Come learn how
QA meets AI.
Structured lessons, deep-dive articles and a podcast: for testing software with AI, and testing AI itself.
AI Wrote the Test Cases: Now Who Tests the Test Cases?
Turning a user story into Gherkin scenarios with an LLM sounds like free QA coverage. Ungraded, it's also a great way to ship a test suite that looks thorough and only covers the happy path. A coverage rubric for the generator itself.
Read itDeep-dives with runnable code
Long-form engineering write-ups: LLM evals, regression harnesses, self-healing suites. Every post ships with code you can run.
Browse articlesVideos, a podcast and guided paths
Watch, listen, and build. Structured lessons that take you from testing basics to shipping LLM evals in CI.
Start learningHands-on help for your team
Consulting, eval setup and workshops from an engineer who does this in production, not in slides.
See servicesFresh from the lab.
AI Wrote the Test Cases: Now Who Tests the Test Cases?
Turning a user story into Gherkin scenarios with an LLM sounds like free QA coverage. Ungraded, it's also a great way to ship a test suite that looks thorough and only covers the happy path. A coverage rubric for the generator itself.
Catching LLM Hallucinations With a Regression Harness
A pytest harness that runs the same prompts across model calls, snapshots the outputs, and flags drift automatically, so a silent hallucination regression doesn't ship unnoticed.
Chaos Monkey for Agents: Breaking Tool Calls on Purpose
The Testing LangGraph Agents post proved the graph is wired correctly under ideal conditions. Real tools fail: timeouts, malformed responses, outages. Inject those failures on purpose and verify the agent degrades gracefully instead of crashing or looping forever.
LLM evaluation, demystified
Ground-truth sets, judges, thresholds: how to score what can’t be asserted.
Automation that maintains itself
Self-healing suites, AI-assisted test generation, and where to draw the line.
CI patterns that scale
Nightly drift checks, model-upgrade gates, and builds that fail for good reasons.
No hype, receipts included
Every claim comes with code, honest limitations, and a way to reproduce it.