I hear this from teams every time we're scoping a new deployment. My answer is always the same: start small.
After years of building and deploying AI, IoT, and neural systems in production at AINNA, I've learned that AI delivers the most value when it's used as a builder, not a worker for repetitive tasks.
For example, instead of asking an LLM to process 1,000 pages of bank statements every month, ask it to build a deterministic extraction pipeline that can process those statements automatically. Once the pipeline is built, deployed, and tested, it runs those 1,000 pages - or ten million - without repeatedly hitting the model for the same operation.
Using this approach, our AI consumption dropped from 32 billion tokens in the first month to around 3 billion tokens the following month.
Don't use AI to repeatedly do the work. Use AI to build the system that does the work.
Start small. Build once. Scale forever.
#ArtificialIntelligence #AI #BusinessAutomation #DigitalTransformation #SystemEngineering #Automation #SME #Innovation #NeuralOps
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Hujah pasal 32 ni munasabah dan kemas.
Read this twice. ask it to build is what stayed with me.
Di sini baru 32 nampak masuk akal.
Bookmarked, mostly for dropped from 32 32 billion.
32这部分我看了几遍，值得再想。
The numbers around start small make more sense than most posts I read.
First piece I have read that treats don't use AI honestly.
You can tell the writer actually worked on use AI to build.