6 items across 1 sections
How the AI Execution Lab publishing workflow operates — Claude Code as the primary authoring tool, parallel background agents for high-volume sessions, MDX components as a structured content language, and build-time verification as the quality gate. Publishing velocity, failure detection rates, and the evidence-first content standard.
End-to-end case study: launching lab.asquaresolution.com — a public AI engineering journal built on Next.js 15 App Router, MDX content pipeline, Vercel deployment, custom content sections, and an execution tracks system.
How asquaresolution.com (WordPress) was wired into a four-property ecosystem with AI Execution Lab, TrustSeal, and ScamCheck — covering navigation integration, cross-domain GA4, SEO cross-linking, and the measurable traffic effects of treating standalone apps as one brand.
How the AI Execution Lab Vercel deployment pipeline evolved from initial setup through two documented build failures to a stable production configuration — covering edge runtime failure, next-mdx-remote v6 blockJS, environment variable scoping, preview workflows, and current build performance.
Architecture and build record for TrustSeal (trustseal.asquaresolution.com) — an AI-powered website trust verifier and fact-checker. React/Vite/Firebase/Gemini/Razorpay on GitHub Pages.
Architecture and build record for ScamCheck (scamcheck.asquaresolution.com) — an AI-powered scam detection tool. React/Vite/Firebase/Gemini on GitHub Pages with plain CSS.