Model Routing: How to Cut LLM Token Costs
A guide to cutting LLM token costs with model routing, semantic caching, code mode for tool calls, and enforced budgets.
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AI Governance Framework for Enterprises: The 2026 Guide
A guide to building an enterprise AI governance framework, from NIST AI RMF, ISO 42001 and EU AI Act requirements to runtime controls.
Open Source Observability Platform for LLM and Agent Workloads
TL;DR
* An open source observability platform for LLM traffic is assembled from four building blocks: the OpenTelemetry Collector for pipelines, Prometheus for metrics, Grafana for dashboards, and Jaeger (or another OTLP backend) for traces.
* A generic stack records HTTP status codes and latency but has no native concept of
AI Security Risks: A Practical Guide for Engineering Teams
A register of AI security risks for engineering teams, mapped to the OWASP Top 10 for LLM Applications with the enforcement layer for each.
AI Security Posture Management for LLM Applications
A guide to AI security posture management for LLM applications, covering how AI-SPM differs from CSPM and DSPM and its four pillars.
How MCP Tools Work: Discovery, Invocation and Access Control
TL;DR
* MCP tools are executable functions an MCP server advertises to a client through tools/list and runs on request through tools/call, each described by a JSON Schema the model uses to build arguments.
* The protocol defines two error paths: JSON-RPC protocol errors for unknown tools or
The MCP Protocol: Transports, Primitives, and the Message Lifecycle
TL;DR
* The MCP protocol is a JSON-RPC 2.0 standard with two transports, stdio and Streamable HTTP, and three server primitives: tools, resources, and prompts.
* Revision 2026-07-28 made MCP stateless: the initialize handshake is gone, and every request carries its protocol version and client capabilities in