TestMu AI Blogs

Continuous verification proves AI-generated code behaves before it merges. Why green pipelines miss it, where the gate belongs, and how to keep it credible.

Executable specifications turn requirements into tests your build runs. Learn how they work, how they differ from test cases, and how to write and run them.

How to build an MCP server: architecture, STDIO vs Streamable HTTP transports, Python vs TypeScript SDK trade-offs, and step-by-step environment setup.

MCP vs API compared on discovery, state, and authorization, plus what the July 2026 spec revision changed and when to use each one in your AI agent stack.

11 QA bottlenecks that slow releases, how to measure which one is your real constraint, and the specific fix for each, with our own parallel-execution data.

Test automation vendors bill on six different units. See how each pricing model works, which costs stay off the quote, and how to normalize two rival quotes.

How Cursor rules work: where .mdc files live, which of the four rule types fires when, the surfaces rules never reach, and how to verify what Cursor writes.

Claude Code vs Antigravity compared on autonomy, artifacts, rate limits, cost, and test quality, plus the verification gap that both coding agents leave open.

Agent-native architecture makes every capability discoverable, callable, and parseable by an AI agent. Learn the four properties and how to verify them in CI.

AI code hallucinations are invented packages, APIs, and logic that look real but are not. Learn how they happen, how to catch them, and the tools that help.

AI code security keeps AI-generated code free of vulnerabilities, leaked secrets, and unsafe dependencies. Learn the risks, how to secure it, and the tools.

AI testing tools read your test fixtures, DOM, and CI logs. Learn what SOC 2 actually covers, where it stops for AI, and the exact questions to ask a vendor.

Agent-written code floods the pipeline with volume and risk. Learn how to build CI/CD gates that verify AI code before it merges, and the practices that scale.

The TestMu AI QA Job Board is a free hub where QA professionals register one profile, showcase AI and automation skills, and get discovered by hiring leaders.

SaaS testing explained: tenant isolation assertions, entitlement and billing states, testing without a release candidate, and choosing a browser matrix.

AI code review judges whether code looks correct; verification proves whether it works. See what each catches, where review fails, and how to combine them.

Claude MCP connects Claude to real tools through one open standard. Learn its architecture, primitives, setup, custom servers, and security in one guide.

Agent functional testing explained: how to derive test cases from a capability spec, partition natural-language inputs, and build a coverage model for agents.

Agent handoff testing catches context loss, orphaned tool calls, and delegation loops between AI agents. Learn the failure modes, assertions, and CI gates.

Make.com testing beyond Run Once: the bundle execution model, all five error-handler directives, testing routers and filters, and catching silent failures.