Uploaded May 2026 | Updated September 2026, 1 hour ago
You give your developers AI coding tools. The speed-up is real. A few quarters later the bill lands on the CFO's desk and nobody knows where the spike came from. That's just programming. Now imagine the rest of the org using AI at the same rate.
@thecote walks through three things he's hearing from enterprise IT execs right now: the cost surprise (AI FinOps as a thing whether or not anyone's named it yet), the use-case gap (programming and customer service are obvious, the next eight are not), and the control problem (identity, performance, compliance - the boring stuff that always gets retrofitted instead of built in).
Interested in a platform that can help you with enterprise-y excellence? Just TryTanzu.ai
Key topics:
- Why the AI cost surprise looks exactly like the 2010s public cloud cost surprise, and what AI FinOps will probably have to become
- Why programming and customer service dominate the use-case list, and what's actually blocking the next ten
- Why forward-deployed engineering teams keep showing up at the enterprise AI use-case problem - and what that says about how hard the integration work really is
- Why controls (identity, compliance, performance, cost metering) keep getting bolted on after the fact, and why this time has to be different
- The OAuth-and-MCP authentication mess, and what it means for tracking who authorized what across an agent stack
- Why we're past the phase of amazement and into the phase of running AI as production infrastructure
Rising token-usage chart shown in the video, via Goldman Sachs: goldmansachs.com/insights/articles/ai-agents-forecast-to-boost-tech-cash-flow-as-usage-soars?ref=cote.io
Index:
0:00 Enterprise AI Pain Points
0:07 Cost Shock Hits
0:43 Beyond Coding Spend
1:07 Hunting Real Use Cases
1:53 Why Use Cases Stall
2:30 Control and Governance
3:12 Cost Monitoring and Cutbacks
3:39 Identity and Performance Mess
4:14 From Demos to Business Processes
4:37 Better TryTanzu.ai
You give your developers AI coding tools. The speed-up is real. A few quarters later the bill lands on the CFO's desk and nobody knows where the spike came from. That's just programming. Now imagine the rest of the org using AI at the same rate.
@thecote walks through three things he's hearing from enterprise IT execs right now: the cost surprise (AI FinOps as a thing whether or not anyone's named it yet), the use-case gap (programming and customer service are obvious, the next eight are not), and the control problem (identity, performance, compliance - the boring stuff that always gets retrofitted instead of built in).
Interested in a platform that can help you with enterprise-y excellence? Just TryTanzu.ai
Key topics:
- Why the AI cost surprise looks exactly like the 2010s public cloud cost surprise, and what AI FinOps will probably have to become
- Why programming and customer service dominate the use-case list, and what's actually blocking the next ten
- Why forward-deployed engineering teams keep showing up at the enterprise AI use-case problem - and what that says about how hard the integration work really is
- Why controls (identity, compliance, performance, cost metering) keep getting bolted on after the fact, and why this time has to be different
- The OAuth-and-MCP authentication mess, and what it means for tracking who authorized what across an agent stack
- Why we're past the phase of amazement and into the phase of running AI as production infrastructure
Rising token-usage chart shown in the video, via Goldman Sachs: goldmansachs.com/insights/articles/ai-agents-forecast-to-boost-tech-cash-flow-as-usage-soars?ref=cote.io
Index:
0:00 Enterprise AI Pain Points
0:07 Cost Shock Hits
0:43 Beyond Coding Spend
1:07 Hunting Real Use Cases
1:53 Why Use Cases Stall
2:30 Control and Governance
3:12 Cost Monitoring and Cutbacks
3:39 Identity and Performance Mess
4:14 From Demos to Business Processes
4:37 Better TryTanzu.ai
