Insights on full-stack development, serverless architecture, and business impact.
22 results
As AI agents become better at using tools, the bottleneck shifts from model quality to permission design. This post lays out a least-privilege operating model for MCP-based tool use.
A practical explanation of vector databases, how they differ from traditional databases, and why they matter for AI search, RAG, and recommendation systems.
A technical explanation of how vector databases store embeddings, search them with ANN, and match results back to original documents.
If MCP standardized tool connectivity, permissions, policy, audit, and isolation are what make production AI agents safe.
MCP, multi-agent workflows, and tool integrations are hot right now, but production systems live or die by context, state, and control planes — not the protocol alone.
Google Workspace's agentic expansion and NVIDIA's BlueField-4 STX point to the same shift: AI is becoming an operations-architecture problem. This post reframes AI workloads through a control-plane lens.