Insights on API testing, shift-left, no-code automation, and CI/CD. Guides and best practices for modern QA teams.
Eighteen AI testing tools sorted into the five jobs they actually do — spec-driven generation, traffic recording, self-healing UI, authoring assistants and LLM evals — with what each is genuinely good at and what to verify in a trial.
Eighteen AI testing tools sorted into the five jobs they actually do — spec-driven generation, traffic recording, self-healing UI, authoring assistants and LLM evals — with what each is genuinely good at and what to verify in a trial.
How to gate AI-assisted development — why line coverage stops meaning anything, the four checks that hold, and where human review should be spent when volume outruns it.
The agentic QA tool landscape in four groups, what agentic actually means, the four questions that separate a usable tool from a demo, and how to put one in a pipeline without losing determinism.
The 10 best API mocking and service virtualization tools in 2026, compared across spec-driven, standalone stub server, and enterprise virtualization categories.
What an API testing framework actually is, the three real categories to choose between, and a practical decision framework based on team language, CI/CD needs, and who should be able to read the tests.
How to build an LLM eval suite that actually catches regressions — dataset design, scoring functions, LLM-as-judge calibration, thresholds, CI gating and the tooling landscape.
The 11 best API load testing tools in 2026, compared on scripting language, protocol support, CI/CD fit, and pricing model — free/open source and commercial.
A practical method for testing LLM-backed features — deterministic shell versus probabilistic core, invariant tests, golden-set evals, regression on prompt changes, and what to run in CI.
The MCP threat model and the test cases that cover it — tool poisoning, confused deputy, token passthrough, session hijacking, DNS rebinding and excessive agency, with runnable assertions for each.
