Particle Accelerator: A Particle41 Podcast
Your AI agent nailed the demo. But two weeks after going live, you're staring at support tickets you can't reproduce, cloud bills you can't explain, and behavior nobody predicted. In this episode of Particle Accelerator, our host Benjamin Johnson sits down with Pratik Verma, Founder and CEO of Okahu AI, to unpack exactly why AI agents break in production and what it takes to actually build reliable, observable agentic systems. Pratik has spent years at Microsoft and leading his own AI infrastructure companies. His open-source Monocle library and Okahu platform are purpose-built for the era of non-deterministic, LLM-powered agents, filling the gap that Datadog, New Relic, and traditional APM tools simply weren't designed for. In this conversation, Benjamin and Pratik get into: The most common root cause of agent failure (hint: it's not the model) Why the orchestration layer is where everything breaks Real-world example, how an Epson QA team cut triage from 30 hrs to 2 hrs with agents The structural difference between tracing a microservice vs. tracing an agent Evals vs. observability, what they are, why you need both, and how they connect How to instrument for token cost waste from day one MCP observability, what happens when you can't see inside the calling agent The self-healing agent loop, observability, coding agent, fix and repeat What software engineering looks like in 3 years Chapters: 00:00 - Intro & Guest Welcome 01:05 - Why agents fail: lab vs. production reality 02:28 - The orchestration layer: where flexibility becomes fragility 04:00 - The noun confusion failure mode (real-world example) 04:51 - The failure mode engineering leaders never see coming 06:29 - Why Datadog doesn't work for AI agents 11:22 - Instrumenting for cost: token budgets, session tracking & alerts 14:22 - Evals vs. observability: drawing the line 17:21 - From deterministic to non-deterministic systems 18:24 - Real-world case study: Epson QA agents 22:51 - Call center AI & observability signals in practice 30:07 - MCP observability and institutional knowledge loops 35:10 - The emerging agent economy and skill repositories 46:26 - What the next 3 years of AI looks like Pratik Verma, Founder & CEO, Okahu AI Connect with him: https://www.linkedin.com/in/pratikrverma/ Learn more at: https://www.okahu.ai/ Benjamin Johnson, Host, Particle Accelerator & CEO, Particle41 Connect with Benjamin on LinkedIn: https://www.linkedin.com/in/benjaminrjohnson/ Learn more about Particle41: https://particle41.com/ #AIAgents #MLOps #AIObservability #ProductionAI #EngineeringLeadership #TheParticleAccelerator #Particle41
111 episoder
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