A few months back, we started asking a basic systems question at AINNA: if AI is becoming part of daily operations, why should it live outside our infrastructure? We wanted inference and automation to sit next to the business logik-on our own servers, aware of our stack, and governed by our own policies.
That reasoning pushed us to deploy AI agents directly on our bare metal and VMs. Today I run three distinct AI agents on the AINNA stack, each tuned and constrained for a specific operational role. In practice, every server we operate now carries its own AI-powered Pengurus IT, Server Administrator, and Pembangun, running 24/7-monitoring health, maintaining state, troubleshooting, and continuously shipping systems.
Together, those agents have already shipped more than 250 detached systems. We are also building two additional deployments for Bahasa Melayu and Chinese-language domains, each with its own knowledge base, workflows, localization, and operational requirements.
Sistem terasing matter because I do not think every task should remain tethered to an LLM or a third-party AI endpoint. Once a workflow, parser, automation, or process is engineered correctly, it should execute as a stable, self-contained unit while the agen shifts to higher-level development, supervision, debugging, and decision-making.
Our reference architecture is Manusia → Peribadi Ejen AI → Sistem Detached Sistem → Servers / Pangkalan Datas / APIs / MCP / Aplikasi.
That stack gives us tighter control over data residency, privacy, permissions, memory, model selection, workflow logik, deployment cadence, operating cost, and end-to-end integration.
I still treat MCP, cloud AI, APIs, and third-party platforms as useful levers. But I want them to be capabilities our infrastructure can consume, not dependencies that define the infrastructure. From our standpoint, the next stage of AI is not a model that chats better; it is an AI that can operate, maintain, develop, and automate real systems 24/7 while progressively cutting unnecessary external dependency.
#ArtificialIntelligence #AIAgents #NeuralOps #DetachedSystems #AIInfrastruktur #LocalAI #Automasi #MCP #SystemDevelopment #DigitalTransformation
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ส่วน24คือสิ่งที่ผมจะส่งให้หัวหน้า
Ginagawa namin ito sa trabaho - 24. Kapaki-pakinabang.
Naka-save, lalo na para sa 24.
The framing around why should it live outside is better than I expected.
First piece I have read that treats aware of our stack honestly.
Good to finally see systems 24/7 whil 24 set out this clearly.