The first month solves architecture. The second month builds, migrates, QAs, and ships. Launching without the architecture work would be faster in the same way skipping the foundation makes a building faster.
What makes 60 days realistic for a site this size: AI does the content sort, humans make the calls. A traditional manual audit of 6,000+ pages takes a team of content strategists three to four weeks. AI compresses that to one week of automated classification plus a week of human review.
| Phase | Window | What it solves |
|---|---|---|
| Phase 1 — Architecture | Days 0–30 | Who you are, what stays, what goes, how it's structured |
| Phase 2 — Build & Launch | Days 30–60 | Designed, migrated, QA'd, live |
| Phase 3 — Optimization | Day 90+ | What the data says to do next |
The first month solves architecture. AI does the content sort. Humans make the calls.
Kickoff and provisioning. Nothing built yet; everything unblocked.
Every page on logan.edu — the 3,098 in the sitemap, the 6,000+ Google has indexed, and the 407 traffic-earning PDFs found in the audit — runs through an AI classification pipeline.
Output: a structured inventory Logan reviews on Day 14. No more guessing what to migrate. No more spreadsheets with 3,000 rows and no decisions attached.
This is the work that used to take agencies a month to do badly. We do it in a week and the humans on Logan's team decide what stays.
Logan's team walks through the AI inventory, makes the final calls, and locks the architecture.
Visual direction approved, no surprises waiting for launch.
The second month builds, migrates, QAs, and ships.
The site exists as a real, reviewable thing — not yet public.
Site goes live. Monitoring active.
Post-launch review and tier evaluation. The data tells us what to do next.
First substantive measurement of the rebuild's impact.