About the Founder

After 25+ years in the trenches of performance testing, I've seen it all. From the early days of legacy systems to today's cloud-native architectures, I've spent my career as a consultant solving the most complex performance challenges across government agencies, financial institutions, and major retailers. Every project taught me something new, but more importantly, every project showed me the same recurring theme: the tools we rely on, while powerful, require an enormous amount of manual heavy lifting.

I've always been a tinkerer at heart. While other consultants would work within the constraints of existing tools, I found myself constantly asking "what if we could make this better?" This led me down countless rabbit holes—building custom plugins, automating workflows, and finding innovative ways to squeeze every ounce of efficiency from our testing arsenal.

But it wasn't until recent years, working deep within government systems, that I got my hands truly dirty with JMeter's infrastructure. What started as building custom plugins and integrations for my clients quickly evolved into something much bigger. Late nights and weekends became my playground for experimentation, diving under the hood of this incredible open-source tool that has quietly become the backbone of performance testing worldwide.

Here's the thing about JMeter—it's arguably the market-leading performance testing tool right now, and certainly the king of open-source solutions. But anyone who's spent serious time with it knows the reality: it's far from perfect. The manual correlation work, the script debugging marathons, the time spent on repetitive tasks that should be automated—it all adds up to enormous inefficiency.

That's when the lightbulb moment hit. I wasn't just at a crossroads in my career; I was at a "JMeter" point in the industry's evolution. Here was this phenomenal tool that so many testers depend on, but it was crying out for the intelligence that only AI could provide. The pain points I'd been experiencing for decades weren't unique to me—they were universal challenges that every performance tester faces daily.

So I made the leap. What began as a personal passion project to scratch my own itch has evolved into Peak 3000's revolutionary AI-powered JMeter plugin. Because sometimes the best solutions come from those who've lived with the problem the longest.