LLM
Artificial IntelligenceArchitecting AI Agent Systems: A Strategic Framework for Production Deployment
Choosing the right LLM framework is a strategic business decision that determines scalability, cost control, and system resilience. Learn how to handle the trade-offs between speed, flexibility, and governance when building production-grade AI automation.
Frederico VicenteNov 202512 min read
InfrastructureEnabling Private LLM Execution: Trusted Execution Environments and Encrypted Containers
Running LLM inference and fine-tuning on private datasets requires bridging theoretical cryptography with practical high-throughput systems. Learn how TEEs and encrypted containers create compliance-ready, hardware-isolated execution environments for confidential AI workloads.
Frederico VicenteNov 202516 min read
Artificial IntelligenceModel Context Protocol: Standardizing Context and Tool Integration for Agentic AI
As LLMs evolve from stateless prompt responders to stateful, tool-using agents, fragile hand-wired orchestration is breaking down. MCP provides a vendor-neutral protocol for connecting models with structured context, tools, and external systems at runtime.
Frederico VicenteNov 202515 min read
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