TestMu AI Blogs

How to run E2E tests in pull requests without stalling code review: set a time budget, control flakiness, gate on real devices, and show reviewers the cause.

Measured defect rates for AI-generated code range from 8% to 68% depending on what each study counted. What actually breaks, and which test gate catches it.

Claude Code is Anthropic's agentic coding tool for the terminal. Learn how a session works, where it runs, and how skills, MCP, hooks and subagents extend it.

Codex skills put your team's conventions in a SKILL.md the agent loads on demand. How to write one, make it trigger reliably, and verify Codex followed it.

Cursor, Copilot, and Codex all read plain markdown instruction files. The exact paths, one AGENTS.md that covers all three, and the command that verifies work.

Agent-native CI explained: the diagnosis loop, the workflow_run architecture, guardrails against a hidden regression, and what still needs a human to decide.

Agentic AI architecture splits planner, generator, and evaluator roles. Why a generator cannot grade its own output, and how to wire an independent evaluator.

Agentic automation gives software a goal instead of a script. See how it works, where it fits, and what our cloud runs showed actually breaks when a UI changes.

Four measured agent-run browser checks against plain CI: real durations, where each model costs more, and the line items that never reach either invoice.

AGENTS.md works best as a testing contract: the exact commands an agent must run, what done means, how to handle a failing suite, and what it must never touch.

Claude Code hooks fire on lifecycle events, not on model judgement. Events, matcher syntax, exit codes, and how to run a real browser check from a Stop hook.

Claude Code plugins bundle skills, agents, hooks, and MCP servers into one installable unit. Learn plugin.json, marketplaces, install scopes, and verification.

Claude Code subagents explained: context isolation, the complete frontmatter reference, where definitions live, and how to verify what one actually shipped.

Codex CLI runs OpenAI's coding agent in your terminal. Install it, choose the right sandbox and approval modes, run it in CI, and verify what it actually ships.

Seven plugins that let a coding agent generate and run tests, ranked on capability and adoption, with GitHub star counts and licences verified in August 2026.

Cursor CLI explained: installing it on every platform, the three modes, the full command reference, a real CI example, and how to verify what it actually did.

Debug E2E test failures faster: capture the right artifacts, tell a real bug from a flake, fix CI-only failures, and know when to retry or quarantine a test.

Antigravity CLI and Gemini CLI both write code and stream NDJSON, and neither opens a browser. Run them headless and chain a real browser check on the end.

What the GitHub MCP server does, which toolsets it exposes, how to scope access, and exactly where it stops when an AI agent tries to verify a change.

How to scale test automation with AI: five verified strategies, the maturity roadmap from pilot to enterprise scale, and where it still needs human judgment.