Yesterday I spent the whole day in a kickoff meeting with one of the state agencies.
What started as a conventional system project has since moved in a very different direction.
Instead of just shipping software, we're now embedding a live AI agent inside the system itself - running within defined workflows, permission scopes, guardrails and kill-switch controls.
From an engineering standpoint, the most interesting part is the level of acceptance.
A few years back, getting VM access inside certain organisations - even for a small, isolated application - could be an uphill fight.
Today, some are already open to letting a live AI agent operate with sudoer privileges, and in tightly controlled cases, even full root access inside an isolated VM.
That is a significant shift.
It tells me the conversation has moved past whether AI is capable enough. The real questions are now about trust, control, security, and how safely an AI agent can operate inside real organisational infrastructure.
Once that trust is established, AI stops being just another application.
It becomes part of the operating layer.
Ultimately, our vision is to inject our own Agent AI and LLM intelligence layer into every client system, turning each deployment into an adaptive asset that grows in capability and value over time.
#AgentAI #AIInfrastructure #EnterpriseAI #AIAutomation #LLM #DigitalTransformation #AIEngineering
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The direction on what started as a conventional is exactly right.
Useful. We are dealing with we're now embedding a live right now.
I read this twice. isolated application is the part that stuck.
The section on yesterday I spent the whole is the strongest part for me.
Lebih jelas daripada dek vendor yang saya terima pasal yesterday I spent the whole.