<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>The Knowledge Elephant insights</title><description>Practical guidance on AI readiness, AI agents, Azure cloud and modernising SaaS platforms.</description><link>https://www.theknowledgeelephant.com/</link><item><title>What AI Readiness Actually Means, and How to Measure It</title><link>https://www.theknowledgeelephant.com/blog/what-ai-readiness-means/</link><guid isPermaLink="true">https://www.theknowledgeelephant.com/blog/what-ai-readiness-means/</guid><description>Your organisation is AI-ready when adding or changing an AI feature is routine, reviewable and reversible. Six areas to measure it, with the evidence to look for.</description><pubDate>Sat, 07 Nov 2026 00:00:00 GMT</pubDate><category>AI readiness</category><category>AI strategy</category><category>Assessment</category><category>Agentic AI</category></item><item><title>A Paved Road for AI Workloads on Azure</title><link>https://www.theknowledgeelephant.com/blog/a-paved-road-for-ai-workloads-on-azure/</link><guid isPermaLink="true">https://www.theknowledgeelephant.com/blog/a-paved-road-for-ai-workloads-on-azure/</guid><description>The Azure platform defaults we set before a team ships its first AI feature: managed identity, private model endpoints, an AI gateway, tracing, cost attribution and eval gates.</description><pubDate>Sat, 07 Nov 2026 00:00:00 GMT</pubDate><category>Azure</category><category>Platform engineering</category><category>Infrastructure as code</category><category>OpenTofu</category><category>FinOps</category></item><item><title>Agentic Workflows in Regulated Fintech: Guardrails That Survive an Audit</title><link>https://www.theknowledgeelephant.com/blog/agentic-workflows-in-regulated-fintech/</link><guid isPermaLink="true">https://www.theknowledgeelephant.com/blog/agentic-workflows-in-regulated-fintech/</guid><description>How to put AI agents into payments, collections and lending workflows without creating reportable incidents: propose-approve, idempotency, decision records and residency.</description><pubDate>Sat, 07 Nov 2026 00:00:00 GMT</pubDate><category>Fintech</category><category>Compliance</category><category>Agentic AI</category><category>Audit</category></item><item><title>Designing an MCP Server Agents Cannot Misuse: Lessons from FAQ Hub</title><link>https://www.theknowledgeelephant.com/blog/designing-an-mcp-server-agents-cannot-misuse/</link><guid isPermaLink="true">https://www.theknowledgeelephant.com/blog/designing-an-mcp-server-agents-cannot-misuse/</guid><description>What we learned exposing a shared SaaS platform to AI agents over the Model Context Protocol: scoped keys, plan-then-apply tools, explicit publish and a gap feedback loop.</description><pubDate>Sat, 07 Nov 2026 00:00:00 GMT</pubDate><category>Model Context Protocol</category><category>Agentic AI</category><category>API design</category><category>FAQ Hub</category></item><item><title>Keeping Customer Data Separate When AI Agents Call Your Systems</title><link>https://www.theknowledgeelephant.com/blog/keeping-customer-data-separate-with-ai-agents/</link><guid isPermaLink="true">https://www.theknowledgeelephant.com/blog/keeping-customer-data-separate-with-ai-agents/</guid><description>Shared SaaS platforms were built for apps that only ask for their own customer&apos;s data. AI agents write their own requests. Five patterns that keep each customer&apos;s data private.</description><pubDate>Sat, 07 Nov 2026 00:00:00 GMT</pubDate><category>SaaS</category><category>Data privacy</category><category>Security</category><category>Agentic AI</category></item></channel></rss>