Deep dives into AI code security, the competitive landscape, and the future of autonomous software development.
88% of organizations reported AI agent security incidents in 2025. With 47% of enterprise AI agents running without oversight, the guardrails crisis is here. Here's what's failing — and a five-step action plan for CTOs.
From OpenAI Codex to Claude Code to AWS Strands, the agent SDK landscape exploded in 2025. The definitive breakdown of who's winning, the protocol wars (MCP vs. A2A), and why governance is the missing layer.
Security teams see two extremes: source code in Git, and running code in production. Everything in between is a black box. Here's why real-time work-in-progress monitoring is the critical missing layer in DevSecOps.
Every transformative technology needs governance. Cars needed traffic lights. Factories needed safety regulations. AI coding tools need guardrails. The evolution from basic autocomplete to autonomous agents — and why speed without quality creates existential risk.
How a single malicious comment in your codebase can trick GitHub Copilot into generating SQL injection vulnerabilities — and why your SAST scanner won't catch it until it's too late.
AI coding tools promised 55% productivity gains. Instead, companies are hemorrhaging billions on bad AI code. Here's the hidden cost breakdown with real data.
We analyzed 30+ AI security tools across 7 categories — from GitHub Copilot Enterprise to Lakera AI. Here's what the competitive landscape tells us about the future of AI code governance.