Ranger reposted this
Why is no one talking about AI code creating massive product risk? AI coding tools are incredible at turning every engineer into a 10x engineer. But there’s a catch: when your small team is shipping more code than ever, the bottleneck shifts to QA. Suddenly you’ve got 10x the output and 0.1x the testing capacity. That imbalance creates massive risk. QA doesn’t scale linearly with lines of code. It scales exponentially with the complexity of your product surface area. Here’s a simple example: An AI agent adds a new checkout flow. It compiles. The happy-path test passes. Looks good, right? But what about the edge cases? Discount + gift card + expired credit card. Or users on old browsers. Or data migrations running mid-transaction. That’s where the slop leaks through—and where support tickets and lost revenue pile up. Multiply that by every “10x” engineer on your team and suddenly QA becomes the choke point. You’re moving fast, but you’re not sure what’s breaking until customers start telling you. Even frontier models know this. OpenAI’s GPT-5 system card highlights that agents evaluate themselves against whether Playwright tests pass. Good testing is the loop-closer. It's how both humans and machines learn what’s truly working. Think of it this way: In the race for coding greatness, everyone's fixated on building faster with AI. Meanwhile, nobody’s checking the brakes. QA is the pit crew — invisible until something explodes at 200 mph. That's what we're creating at Ranger: a QA agent that actually keeps pace with your code output, so you can scale faster without flaming out. AI can multiply your velocity or multiply your tech debt. The difference is whether you’ve got QA that can keep up.