Guides, research, and field reports on AI agent testing, adversarial security, and conversational AI quality. Findings are test evidence, not a certification.

Spot-checking chats, screenshots, and last month's eval are not this week's product. The job is a written weekly brief with transcript-backed findings.
Spot-checking chats, screenshots, and last month's eval are not this week's product. The job is a written weekly brief with transcript-backed findings.
Read moreA green Git repo is not a stable LLM product. Back-to-school traffic and floating model aliases changed what you shipped this week, with no pull request.
Read moreA code freeze locks Git before Labor Day. Vendor defaults and routing weights keep moving. Your last observed behavior is already a stale baseline.
Read moreA quiet repo is not proof production is unchanged. Post-Black Hat MCP write-ups show capability-graph drift with zero commits.
Read moreThe LiteLLM breach exposed more than credentials. It showed why AI reliability controls must detect behavior changes beyond application code diffs.
Read moreA Claude agent exploited a gym booking workflow. The real lesson is that permissions, tools, and defaults now shape product reliability.
Read moreExplore how GPT-4's new features impact compliance and security in AI development, and how to adapt your workflows accordingly.
Read moreRising cybercrime demands that organizations integrate security into AI development, not as an afterthought but as a core component.
Read moreLabor Day week Git stays frozen while the September 1 vendor control plane still ships. A pinned model ID and green main are not the same product.
Read moreAnthropic's Claude Code default change exposes a control gap: AI behavior can shift without a commit, while CI keeps checking yesterday's assumptions.
Read moreThe rush to integrate AI in CI/CD pipelines is real, but are we sacrificing quality for speed? Hereβs how to maintain standards amidst innovation.
Read moreCompanies are accumulating AI operations debt faster than they realize. The rush to deploy is creating infrastructure complexity that traditional DevOps can't handle.
Read moreGitHub'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a tipping point where AI generates more enterprise code than humans write, but QA infrastructure remains dangerously outdated.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 moreMicrosoft's latest AI pricing changes expose the uncomfortable truth: enterprise AI costs don't scale like traditional software, and CFOs are demanding answers.
Read moreHow to quantify the ROI of adversarial AI testing and convince your leadership that proactive chatbot QA saves money.
Read more