Insights
Writing from Katie Kearns and Structured Ink about technical communication, documentation systems, and the human work behind sustainable delivery.
This is the permanent home for Structured Ink articles, field notes, and practical guidance. Search by question, browse by topic, or follow related reading from one Insight to the next.
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Documentation becomes business infrastructure when it reduces repeated work, preserves decisions and operational knowledge, and gives people a reliable way to understand and change complex systems.
Read the article →By Katie Kearns · August 31, 2026
Featured Insight
Enterprise AI needs two kinds of governance: a knowledge control plane that defines what the system may retrieve, trust, retain, and present, and an action control plane that defines what it may reach, change, initiate, or approve.
Read the article →By Katie Kearns · August 12, 2026
Structured Ink helps technical teams diagnose the workflows, sources, terminology, ownership, and publishing systems behind documentation problems, then build information people can trust and maintain.
Read the article →By Katie Kearns · August 3, 2026
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22 Insights
Structured Ink’s website became a working case study in editorial architecture: defined voices, explicit sources of truth, structured content, version control, quality gates, and human approval boundaries.
Read the article →By Katie Kearns · September 15, 2026
Meta's Project OT is a warning about making slow, difficult-to-reverse organizational changes before fast-moving technical capabilities and their control systems have proved they can carry the load.
Read the article →By Katie Kearns · September 15, 2026
Frontier AI safeguards can detect and contain misuse, but some outputs create knowledge or capability that cannot be recalled, patched, or meaningfully reversed.
Read the article →By Katie Kearns · September 14, 2026
Once AI systems ingest documents, those documents become part of the system's attack surface—and trusted instructions can become dangerous as their dependencies age.
Read the article →By Katie Kearns · September 14, 2026
Congress is already using AI across legislative and operational work. The useful question is whether consequential AI-assisted work has enough provenance, review, version history, and ownership to be trusted.
Read the article →By Katie Kearns · September 10, 2026
Anthropic's move to mark Claude-generated text is useful provenance infrastructure, but a watermark does not answer every question about authorship, originality, human review, or responsibility.
Read the article →By Katie Kearns · September 10, 2026
The New Orleans 911 AI story shows why system boundaries matter. A narrow duplicate-crash-call workflow is not the same thing as replacing human call-takers, and the difference is part of the safety architecture.
Read the article →By Katie Kearns · September 9, 2026
Reliable AI retrieval depends on documentation that identifies its subject, audience, version, authority, ownership, permissions, and lifecycle state.
Read the article →By Katie Kearns · September 4, 2026
GPT-6 Astra’s most consequential result may not be raw intelligence, but stronger agency paired with better scope adherence. The evidence reinforces why aligned models still need enforceable authorization architecture.
Read the article →By Katie Kearns · September 4, 2026
Automation savings are incomplete unless organizations count the supervision, verification, exception handling, incident response, remediation, and recovery work that automation creates elsewhere.
Read the article →By Katie Kearns · September 3, 2026
A company’s technical-writer hiring process reveals how well it understands documentation itself. Vague roles, keyword screening, generic writing tests, and unsupported writers are often symptoms of a larger documentation operating-model problem.
Read the article →By Katie Kearns · September 3, 2026
Trying to explain a workflow step by step exposes hidden requirements, inconsistent terminology, permission gaps, broken examples, and unresolved product decisions. Documentation can act as a practical pressure test for product quality.
Read the article →By Katie Kearns · September 2, 2026
Some AI scaling limits are not capacity bottlenecks at all. They are hard serial dependencies: critical-path work, real-world feedback, and minimum elapsed time that additional people or agents cannot parallelize away.
Read the article →By Katie Kearns · September 2, 2026
NVIDIA's NeMo Switchyard points toward a more useful enterprise AI question than which model is best: how should a system route different tasks across models while preserving quality, cost, latency, privacy, and accountability?
Read the article →By Katie Kearns · September 1, 2026
AI can dramatically increase the amount of work an organization generates while overwhelming its ability to review, integrate, govern, and safely operationalize that work.
Read the article →By Katie Kearns · August 31, 2026
Documentation becomes business infrastructure when it reduces repeated work, preserves decisions and operational knowledge, and gives people a reliable way to understand and change complex systems.
Read the article →By Katie Kearns · August 31, 2026
Meta's AI-native restructuring shows why employees are not just producers of output. They also provide coordination, review, institutional memory, constraint, and recovery capacity that functions as part of the organization's control system.
Read the article →By Katie Kearns · August 28, 2026
Multi-agent systems create a second security surface: the communication paths, shared state, delegated work, and persistent context that let agents coordinate. Those coordination mechanisms need explicit permissions, logging, attribution, monitoring, and kill controls.
Read the article →By Katie Kearns · August 19, 2026
Private companies entering offensive cyber operations face the same boundary problem penetration testers already know, but with harder attribution, third-party infrastructure, changing conditions, and the risk of retaliation. Scope, stop conditions, and evidence have to contain both the action and what comes back.
Read the article →By Katie Kearns · August 14, 2026
Enterprise AI needs two kinds of governance: a knowledge control plane that defines what the system may retrieve, trust, retain, and present, and an action control plane that defines what it may reach, change, initiate, or approve.
Read the article →By Katie Kearns · August 12, 2026
The UK AI Security Institute’s cyber evaluation revealed a gap between the boundaries described to AI agents and the controls the technical environment actually enforced. Organizations should constrain agents at least as carefully as they constrain human users.
Read the article →By Katie Kearns · August 5, 2026
Structured Ink helps technical teams diagnose the workflows, sources, terminology, ownership, and publishing systems behind documentation problems, then build information people can trust and maintain.
Read the article →By Katie Kearns · August 3, 2026
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