QA Wolf

TFW one of your customers launches something amazing that you helped them perfect. 🥰 QA Wolf helped Brilliant: ⏩ Reduce QA cycles from 24 hours to 5 minutes. ⏩ Up their testing capacity by the equivalent of 4–5 additional QA engineers. ⏩ Detect 8–10 bugs per month saving millions of dollars in top-line revenue Read our case study with Brilliant below -- link in comments!

Unpopular opinion: AI coding tools might be creating more -10x engineers than 10x ones. AI is making everyone faster. But faster at what? AI-generated code has 1.7x more bugs than human-written code. So, when your team is shipping at 2x the velocity, they might also be shipping at 2x the risk. Enter the -10x engineer. They're not the one who can't keep up. They're the one moving the fastest. Shipping the most. Right up until they cause a site outage that costs millions. Or refactor the auth system on a Friday and take down login for half your users. The original 10x engineer was exceptional because of judgment. Knowing which shortcuts were landmines. Knowing when to slow down. Knowing what to throw away entirely. AI can 10x your output. It cannot 10x your judgment. Learn how to protect your codebase from -10x engineers in our latest piece. Link in the comments.

Everyone's talking about how AI is creating 10x engineers (or if you’re the founder of ClickUp, 100x engineers). Nobody's talking about the -10x engineers it’s also creating. They’re the type who loves coding with AI but doesn’t love the verification part as much. They don't break one thing. They break things at scale, at speed, and across systems. It’s the engineer who refactors the auth system on a Friday and takes the site down. Or the one who makes changes to a major service that breaks a dependency a week later. We started calling this the -10x engineer at QA Wolf. And they're the completely foreseeable consequence of how the industry adopted AI for coding. The math is simple: AI-generated code has 1.7x more issues than human-written code. And the volume of code AI makes possible outpaces the capacity of our normal verification processes. If your team is adopting AI coding tools without also: → Raising the bar on what "reviewed" actually means → Running comprehensive automated E2E tests that can block releases → Using feature flags and canary deployments to limit blast radius → Teaching engineers how to interrogate AI output, not just use it ...you're not creating 10x engineers. You're often just making mistakes faster. Learn more in our latest piece about how to spot -10x engineers and protect your team from them. https://lnkd.in/geePU3vM

They're not angry. They're just disappointed.

Code reviews are broken. And that's fueling a verification crisis. Here's what's happened to the average PR because of AI coding agents: → 70% more issues per PR → 154% longer diffs → 91% longer review times Same number of human reviewers. Same cognitive limits. The result? A 23.5% increase in incidents per PR and a 30% jump in change failure rates. AI code review tools help — but even the best ones miss 50% of bugs, according to independent benchmarks. And the bugs AI generates most often aren't likely to be caught in a review: → Integration failures → Silent data loss → Multi-step workflows that pass review and break in prod The fix isn't a better review process. It's more layers of verification. Like automated end-to-end testing that runs on every PR, covers every critical user flow, and blocks broken releases before they ship. We write about the crisis in the link in the comments and the need for more quality gates that scale with the speed of AI development.

QA Wolf now lets you feed any image, video, or audio file directly into the camera or microphone on real iPhones and iPads. So if your app does any of this: - Scans a receipt, then converts it to a PDF or extracts text with OCR - Identifies a song playing on the radio - Records and posts a video on social media - Scans barcodes and QR codes  - Hosts a video chat and validates call quality …you can test it the way your users will actually experience it. Here’s a look at Cameo using our video injection technology to test their iOS app. If you’re missing coverage for your complex workflows, schedule a demo to see our agentic testing platform in action.

QA Wolf now supports VPN configuration for iOS app testing. If your app serves different content by region, or your backend lives behind a private network, you've always had to work around your testing platform to cover those cases. Now you don't. VPN sessions spin up automatically at the start of each test run and tear down when it's done—no manual setup, no leftover state, no extra overhead when you want to run your suite. Come schedule a demo of our agentic testing platform, including 100% parallel run infrastructure for iOS apps, Android apps, and web apps. Read more about it here: https://lnkd.in/eGVbCrBp

Hirevue wanted to ship faster without pulling engineers away from building the product. That’s why they partnered with QA Wolf. Before that, a legacy QA process built on Selenium and manual checks created constant context switching, uneven coverage, and slower releases across a complex global stack. The result: Hirevue doubled release velocity from bi-weekly to weekly releases, saved 10+ hours of manual testing per release per region, and achieved FedRAMP authorization for a new product in under 9 months. “With QA Wolf we were able to repurpose our QA expenses into innovation and better quality product delivery.” — Alberto Silveira, CTO Read the full case study: https://lnkd.in/g25eyqcu

Your PRs are moving faster than your QA can keep up. For engineering orgs pushing toward daily releases, QA becomes the bottleneck. Traditional test coverage doesn't scale with today's shipping velocity. Confidence drops. Flaky tests pile up. Engineers spend cycles maintaining coverage instead of building. If you're a CTO or engineering leader balancing speed and quality, don't miss this live look at how QA Wolf ships daily without sacrificing release confidence. See It in Action: AI-Powered QA for Daily Releases 🗓️ Thursday, April 30th @ 12 PM PT QA Wolf co-founder & CEO Jon Perl joins host Caleb Masters to show QA Wolf running the testing lifecycle. 30-minute live demo + Q&A: - Mapping AI autonomously identifies user flows - Automation AI generates deterministic test code - Full test runs across web, iOS, and Android in minutes, not hours Save your seat: https://lnkd.in/gY3NZCHZ

Now you can run E2E tests on any combination of device and OS, including tablets, foldables, even Point of Sale systems. The great thing about Android is that it runs on just about anything. But different device specs (size, memory, processor) and different OS versions, from stock Android to OEM skins, can change the behavior of your app in fun and baffling ways. Being able to pick and choose the exact configuration of device and OS that your users have in their hands gives you more confidence in your releases so you can ship more often. Come schedule a demo of our agentic testing platform, including the 100% parallel run infrastructure for Android, iOS, and web apps. And if you’re interested in how we designed our infrastructure, check out this post: https://lnkd.in/eN5bQBjJ