Kamya Shah

Kamya Shah

Claude Code Internal MCP Servers: Connect Without Exposing Credentials

Claude Code Internal MCP Servers: Connect Without Exposing Credentials

TL;DR * Putting MCP server credentials in Claude Code's settings.json, .mcp.json, or environment files spreads secrets to every developer machine with no rotation path and no audit trail. * Bifrost stores upstream MCP credentials on the gateway and gives each developer a scoped virtual key, so Claude

Reliable AI: How Engineering Teams Prevent LLM Failures

Reliable AI: How Engineering Teams Prevent LLM Failures

TL;DR * Reliable AI in production depends less on model quality than on what happens when a provider call fails, because 429 rate limits and 5xx errors arrive on a routine basis. * Retries and fallbacks solve different problems: retries handle transient errors inside one provider, fallbacks switch providers once the

Shadow AI: How CISOs Get End-to-End AI Governance

Shadow AI: How CISOs Get End-to-End AI Governance

How CISOs extend AI governance to shadow AI on employee machines, including desktop apps, browser AI and coding agents.

Top 5 MCP Gateways Built for Production AI Systems

Top 5 MCP Gateways Built for Production AI Systems in 2026

TL;DR * An MCP gateway for production aggregates MCP tool servers behind one endpoint and adds authentication, per-client tool filtering, observability, governance, and failover. * Bifrost ranks first: it adds 11 microseconds of overhead per request at 5,000 RPS and combines OAuth 2.0, tool filtering, clustering, and Code

Model Routing: How to Cut LLM Token Costs

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.

AI Governance Framework for Enterprises: The 2026 Guide

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.

5 MCP governance features enterprises should demand from an AI gateway

5 MCP Governance Features Enterprises Should Demand

TL;DR * MCP governance controls which tools AI agents can discover and call, how they authenticate, how access is recorded, and what tool traffic costs, enforced at a central AI gateway. * The five features to demand are deny-by-default tool access, curated tool bundles scoped to identity, centralized MCP