My Mind essays

A practical guide to separating public web access, AI product feeds, and in-channel checkout—then choosing what to allow, pilot, or block based on catalog quality, B2B pricing, terms, and order operations.

A practical guide to deciding whether ChatGPT and Google AI Mode ads deserve a small test, whether your website and measurement need work first, or whether the channel is not ready for you.

A practical guide to deciding what to do when employees are already using or building AI: inventory first, govern useful work, buy coverage when needed, and block what cannot be contained.

A practical guide to choosing a deterministic function, provider-hosted code execution, a managed sandbox, or a self-hosted runtime for a B2B AI workflow.

A practical guide to choosing provider-constrained JSON, typed tool calls, application validation, bounded repair, and human review for production B2B AI workflows.

A practical guide to choosing a managed frontier API, managed open-weight endpoint, or self-hosted inference path by measuring data boundaries, quality, utilization, and operations.

A practical guide to choosing native parsing, OCR and layout extraction, specialized Document AI, multimodal models, human review, or a hybrid pipeline for messy B2B documents.

A practical guide to choosing delegated user access, workload identity, or a separate agent and task principal for B2B AI workflows.

A practical guide to choosing deterministic checks, trace evaluation, LLM judges, human review, and production monitoring for a B2B AI product.

A practical guide to deciding whether a B2B software product should add an MCP server, keep its API, build an interactive surface, or postpone the work.

A practical guide to choosing a direct API, deterministic browser automation, computer-use agent, or manual workflow for real B2B work.

A practical guide to choosing synchronous responses, background jobs, provider background mode, batch processing, or durable workflows for B2B AI work.

A practical guide to choosing retrieval, fine-tuning, both, or neither by diagnosing the real failure in a B2B AI workflow.

A practical guide to choosing one model, explicit routing, or adaptive routing by measuring quality, cost, latency, reliability, and recovery in the real workload.

A practical guide to persistent AI-agent memory: when to use it, what to store, how to handle scope and staleness, and why memory must never become authorization.

A practical guide to people-first content, crawlability, canonical URLs, structured data, crawler controls, measurement, and what not to promise.

A practical guide to prompt injection, tool permissions, approvals, auditability, recovery, and safer AI automation pilots.

A plain-English guide to AI agents, workflows, tools, safety, and the product ideas worth testing before you build something expensive.