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Elliot Gunton, Qian Li, Alan Nichol & 1 more speaker · Jul 8th, 2025
No YAML? No Problem: Orchestrate Kubernetes Workflows the Easy Way with Python
Sick of writing orchestration logic in YAML? You’re not alone. Discover how Hera, the Python SDK for Argo Workflows, lets you express complex Kubernetes workflows using clean, testable Python code. Keep your business logic and orchestration logic in one place — no indentation nightmares required.
Building Reliable AI Applications with Durable Workflows
Chaining functions together is easy. Keeping AI workflows running when things go sideways? That’s the hard part. This talk introduces durable workflows — systems that checkpoint state, recover automatically, and gracefully handle everything from human delays to API flakiness. You’ll see real examples of AI pipelines that stay resilient in production.
Process Calling: Agentic Tools Need State
Function calling gave LLMs a way to "do" things — but it’s not enough. When you’re building agents for customer-facing use cases, stateless abstractions fall short fast. Learn why the future of agentic tooling is process-based, not function-based, and what it means to build agents that remember, recover, and reliably finish what they start.
# Argo Workflows
# Kubernetes
# YAML
# LLM
# Pipekit
# DBOS, Inc
# Rasa
Soham Chatterjee · Jul 8th, 2025
Anthropic's Model Context Protocol (MCP) is revolutionizing AI integration by providing a standardized way for LLMs to connect with external systems. Learn the core concepts, architecture, and build a practical Hacker News server that extends Claude's capabilities with real-time data access.
# MCP
# LLMs
# AI Applications
Kai Wang & Demetrios Brinkmann · Jul 4th, 2025
Kai Wang joins the MLOps Community podcast LIVE to share how Uber built and scaled its ML platform, Michelangelo. From mission-critical models to tools for both beginners and experts, he walks us through Uber’s AI playbook—and teases plans to open-source parts of it.
# Uber
# AI
# Machine Learning
Nikolaus West & Demetrios Brinkmann · Jul 1st, 2025
Nikolaus West, CEO of Rerun, breaks down the challenges and opportunities of physical AI—AI that interacts with the real world. He explains why traditional software falls short in dynamic environments and how visualization, adaptability, and better tooling are key to making robotics and spatial computing more practical.
# Physical AI
# Robotics
# Rerun
Médéric Hurier · Jul 1st, 2025
The slow, batch-processing nature of the data lake is obsolete for modern Generative AI, which requires instant access to fresh data. In this article, the author proposes a shift away from centralizing data, advocating instead for an API-first approach. This allows AI applications to directly and quickly access live data from its source, enabling truly real-time, responsive features.
# AI
# Data Science
# Generative AI Tools
# Machine Learning
# Programming
Kostas Pardalis, Yoni Michael & Demetrios Brinkmann · Jun 27th, 2025
LLMs are reshaping the future of data and AI—and ignoring them might just be career malpractice. Yoni Michael and Kostas Pardalis unpack what’s breaking, what’s emerging, and why inference is becoming the new heartbeat of the data pipeline.
# LLM
# AI infrastructure
# Typedef
Greg Kamradt & Demetrios Brinkmann · Jun 24th, 2025
What makes a good AI benchmark? Greg Kamradt joins Demetrios to break it down—from human-easy, AI-hard puzzles to wild new games that test how fast models can truly learn. They talk hidden datasets, compute tradeoffs, and why benchmarks might be our best bet for tracking progress toward AGI. It’s nerdy, strategic, and surprisingly philosophical.
# AI Benchmark
# ARC AGI
# Data Independent
Deepti Srivastava & Demetrios Brinkmann · Jun 20th, 2025
I’m sure the MLOps community is probably aware – it's tough to make AI work in enterprises for many reasons, from data silos, data privacy and security concerns, to going from POCs to production applications. But one of the biggest challenges facing businesses today, that I particularly care about, is how to unlock the true potential of AI by leveraging a company’s operational business data. At Snow Leopard, we aim to bridge the gap between AI systems and critical business data that is locked away in databases, data warehouses, and other API-based systems, so enterprises can use live business data from any data source – whether it's database, warehouse, or APIs – in real time and on demand, natively. In this interview, I'd like to cover Snow Leopard’s intelligent data retrieval approach that can leverage business data directly and on-demand to make AI work.
# AI and Business Data
# LLM
# Snow Leopard AI
Sebastián Ramírez & Demetrios Brinkmann · Jun 17th, 2025
The creator of FastAPI is back with a new chapter—FastAPI Cloud. From building one of the most loved dev tools to launching a company, Sebastián Ramírez shares how open source, developer experience, and a dash of humor are shaping the future of APIs.
# FastAPI
# FastAPI Cloud
# FastAPI Labs
Shreya Shankar, Willem Pienaar & Demetrios Brinkmann · Jun 13th, 2025
Willem Pienaar and Shreya Shankar discuss the challenge of evaluating agents in production where "ground truth" is ambiguous and subjective user feedback isn't enough to improve performance.
The discussion breaks down the three "gulfs" of human-AI interaction—Specification, Generalization, and Comprehension—and their impact on agent success.
Willem and Shreya cover the necessity of moving the human "out of the loop" for feedback, creating faster learning cycles through implicit signals rather than direct, manual review.
The conversation details practical evaluation techniques, including analyzing task failures with heat maps and the trade-offs of using simulated environments for testing.
Willem and Shreya address the reality of a "performance ceiling" for AI and the importance of categorizing problems your agent can, can learn to, or will likely never be able to solve.
# Production failure
# AI system
# Observability