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"It's been so long since I've been sleep deprived and over-caffeinated, yet so motivated."
That's what I posted in our internal slack channel after my first week joining Resolve AI as Director of Sales (West). Friends from MongoDB and New Relic have been asking me the same question: "Why change right now? And why join Resolve AI?"
The answer isn't what you'd expect.
After 10 years building and scaling at MongoDB and New Relic, I had a comfortable path ahead and the satisfaction of working with technologies that genuinely help engineering teams.
Scaling MongoDB, I saw how production systems grew exponentially more complex with every new service and dependency, just by the sheer amount of data every enterprise generated. During my time at New Relic, I helped our customers monitor and observe their production systems, helping them know when something was wrong. But I also saw the massive untapped potential in helping them understand what’s wrong, why, and how to fix it.
Now, I realized we are at an inflection point: AI changed everything about how we build software, but didn’t move the needle on how we troubleshoot and run it.
We're generating 10X more code and creating 100X more complex systems, but we're still debugging incidents the same way we did a decade ago. Dashboard by dashboard. Alert by alert. Human intuition struggling to keep pace against exponential complexity.
The companies that figure out AI-native engineering first won't just move faster. They'll make traditional approaches look obsolete.
Look, when you've spent a decade in sales at two successful companies, you get approached with opportunities constantly. For me to actually leave, it had to be something special.
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When I told the Resolve AI team I'm "seeking partners as we build and ride this rocket ship together," I meant it. This isn't about individual sales targets. This is about collectively working with our customers to fundamentally change how engineering teams operate.
At Resolve AI, our mission is to help keep the world’s software running. We're defining the category that every AI-forward engineering team will eventually need. Every company faces exponential complexity in production systems, especially with AI assisting in writing software. The question is whether you’ll adopt it before or after their competition.
From a go-to-market perspective, we're focused on partnering with organizations where reliability and uptime are critical business outcomes. These are companies where engineering velocity defines market position and where troubleshooting is a critical blocker.
We have the chance to build a generational company by solving a problem that touches every company building software. I couldn't be more fired up. If this problem sounds interesting and challenging for you, we’re looking to expand our team. Check out the open roles here.
