We have been experimenting with a different approach at AINNA through our **NeuralOps principles**.
Agent AI is useful during development - understanding requirements, generating logic, building workflows, testing, and helping turn business processes into working systems.
But once a process becomes predictable, repetitive, and rule-based, we try to remove AI from the execution loop.
The task is handed over to deterministic software.
The result is quite interesting.
A process can continue running **24/7**, whether it executes 100 times or millions of times, without consuming LLM tokens for the detached execution.
More importantly, deterministic execution does not introduce LLM hallucination into tasks where the expected result should always follow the same logic.
This has changed how we think about AI.
**AI does not necessarily need to run the operation.
Sometimes, AI's most valuable role is to build the system that does.**
For SMEs especially, this could be a practical way to approach AI - use intelligence where intelligence is actually needed, and let conventional software handle scale, repetition, and consistency.
Still experimenting. Still learning.
But increasingly, we believe the future may not be about putting AI into everything.
**It may be about knowing when to take AI out.**
#AINNA #NeuralOps #AgentAI #AIEngineering #SME #Automation #SoftwareEngineering
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मुझे 24 वाला हिस्सा पसंद आया, यह बहुत सैद्धांतिक नहीं है।
Clear and short. Sharing whether it executes 100 times with my team.
Bookmarked, mainly for rule-based.
The bit about it executes 1 100 is what I keep coming back to.