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The AI Cloud Engineer Needs Context, Not Just a Bigger Model

31 July Online

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About this event

Most teams are asking the wrong question about AI in DevOps.
The real question is not:
“Which model should we use?”
The better question is:
“What context does the model need to make a safe, useful, and infrastructure-aware recommendation?”
Cloud and DevOps work depends on live, private, and constantly changing information. This includes service dependencies, Kubernetes configurations, cloud inventory, cost trends, security rules, migration constraints, internal SOPs, provider guidance, and business priorities.
A general-purpose AI model cannot know this context on its own. Without it, AI can produce fluent but risky answers. It may miss hidden dependencies, underestimate migration effort, ignore company-specific operating procedures, or recommend solutions that do not fit the real infrastructure environment.
In this meetup, Max Karambelas, Founder and CEO of CloudGo.ai, will explain how CloudGo approaches AI for cloud operations by converting scattered infrastructure data, documents, provider guidance, and operating procedures into structured context that AI can reason over.
The session will explore practical lessons from building AI-assisted migration and modernization workflows. Max will discuss where AI can accelerate engineering work, where human review still matters, and how cloud teams can reduce planning effort while improving consistency, traceability, and confidence.
This is not a session about chasing the biggest model. It is about understanding how context, infrastructure awareness, and human validation can make AI more useful for real DevOps and cloud engineering work.
Who Should Attend
This session is ideal for:
Cloud engineers
DevOps engineers
Platform engineers
Solution architects
Cloud migration teams
Managed service providers
Engineering managers
Startup Founders
AI and automation teams
Anyone exploring AI-assisted cloud operations
What You Will Learn
By joining this session, you will learn:
Why bigger AI models alone are not enough for cloud and DevOps work
What type of infrastructure context AI needs to make better recommendations
How scattered cloud data and internal documentation can become useful AI context
Where AI can reduce manual cloud assessment and migration planning work
Why human review is still important in AI-assisted engineering workflows
How teams can improve consistency, traceability, and confidence in cloud decisions
How AI can support modernization and migration without removing engineering control
Speaker
Max Karambelas
Founder and CEO
CloudGo.ai
Session Theme
AI for cloud operations, infrastructure context, migration planning, modernization, DevOps decision-making, and trusted AI-assisted engineering.

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