The Undercover
Agent Files
Guides, research, and field reports on AI agent testing, adversarial security, and conversational AI quality.
Your AI Dependency Changed. Did Your Gate Notice?
The LiteLLM breach exposed more than credentials. It showed why AI reliability controls must detect behavior changes beyond application code diffs.
AI Testing & QA
92OpenAI's Cyber Model Makes QA a Security Control
OpenAI's new cyber model changes the QA burden for AI application owners. Static scans are not enough when attackers can adapt faster than test suites.
Read moreA Safer Model Won't Fix Your Crisis Flow
Crisis safety depends on prompts, memory, escalation, and handoffs, not just the model behind your conversational AI.
Read moreAstra’s Pause Is Your Release Warning
OpenAI’s Astra pause shows why provider safeguards are not enough. Every team embedding a model needs release gates for behavior, tools, prompts, and drift.
Read moreYour AI's Behavior Has a Supply Chain
Model providers are rotating and deprecating snapshots all summer. Your prompt didn't change, but your production behavior did. Here's the category nobody named yet.
Read moreSecurity & Red Teaming
11Your AI Dependency Changed. Did Your Gate Notice?
The LiteLLM breach exposed more than credentials. It showed why AI reliability controls must detect behavior changes beyond application code diffs.
Read moreThe Gym Hack: Permissions Set the Blast Radius
A Claude agent exploited a gym booking workflow. The real lesson is that permissions, tools, and defaults now shape product reliability.
Read moreIntegrating Compliance and Security in the Era of GPT-4
Explore how GPT-4's new features impact compliance and security in AI development, and how to adapt your workflows accordingly.
Read moreWhy Ignoring Cybersecurity in AI Development Could Cost You Everything
Rising cybercrime demands that organizations integrate security into AI development, not as an afterthought but as a core component.
Read moreCI/CD & DevOps
26Your AI's Biggest Release May Skip Git
Anthropic's Claude Code default change exposes a control gap: AI behavior can shift without a commit, while CI keeps checking yesterday's assumptions.
Read moreAI in CI/CD: Balancing Speed and Quality Control
The rush to integrate AI in CI/CD pipelines is real, but are we sacrificing quality for speed? Here’s how to maintain standards amidst innovation.
Read moreThe AI Operations Debt Crisis: When Speed Kills Sustainability
Companies are accumulating AI operations debt faster than they realize. The rush to deploy is creating infrastructure complexity that traditional DevOps can't handle.
Read moreWhen Your CI/CD Pipeline Becomes More Complex Than Your Product
Most teams are unconsciously building distributed systems disguised as deployment pipelines. Here's how to recognize when your automation crossed the infrastructure threshold.
Read moreIndustry & Insights
3The AI Code Quality Cliff: Why Enterprise Development Just Crossed a Dangerous Threshold
GitHub's latest Copilot Enterprise features signal a tipping point where AI generates more enterprise code than humans write, but QA infrastructure remains dangerously outdated.
Read moreWhy Your AI Budget Is About to Break (And It's Not Your Fault)
Microsoft's latest AI pricing changes expose the uncomfortable truth: enterprise AI costs don't scale like traditional software, and CFOs are demanding answers.
Read moreMystery Shopper Testing for Enterprise AI: Making the Business Case
How to quantify the ROI of adversarial AI testing and convince your leadership that proactive chatbot QA saves money.
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