TestMu AI Blogs

Inbound and outbound phone agents are two test problems. See what changes at turn zero, which legal duties you can assert, and how to split one phone suite.

LLM evals score a model. End-to-end agent testing gates a build. See what each one proves, where they disagree, and how to run both without duplicating work.

A pass-rate delta hides most of what a model upgrade actually changed. See how to measure churn, detect backend moves, and gate on cost and latency as well.

OpenAI says gpt-realtime scores just 30.5% on instruction following. Learn what to assert when testing an OpenAI Realtime voice agent, and how to gate it in CI.

Agentic SDLC and STLC diverge on one thing: verifiability. Learn what AI agents change in every phase, which exit criteria still hold, and how to adopt them.

The agentic testing life cycle points the QE loop at the agent itself. See the six phases, what a verdict proves, and the gap between tested and verified.

The Test Deduplication Agent scans your Test Manager project for duplicate test cases and scores every match. Archive the ones you are unsure about.

Test, develop, or just play: 15 iPhone emulators for PC, Mac, and cloud in 2026, what each one does best, what's free, and the trade-offs to know.

Compare 6 AI mobile app testing CLIs on what each returns to CI: device state, screenshots, or a pass/fail verdict. Verified commands, real runs, honest limits.

Compare 7 AI browser testing CLIs on what each returns to CI: page state, screenshots, or a pass/fail verdict. Verified commands, real runs, and honest limits.

Compare 9 Playwright CLI alternatives, from Cypress and WebdriverIO to agentic CLIs like Kane CLI, Shortest, and Hercules. Commands, fit, and tradeoffs.

Compare 5 Playwright MCP alternatives for AI agents, from Chrome DevTools MCP to Kane CLI and Mobile MCP, with tool counts, context cost, and setup commands.

Andrew Knight of Cycle Labs on the AI stack, plan-generate-heal, spec-driven development, and a live build that produced 13 passing Playwright login tests.

Ojus Save of Render on why the request is the wrong unit to price an agent run, what the admission event commits you to, and how to budget the run instead.

Angela Cutulenco on the four CMDB layers an AI agent cannot read, why an empty field looks like a low rating, and what to ask instead of fixing your data.

Three banking practitioners on the filters that decide agent versus copilot, testing behaviour as a distribution, and why data beats legacy as the real blocker.

Sumit Shatwara of Cognition on the autonomy ladder, the golden question behind every delegation, and why your test suite caps how much you can safely hand over.

Dr. Lisa Dieker on co-designing AI agents with disabled users, why Project RAISE dropped facial tracking, and why compliance is not the same as accessibility.

A panel with nunu.ai and Tirta Ventures on vision-based mobile agents: where they match humans, where they do not, and what QA becomes when agents run at scale.

Mallika Fernandes of Accenture on the five stages of AI reliance, why code got cheap, and the Concorde lesson waiting for teams that ignore token economics.