E67: Monitoring the Probabilistic Stack with Alexis Gauba (Raindrop) скачать в хорошем качестве

E67: Monitoring the Probabilistic Stack with Alexis Gauba (Raindrop)

This week, we’re joined by Alexis Gauba, Co-Founder of Raindrop, an AI native observability platform built for agents in production. Alexis breaks down why operating agents is fundamentally different from monitoring traditional software. As systems shift from deterministic code to probabilistic behavior, dashboards alone are not enough. Teams need to detect unknown issues, track signals like forgetting, and understand long agent trajectories across millions of AI events. We discuss why agent observability has become essential over the past year, what makes agent infrastructure distinct from prior platform shifts, and when internal tooling stops scaling. Alexis also explains Raindrop’s approach to production monitoring, combining explicit signals with automated detection to help teams not just find issues, but fix them. Episode chapters: 2:05 - Founding Raindrop 3:54 - Building with Close Friends 5:44 - What Raindrop Actually Does 7:45 - The Reliability Challenge of Agents 9:55 - Monitoring Agents at Scale 14:45 - Experiencing the Pain Firsthand 18:00 - The Rise of Agent Infrastructure 22:17 - Internal AI Use Cases 24:07 - Hiring for Initiative and Ownership 28:30 - The Power of Multitasking 32:06 - Quick Fire Round This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo. This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.