Uploaded February 2026 | Updated September 2026, 8 hours ago
Enterprise AI Has a Product-Market Fit Problem. Enterprise AI isn't stalled because the models are weak. It's stalled because we haven't discovered product-market fit inside the enterprise yet.
You can hear more details in my co-worker Purnima Padmanabhan's talk at AI in Finance Summit NYC in April: ny-ai-finance.re-work.co
You don't find real AI value by theorizing in workshops. You find it by running experiments for months inside your actual systems - against real data - in a governed environment.
That requires a platform.
Without one, AI pilots turn into disconnected experiments, shadow infrastructure, and compliance risk. With one, experimentation compounds into institutional learning.
In this video, I break down:
- Why enterprise AI is still in discovery mode
- Why experimentation must be long-running, not one-off
- How governance enables innovation instead of blocking it
- Why a secure platform foundation is the baseline for AI ROI
If you're thinking about AI strategy, platform engineering, or how to make AI experimentation safe and scalable, this is where to start.
Featured:
- Sean Goedecke - seangoedecke.com/ai-products
- Product Manager Playbook - vmware.com/docs/white-paper-vmware-tanzu-labs-product-manager-playbook
- Free book! - The Business Bottleneck - go-vmware.broadcom.com/01-248_reg_the-business-bottleneck
- What is AI Middleware, and Why You Need It - blogs.vmware.com/tanzu/what-is-ai-middleware-and-why-you-need-it
- Three Questions That Will Define AI In 2026 - forrester.com/blogs/three-questions-that-will-define-ai-in-2026
- Building an Enterprise MCP Server Marketplace with Tanzu Platform - blogs.vmware.com/tanzu/building-an-enterprise-mcp-server-marketplace-with-tanzu-platform
#EnterpriseAI #PlatformEngineering #TanzuPlatform #AIGovernance #CloudFoundry #VMware #Tanzu
Enterprise AI Has a Product-Market Fit Problem. Enterprise AI isn't stalled because the models are weak. It's stalled because we haven't discovered product-market fit inside the enterprise yet.
You can hear more details in my co-worker Purnima Padmanabhan's talk at AI in Finance Summit NYC in April: ny-ai-finance.re-work.co
You don't find real AI value by theorizing in workshops. You find it by running experiments for months inside your actual systems - against real data - in a governed environment.
That requires a platform.
Without one, AI pilots turn into disconnected experiments, shadow infrastructure, and compliance risk. With one, experimentation compounds into institutional learning.
In this video, I break down:
- Why enterprise AI is still in discovery mode
- Why experimentation must be long-running, not one-off
- How governance enables innovation instead of blocking it
- Why a secure platform foundation is the baseline for AI ROI
If you're thinking about AI strategy, platform engineering, or how to make AI experimentation safe and scalable, this is where to start.
Featured:
- Sean Goedecke - seangoedecke.com/ai-products
- Product Manager Playbook - vmware.com/docs/white-paper-vmware-tanzu-labs-product-manager-playbook
- Free book! - The Business Bottleneck - go-vmware.broadcom.com/01-248_reg_the-business-bottleneck
- What is AI Middleware, and Why You Need It - blogs.vmware.com/tanzu/what-is-ai-middleware-and-why-you-need-it
- Three Questions That Will Define AI In 2026 - forrester.com/blogs/three-questions-that-will-define-ai-in-2026
- Building an Enterprise MCP Server Marketplace with Tanzu Platform - blogs.vmware.com/tanzu/building-an-enterprise-mcp-server-marketplace-with-tanzu-platform
#EnterpriseAI #PlatformEngineering #TanzuPlatform #AIGovernance #CloudFoundry #VMware #Tanzu
