Core framework for AI Execution Lab. Running Next.js 15 with the App Router, static site generation, and MDX content pipeline. The server/client module boundary and edge runtime behavior have produced documented failures. All content pages are statically generated at build time — no server-side rendering at runtime.
Operational records — 10 total
What it actually takes to operate a Next.js 15 App Router platform on Vercel in production: deployment configuration, monitoring, known failure modes, build performance, and the operational discipline that keeps it stable. From real operational experience on AI Execution Lab.
Testing whether structured semantic HTML (dl/dt/dd elements with explicit field labels) increases AI crawler fact extraction accuracy compared to prose failure descriptions. The QuickFix component was designed as an operational hypothesis — this lab documents the reasoning, the implementation, and the observable indicators.
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 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.
Production deployment of the Operational Intelligence Layer: failure-memory.ts, execution pathways, confidence scoring, /ops observability upgrade. 424 pages at build time.
lib/tracks.ts imported fs and path at the top level. track-roadmap.tsx (a 'use client' component) imported from lib/tracks.ts, pulling Node.js modules into the browser bundle. Build failed with Module not found: Can't resolve 'fs'.
Built Phase 4 Execution Tracks architecture, rebuilt the Claude Code Operator track with 8 modules, created the Failure Archive content section, and wrote 3 real failure reports.
export const runtime = 'edge' in app/opengraph-image.tsx blocked the entire Vercel deployment. Took 23 minutes to identify and revert.
NEXT_PUBLIC_GA_MEASUREMENT_ID was scoped to all Vercel environments (Production, Preview, Development). Every preview deployment URL accessed during development fired GA4 events to the production analytics property. Production session counts, traffic sources, and pageview totals were inflated by developer and build-verification activity until the variable was rescoped to Production only.