In the age of generative AI, enterprise teams have three options: extend their legacy data and ML platforms, rely on APIs, or build a custom unified platform for generative AI. For teams choosing to build their own custom AI platform, the PARK Stack (PyTorch, AI Frontier Models, Ray, Kubernetes) is quickly becoming the industry standard.Continue reading “What is the PARK Stack?”
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The PARK Stack Is Becoming the Standard for Production AI
In a previous article, I argued that the open-source project Ray has become the compute substrate many modern AI platforms are standardizing on — bridging model development, data pipelines, training, and serving without locking into a single vendor. Ray Summit is my favorite venue for pressure-testing that thesis because it’s where infrastructure and platform teamsContinue reading “The PARK Stack Is Becoming the Standard for Production AI”
Trends shaping the future of AI infrastructure
Subscribe • Previous Issues The PARK Stack Is Becoming the Standard for Production AI In a previous article, I argued that the open-source project Ray has become the compute substrate many modern AI platforms are standardizing on — bridging model development, data pipelines, training, and serving without locking into a single vendor. Ray Summit is my favoriteContinue reading “Trends shaping the future of AI infrastructure”
Boom, Bubble, or Bust? How to Build a Resilient AI Business
Comparisons to the dot-com bust are common but this AI boom rests on short-cycle hardware. Frontier training chases each GPU generation, rendering last year’s chips economically obsolete for training even as they stay serviceable for inference — forcing relentless reinvestment. This dynamic is amplified by a unique, self-referential financial architecture where capital circulates between techContinue reading “Boom, Bubble, or Bust? How to Build a Resilient AI Business”
How to build an AI business that survives the bubble
Subscribe • Previous Issues Boom, Bubble, or Bust? How to Build a Resilient AI Business Comparisons to the dot-com bust are common but this AI boom rests on short-cycle hardware. Frontier training chases each GPU generation, rendering last year’s chips economically obsolete for training even as they stay serviceable for inference — forcing relentless reinvestment. This dynamicContinue reading “How to build an AI business that survives the bubble”
Reimagining the Database for AI Agents
In a recent piece, I explored the growing mismatch between our existing data infrastructure and the demands of emerging AI agents. Since then, I have had the opportunity to speak with some founders and engineering leaders who are tackling this challenge directly. Their work confirms that the rise of agentic AI is not just anContinue reading “Reimagining the Database for AI Agents”
Inside the race to build agent-native databases
Subscribe • Previous Issues Reimagining the Database for AI Agents In a recent piece, I explored the growing mismatch between our existing data infrastructure and the demands of emerging AI agents. Since then, I have had the opportunity to speak with some founders and engineering leaders who are tackling this challenge directly. Their work confirms that theContinue reading “Inside the race to build agent-native databases”
Agentic AI Applications: A Field Guide
If you’ve been captivated by demos of agentic AI, you’ve likely also encountered the immense challenge of making them work in production. While demos promise unprecedented capabilities, the path to building reliable, scalable, and cost-effective agents is fraught with challenges. This field guide is for teams navigating that chasm, mapping the terrain of architecture patterns,Continue reading “Agentic AI Applications: A Field Guide”
Agentic AI Applications: A Field Guide
Subscribe • Previous Issues Hard Truths About AI Agents: What Works, What Doesn’t, and Why If you’ve been captivated by demos of agentic AI, you’ve likely also encountered the immense challenge of making them work in production. While demos promise unprecedented capabilities, the path to building reliable, scalable, and cost-effective agents is fraught with challenges. This fieldContinue reading “Agentic AI Applications: A Field Guide”
Autonomous Agents are Here. What Does It Mean for Your Data?
By Ciro Greco and Ben Lorica. A striking factoid emerges from Anthropic’s latest Economic Index report: directive AI usage, where users delegate complete tasks to Claude, has surged from 27% to 39% on Claude.ai in just eight months. Among API customers building production systems, that figure jumps to an overwhelming 77%. This rapid shift fromContinue reading “Autonomous Agents are Here. What Does It Mean for Your Data?”