Hassle-free test automation for SaaS startups. Powered by AI.
San Francisco, CA
Joined December 2012
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AI hype is real — 81% of software teams are using AI in their testing workflows. 📈
That’s just one of the things we learned when we surveyed 625 software developers and engineering leaders to learn about their test automation practices. 🧵
In QA, visible test failures are actually the safest thing that can happen.
A green checkmark only means something when you know how it got there.
hubs.ly/Q042Zprd0
Self-healing in QA sounds great…
until you realize you have no idea what was changed.
Self-healing should save you time, not hide regressions.
If the tool can’t show you exactly what was healed, it isn’t helping.
hubs.ly/Q042Zpf00
40 minutes from meeting → production-ready code.
We documented the exact AI-assisted workflow our team used to build a new architecture feature — including the moment a human had to override the AI.
Worth a read 👇
hubs.ly/Q043DnDk0
#SoftwareTesting #AI #DevTools
Some AI for QA tools brag about how many tests they can generate.
Hundreds!
Thousands!
Entire suites written in minutes!
Here’s the part they don’t mention: Most of those tests don’t matter.
Transparency matters: hubs.ly/Q042Zpjt0
QA needs determinism. Same inputs, same behavior, same results.
If your test runner is relying on probability, you’re introducing randomness right where you need certainty.
We wrote about why transparency matters in AI QA and what to look for: hubs.ly/Q042Znw00
Every QA tool could say their AI is “transparent.” But what does that actually mean?
True transparency is seeing what the AI did, why it did it, and what changed because of it.
If you’re trying to evaluate AI tools for QA, check out our guide: hubs.ly/Q041skPJ0
On delete-happy engineering culture, Rails longevity, technical debt, and microservice regret. Ou rengineering manager, Jay Tennier, tells it like it is on the #OnRails podcast with @robbyrussell: hubs.ly/Q03XG0tv0
Done > perfect, and other lessons from running a high-performing engineering team from our own Jay Tennier on the OnRails podcast with @robbyrussell: hubs.ly/Q03XG2rd0
What started as big promises is finally leading to big payoffs.
AI for QA has come a long way in one year.
Our updated report shows how.
🚀 Read The State of Software Test Automation in the Age of AI (2025) → hubs.ly/Q03YmftM0
#RainforestQA #AIforQA
Choosing Rails won't solve all your problems, but it's a good start to building a quality engineering culture. Hear more from our head of engineering on the OnRails podcast with @robbyrussell: hubs.ly/Q03XF-kQ0
Early AI tools didn’t save time — they just added complexity.
Now, AI is maturing enough to improve almost everything about how we approach QA.
We’ve relaunched our report with new commentary on how far the industry has come in one short year.
hubs.ly/Q03YmhsH0
What started as big promises is finally leading to big payoffs.
AI for QA has come a long way in one year.
Our updated report shows small teams are finally seeing AI pay off.
🚀 Read The State of Software Test Automation in the Age of AI (2025) → hubs.ly/Q03Ym4Yn0
We practice what we preach.
Hear more from Jay on the #OnRails podcast with @robbyrussell: hubs.ly/Q03XG0hV0
Rainforest QA retweeted
In the newest episode of On Rails, @robbyrussell speaks with @jaytennier, Engineering Manager at @rainforestqa, about maintaining a long-lived Rails monolith with a small team, why Rainforest pulled microservices back in, how they use adapters for third-party services, and why BigQuery handles their analytics load. Jay also shares their testing philosophy (“wet tests” > DRY), using dry-monads for complex flows, and how celebrating code deletion became part of their culture.
Listen to the full episode here, or wherever you get your podcasts: buzzsprout.com/2462975/episo…
Rainforest QA retweeted
Had a chance to dig in with @rainforestqa's @jaytennier about what it really takes to keep a long-lived Rails monolith thriving with a small team.
In the newest episode of On Rails, @robbyrussell speaks with @jaytennier, Engineering Manager at @rainforestqa, about maintaining a long-lived Rails monolith with a small team, why Rainforest pulled microservices back in, how they use adapters for third-party services, and why BigQuery handles their analytics load. Jay also shares their testing philosophy (“wet tests” > DRY), using dry-monads for complex flows, and how celebrating code deletion became part of their culture.
Listen to the full episode here, or wherever you get your podcasts: buzzsprout.com/2462975/episo…
For a genuinely candid look at technical debt, microservice regret, Rails longevity, delete-happy engineering culture, and building on top of a huge legacy system, check out this ep of #OnRails featuring our eng manager, Jay Tennier and @robbyrussell hubs.ly/Q03XFRNw0
ICYMI: We built AI Test Planner to go deeper.
Hours of AI-driven crawling maps every major feature and path in your app.
We'll help you conquer the “blank page problem” in QA.
Officially GA today!
Check it out: hubs.ly/Q03Wj3GV0
#RainforestQA #ProductAnnouncement
New from Rainforest QA 🚀
AI Test Planner is here.
AI crawls your app → maps every feature → delivers potential test plan.
You (the expert) take it from there.
Skip the blank page and start with confidence:
hubs.ly/Q03Wj1xH0
#RainforestQA #ProductAnnouncement #AIforQA
The blank-page problem in QA ends tomorrow.
Get ready for a new way to plan QA coverage.
Stay tuned — AI Test Planner launches tomorrow. 🚀
#RainforestQA #ProductAnnouncement
