Reference documentation for AI tools, workflows, and production systems.
19 entries
The exact workflow for researching, verifying, and optimizing Lab content using Claude — including screenshot evidence, factual consistency checks, and GEO optimization passes.
Priority scoring model, backlog framework, staleness detection, and the operational logic for deciding what to publish next on AI Execution Lab.
Copy-ready MDX templates for every content type on AI Execution Lab — execution logs, failure reports, lessons, playbooks, case studies, GEO experiments, and system docs.
Implementation-ready copy for asquaresolution.com, TrustSeal, ScamCheck, and AI Execution Lab cross-references. Homepage sections, footer microcopy, CTAs, and intro blocks.
How the four A Square Solutions properties connect operationally — entity architecture, GEO relationship mapping, cross-domain authority, and canonical structure.
Ready-to-paste JSON-LD structured data blocks for WordPress, TrustSeal, and ScamCheck — Organization schema with full sameAs ecosystem array, SoftwareApplication schema for products.
Final production audit for lab.asquaresolution.com — platform readiness, SEO status, GEO/AI-search readiness, and production risk checklist.
How to record, name, store, and publish execution media — screen recordings, walkthrough videos, architecture diagrams, and debug replays.
Complete guide for deploying AI Execution Lab to lab.asquaresolution.com — DNS configuration, Vercel setup, environment variables, SSL, and launch verification.
Complete content pipeline architecture for AI Execution Lab — workflow definitions for every content type, review checklists, publication QA, and weekly/monthly cadence.
Which WordPress posts on asquaresolution.com should link to which Lab content — by category, anchor text patterns, and priority tier.
How to activate Plausible, Google Analytics 4, and Vercel Analytics on the AI Execution Lab platform.
Patterns for using Claude Code to write, validate, and apply WordPress REST API operations safely in production. Dry-run architecture, pre-apply checks, and schema-safe content patching.
Step-by-step deployment process, rollback procedures, and environment management for the AI Execution Lab platform.
Complete reference for all frontmatter fields available across every content section. Required fields, optional fields, valid values, and examples.
Platform description, launch announcement copy, SEO meta summaries, and social positioning for the AI Execution Lab public launch.
Actionable pre-launch, launch, and post-launch checklist for the AI Execution Lab platform.
Weekly publishing workflow, failure-report process, execution log rhythm, and playbook publishing guide for ongoing platform operations.
Step-by-step guide to publishing content in every section of the AI Execution Lab. Covers failure reports, execution logs, labs, case studies, playbooks, docs, and systems.