Product systems / Field notes

Useful thinking before the roadmap hardens.

Original positions on difficult product choices: what to test, how product teams decide, where AI fits, and how systems earn trust.

Latest articles20 published

Product leadershipAugust 11, 2026

Product management is an operating system, not a backlog

A practical view of product management as the decision system connecting strategy, discovery, delivery, and learning.

AI discoverabilityAugust 7, 2026

How to structure product knowledge so AI systems can cite it

A practical architecture for creating attributable, crawlable product knowledge that people and AI-assisted search can understand.

AI discoverabilityJuly 31, 2026

AI citations begin with crawlable, attributable evidence

Why conventional search foundations still matter when teams want their expertise to appear in AI-assisted discovery.

Technical SEOJuly 24, 2026

Technical SEO for JavaScript product sites

A decision checklist for making JavaScript product sites fast, crawlable, canonical, and understandable.

Structured dataJuly 17, 2026

Structured data should describe visible truth

How to use Article, Breadcrumb, Organization, and Service markup without turning structured data into a parallel version of the site.

AI product systemsJuly 13, 2026

AI features are systems, not buttons

A practical way to frame AI product work before a compelling demo becomes a fragile production dependency.

Product strategyJuly 13, 2026

An MVP is a decision system

A point of view on defining MVP scope around learning, not around a compressed version of the final roadmap.

Content architectureJuly 10, 2026

Internal linking is product knowledge architecture

A framework for turning service pages, articles, resources, and definitions into a navigable body of product knowledge.

AI discoverabilityJuly 3, 2026

An llms.txt file is an index, not a ranking strategy

Where llms.txt and agent guidance help—and where teams should avoid treating optional files as a shortcut to AI visibility.

Content operationsJune 24, 2026

Content refreshes need new evidence, not new dates

A review system for updating evergreen content without manufacturing freshness.

SEO systemsJune 10, 2026

Programmatic SEO without scaled content abuse

A decision framework for building templated search pages with unique value, accountable data, and strict publishing thresholds.

Search measurementMay 27, 2026

What to measure when AI changes search discovery

A measurement model connecting search visibility, AI-assisted discovery, landing-page quality, and business outcomes.

AI agentsMay 13, 2026

An AI agent needs a permission model before a prompt

A practical approach to defining tools, data boundaries, approvals, and recovery before an agent enters a real workflow.

Workflow designApril 29, 2026

Human approval is a workflow state, not a disclaimer

How to design review, correction, escalation, expiry, and resumption into agentic workflows.

AI evaluationApril 15, 2026

Evaluate agent workflows before production

A practical evaluation plan for agent tasks, tools, policies, recovery, cost, latency, and human review.

AI systemsApril 1, 2026

RAG quality begins with content ownership

Why content owners, freshness rules, access boundaries, and retrieval evaluation belong in the architecture of a grounded AI system.

AI engineeringMarch 18, 2026

Structured outputs are contracts, not guarantees

How to use schemas as interface contracts while separately evaluating meaning, evidence, permissions, and consequences.

SEO & PPC automationMarch 4, 2026

PPC automation needs conversion truth

A decision framework for conversion definitions, values, attribution checks, guardrails, and review before scaling PPC automation.

SEO & PPC agentsFebruary 18, 2026

Search-term triage is a decision workflow

How to design SEO and PPC search-term triage with evidence, confidence, approvals, and reversible account changes.

Content systemsFebruary 4, 2026

Content briefs should preserve evidence, not just keywords

A people-first content brief for search and AI discovery that keeps sources, intent, internal expertise, and accountability intact.

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