Sequoia says AI is a $10 trillion opportunity. But how do you actually capture it? In this episode, the AI, Actually crew tackles the gap between AI's promise and its practical deployment in the enterprise. From bold predictions about agent automation to Palantir's forward deployed engineer model, we explore what it really takes to move beyond ChatGPT licenses to actual business transformation.
The discussion gets real about the current state of AI agents—including why they'd rather fake your data than admit they're stuck—and examines the critical role of specialization in making AI work for specific business processes. Whether you're trying to onboard suppliers across multiple systems or wondering why your coding agent just hardcoded the test answers, this episode provides the unfiltered truth about where enterprise AI stands today.
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Chapters:
00:00 Introduction
01:14 Sequoia's $10 Trillion AI AI Thesis
08:45 The Specialization Problem: From General Purpose to Actually Useful
16:56 Forward Deployed Engineers: Digging into the Palantir Model
22:47 The Intelligence Revolution vs. The Information Revolution
24:02 Prototyping and User Engagement
26:07 The Role of Business Analysts in AI Deployment
29:24 The Year of the Agent Reality Check: Replit and Autonomous Coding
35:09 Mock Data and Unit Test Cheats: Watch Out for These AI Coding Traps
#aiactually #enterpriseaiadoption #forwarddeployedengineers #palantirFDEmodel #AISpecialization #businessprocessautomation #ReplitAgent3 #AIScaffolding #EnterpriseIntegration #aiROI
