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Research · preprint · 0.3

Defining the Boundaries Before Bringing AI Capability into an Engineering Organization

A position paper based on the author's experience driving AI infrastructure and pilots in a real engineering organization: it proposes four kinds of boundaries—context, responsibility, authorization, and measurement—and offers a falsifiable pilot protocol plus a minimal harness as a demonstration of putting them into practice.

LiyukLiyukPublished August 14, 2026
  • #AI
  • #Software Engineering
  • #Agent Systems
  • #Developer Productivity
  • #Governance
  • #Technology
  1. 1The Five Lenses: Connection-Oriented Problem LocationDeep research · 19 min read
  2. 2Data Measurement as Organizational Protocol: Definitions, Measurement, Tiering, and RetrospectivesDeep research · 11 min read
  3. 3Developer Productivity Is Not a Tool Catalog, but a Feedback SystemDeep research · 9 min read
  4. 4Defining the Boundaries Before Bringing AI Capability into an Engineering OrganizationDeep research · 9 min readThis chapter
  5. 5When AI Lowers Workflow Barriers: How to Redivide Functional Lines and Business LinesDeep research · 14 min read
  6. 6Decompose First, Then Schedule: A Review of Multi-Model Task Decomposition, Capability Switching, and Subtask RoutingDeep research · 13 min read
  7. 7Making an Agent a Collaborable Object: State, Feedback, and Result ConfirmationDeep research · 13 min read
  8. 8Let the Agent Execute: Emotional Adaptation, Trust Calibration, and Human Relief from Execution PressureDeep research · 13 min read
  9. 9The Laws of Human Motivation: The Situational Motivation ModelDeep research · 29 min read
  10. 10AI Does Not Automatically Create Productivity: From Local Acceleration to System ValueShort · 5 min read

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← PreviousThe Laws of Human Motivation: The Situational Motivation Model
Next →Data Measurement as Organizational Protocol: Definitions, Measurement, Tiering, and Retrospectives
View the column “Engineering & AI Judgment”← Previous: Developer Productivity Is Not a Tool Catalog, but a Feedback SystemNext: When AI Lowers Workflow Barriers: How to Redivide Functional Lines and Business Lines →

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