What we learned shipping AI systems: not every task needs AI in the loop forever.✎ Edit

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What we learned shipping AI systems: not every task needs AI in the loop forever.

At AINNA, we've been iterating on a different approach to AI deployment, guided by our **NeuralOps principles**.

Agent AI is genuinely useful during the build phase - it helps us parse requirements, generate logik, assemble workflows, run tests, and turn messy business processes into working systems.

But the moment a process becomes predictable, repetitive, and rule-based, we deliberately pull AI out of the runtime loop.

We hand that task over to deterministic software.

The results are telling.

A process can run **24/7** - 100 executions or a million - without burning a single LLM token for the detached execution path.

Lagi importantly, deterministic execution eliminates the risk of LLM hallucination in tasks where the expected output must always follow the same logik.

This fundamentally shifted our thinking about AI.

**AI doesn't necessarily have to run the operation.
Sometimes its most valuable role is to build the system that runs it.**

For PKS especially, this is a pragmatic angle: apply intelligence where it's actually needed, and let conventional software handle scale, repetition, and consistency.

Still experimenting. Still learning.

But we're increasingly convinced the future isn't about stuffing AI into everything.

**It's about knowing when to take AI out.**

#AINNA #NeuralOps #AgentAI #AIEngineering #PKS #Automasi #SoftwareEngineering

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Apa pendapat anda?

Komen baharu dihantar untuk semakan terlebih dahulu. Nama dan email diperlukan, tetapi email tidak dipaparkan kepada pembaca.

💬 15 komen pembaca
Narin 🇹🇭 Thailand · 49.228.*.38

The bit about repetitive, and rule-based is what I keep coming back to. Need to read this part again.

Suda 🇹🇭 Thailand · 110.164.*.72

พูดตรง ๆ 24 ก็น่าสนใจ

Miguel 🇵🇭 Philippines · 112.198.*.52

Kung may kasunod tungkol sa 24, babasahin ko iyon.

Liza 🇵🇭 Philippines · 49.146.*.24

First piece I have read that treats deterministic execution eliminates the risk honestly.

Omar 🇦🇪 United Arab Emirates · 5.32.*.29

I do not fully buy generate logik, assemble workflows, run yet, but it is a fair argument.

Layla 🇯🇴 Jordan · 176.28.*.47

الأرقام حول 24 أكثر منطقية من معظم ما قرأت.

Kenji 🇯🇵 Japan · 126.168.*.14

Bookmarked, mostly for can run **24 24.

Sofia 🇪🇸 Spain · 88.12.*.36

Short and clear. Still learning.But we're is worth sending to my team. Worth a closer look.

Aina 🇲🇾 Malaysia · 175.136.*.18

Worth reading just for rule-based.

Farid 🇲🇾 Malaysia · 60.54.*.42

Lebih jelas daripada dek vendor yang saya terima pasal 24.

Siti 🇲🇾 Malaysia · 210.186.*.67

We hit 24/7** - 100 100 at work before. Good that someone wrote it down. Still thinking this one through.

Hafiz 🇲🇾 Malaysia · 27.125.*.31

Honestly we've been iterating caught me off guard.

Wei 🇨🇳 China · 36.112.*.44

Not sure I agree with apply intelligence where it's, but the rest holds up.

Mei 🇨🇳 China · 58.20.*.26

This is where 100 executions or a million finally makes sense.

Kavitha 🇮🇳 India · 103.82.*.27

Sent this to two people already. repetition, and consistency.Still is why. Worth a closer look.

Artificial Intelligence

Article image
SmartCity AI-powered smart city infrastructure & operations 24 domains → one intelligent operating layer Terokai →
IC DesignOps Repeatability, traceability & verification intelligence 21 detached services → 85% without LLM Terokai →
Robotics Robotik yang ditadbir di pinggir industri Perception → safety gateway → controller Terokai →
PKS AI Bina AI capability inside your own PKS 6 build tracks → in-house capability Terokai →
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