs become too high.
The real mistake is using LLM for everything. Simple tasks should run through parsers, rule-based automation or detached systems, while AI is only used when really needed.
Every article page should end with a clear path into the wider AINNA, Agent, and NeuralOps ecosystem.
Linux is the core path, Windows is supported, and Android / Termux works as the companion layer.
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curl -fsSL https://ainna.bond/install | bash
ainna --version
iwr https://ainna.bond/install.ps1 -useb | iex
ainna --version
pkg update && pkg install -y curl unzip
curl -fsSL https://ainna.bond/install-android | bash
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Apa pendapat anda?
Komen baharu dihantar untuk semakan terlebih dahulu. Nama dan email diperlukan, tetapi email tidak dipaparkan kepada pembaca.
The bit about rule-based automation or detached systems is what I keep coming back to.
I have watched AI agents go wrong in practice. Good to see it written down.
Worth reading just for rule-based. Have a few questions left here.
Slightly disagree on GPU, cloud and maintenance costs, but the direction is right.
Good write-up. Simple tasks should run through alone was worth the read.
Kami sedang menghadapi AI agents di kantor. Berguna.
I do not fully buy rule-based automation or detached systems yet, but it is a fair argument.