The Governance Decision Hiding Inside an Integration Decision The Model Context Protocol (MCP), introduced by Anthropic in late 2024, has become the "de facto standard" for connecting AI agents to enterprise tools and data in just two years. That is a remarkable adoption curve. It is also a warning sign, not a green light. Here is the fact that should anchor every decision your organization makes about MCP: standardization arrived before security scrutiny did. MCP's security weaknesses are architectural, not implementation bugs. Your organization is very likely adopting, or has already adopted, this protocol in the same sequence: deploy first, govern later. The integration problem MCP solves is real, and the efficiency gain is genuine. But the same design choice that makes MCP powerful (letting an AI agent read natural-language descriptions of tools and decide for itself what to do) is the exact mechanism that removes predictability from your systems and open...
Are AI coding agents worth the investment? AI coding agents have crossed the experimentation phase. Most engineering organizations now use them daily, and measurable productivity gains are real. Yet many orgnizations are discovering an uncomfortable reality: faster code generation does not automatically translate into faster software delivery. The constraint has shifted from writing code to reviewing, governing, and maintaining it. AI has commoditized code generation, what remains scarce is the engineering judgment - understanding architecture, evaluating trade-offs, managing risk, and deciding what code should exist in the first place. Organizations that mistake generated code for engineering productivity will optimize the wrong metric. Organizations deploying coding agents without architectural guardrails, security controls, and revised engineering practices will accumulate a new form of technical debt that will surface months after the initial product...