I’ve run this pattern enough times now: start with an empty server, wire in AI agents, and let them work through reverse engineering, coding, database provisioning, Docker, Nginx, UFW, Fail2Ban, security checks, testing and deployment.
The part that matters from the systems side? AI agents can size and tune the infrastructure against the actual workload. If the app needs 8GB RAM, I don’t want to pay for 32GB just because that’s the default SKU.
That also feeds ESG goals: fewer idle compute resources, lower energy draw, less infrastructure waste, and tighter security, auditing and governance in the build pipeline.
On the business side it shows up as lower development cost, smaller teams, reduced server spend and faster deployment cycles.
Work that used to need a full IT department can now be handled by a few domain experts working alongside AI agents.
Less manpower. Less waste. Lower costs. Faster execution.
The future isn’t just AI-assisted coding. It’s AI-driven, cost-efficient and sustainable system engineering.
#AIAgents #DevOps #ESG #GreenIT #CostOptimization #NeuralOps
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Masih mencerna bagian 8.
The numbers around pay for 32G 32GB make more sense than most posts I read.
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