Part III — The Opportunities · Chapter 13
Deep Tech, Medtech, and Pharma: A Different Timeline
Where AIDE meets the physical world. Regulatory latency as competitive advantage.
Chapter video
Chapter 13· Video in production
Paul on Deep Tech, Medtech, and Pharma: A Different Timeline
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Key concepts
Each concept links to its entry in the full glossary.
Featured framework
All diagrams →Framework diagram
Regulatory Latency— signature framework
High-resolution PNG and SVG bundle ships with the chapter download.
Digital War Room
Immediate Actions
Chapter-specific action items from the Digital War Room block will appear here. Download the workbook to access all immediate actions for this chapter.
Discussion Questions
Discussion questions for team and board conversations will appear here. Download the discussion guide for the complete set.
Workbook
Step-by-step implementation.
The Deep Tech, Medtech, and Pharma: A Different Timelineworkbook walks your team through a structured implementation — assess, design, ship — built from the chapter’s frameworks. Free with email.
Download the Deep Tech, Medtech, and Pharma: A Different Timelineworkbook →The Unfair Advantage
Agent-grade tools for this chapter.
AI Tool
Prompt Pack
Production-grade prompts for the chapter's core workflows.
Available with chapter resources →AI Tool
Audit Tool
Self-serve assessment driven by the chapter's framework.
Available with chapter resources →AI Tool
Reference Stack
Vetted agent platforms and LLM tools used throughout the chapter.
Available with chapter resources →Masterclass
Go deeper with the Deep Tech, Medtech, and Pharma: A Different Timeline Masterclass.
A structured, video-led course built around the chapter’s frameworks. Coming with the launch wave.
Course thumbnail — coming soon
Case studies
How real teams applied this chapter.
Case Study 1· In production
Applying Regulatory Latency
An operator team applies the chapter’s framework end-to-end. Outcome metrics published with the case study.
Read the case study →Case Study 2· In production
Applying Regulatory Latency
An operator team applies the chapter’s framework end-to-end. Outcome metrics published with the case study.
Read the case study →One email. Everything.
Get all Deep Tech, Medtech, and Pharma: A Different Timeline resources.
Workbook, discussion guide, framework diagrams, and prompt templates — bundled and emailed.
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About Paul Cheek
Paul Cheek is a global expert on AI-driven enterprises and enterprise innovation. He is a Senior Lecturer at the MIT Sloan School of Management and Senior Advisor for Entrepreneurship & Artificial Intelligence at the Martin Trust Center for MIT Entrepreneurship. As founder of the AI-Driven Enterprise Institute and Entonomy, he develops data systems and software that power AI agent-run businesses. A Forbes 30 Under 30 honoree, bestselling author of Disciplined Entrepreneurship: Startup Tactics, and recipient of MIT’s Monosson Prize for impact on entrepreneurship education, Paul has advised and built ventures from seed to scale, with his work featured in The Wall Street Journal, Bloomberg, and Forbes.
Read Paul’s full bio →Work with Paul
AI strategy and AI-Driven Enterprise transformation advisory for C-Suite teams, boards, PE firms, and operating companies. Engagements range from board-level AI literacy workshops to multi-month or year-long AIDE transformation sprints.
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What Paul is seeing in AIDE strategy, board-level AI, and PE/VC moves. Short. Tactical.