The Great Transition

1 March 2026 · Original source →

The Great Transition

ONE SENTENCE SUMMARY

A comprehensive mental model of the great transition explains knowledge public, API-driven products, AI-driven enterprises, and ideal state management today.

MAIN POINTS

  1. Knowledge moves from private to public via AI, skills, and open-source diffusion.
  2. AI enables turning expert knowledge into shareable skills embedded in markdown files.
  3. China and open-source diffusion diffuse specialized knowledge into public pools.
  4. Products shift from standalone software to APIs and directory-discovered services.
  5. Interfaces decouple from software; AI agents consume APIs via directories and MCPs.
  6. Enterprises become graphs of operations; AI-driven SOPs replace rigid hierarchies.
  7. Automation moves from assisting labor to enabling companies to do all work themselves.
  8. The work marketplace emerges: people broadcast skills; AI matches work with demand.
  9. Ideal state management: define ideal state, map current state, continuously migrate toward it.
  10. The ultimate use: agentic platforms orchestrating the graph of algorithms powering organizations.

TAKEAWAYS

  1. Use the Great Transition model to interpret AI-driven changes, reducing anxiety.
  2. Shift to API-centric products enables scalable, directory-driven automation.
  3. Individuals can monetize skills through a broadcasted, AI-matched marketplace.
  4. Enterprises become graph-of-operations; SOPs become dynamic, AI-governed workflows.
  5. Ideal state management and verification enable scalable, auditable transformation.

Summary

Daniel Miessler outlines a unifying mental model—the Great Transition—that links AI-driven shifts into a single framework: knowledge goes public, products become APIs, enterprises become graphs, automation replaces labor, and ideal state management guides transformation.

Key Wisdom

  1. The Great Transition unifies multiple AI-driven shifts into one framework.
  2. Knowledge becoming public narrows the gap between private expertise and others.
  3. Products evolve into APIs; directories curate the best services.
  4. Interfaces separate from core functionality and are consumed by AI agents.
  5. Enterprises map all workflows as graphs; SOPs become AI-governed processes.

Actionable Advice

  1. Map your organization’s SOPs into a graph of operations for AI automation.
  2. Build API-first tooling and participate in service directories for easy integration.
  3. Invest in personal AI infrastructure; broadcast your skills and portfolio.
  4. Define an ideal state and use it as a verification criterion for changes.
  5. Design human-centered collaboration models that co-exist with automation.