I built an AI agent that ran production technical SEO on an enterprise site.
Keystone didn’t make recommendations. It shipped real code, fixed broken link networks, deployed and validated schema, and caught regressions the client wasn’t even looking for — on a daily schedule, under a two-tier human-approval guardrail.
Enterprise sites rot in the details.
High authority. A deep content archive. Enterprise scale on WordPress VIP.
Dr. Berg Nutritionals is a large, high-authority health site — the kind of surface area where technical debt hides.
Keeping a site that size technically clean — broken links, redirect chains, schema, sitemaps, citations, crawl health — is relentless, repetitive, detail-heavy work. A human does it slowly and inconsistently.
I wanted to prove a properly designed AI agent could own that entire workload: run it daily, unattended, at a quality bar and pace no single human matches — while staying safe on a live production enterprise site.
A supervised operator, not an autopilot.
I designed Keystone as an OpenClaw agent on a Mac mini, wired into the site’s real toolchain and running on a daily cron.
Each technical-SEO workstream — audits, link fixes, schema, citations, internal linking, health monitoring — became a defined workflow with its own tracking sheet as the system of record. The agent worked, logged, verified, and reported. I supervised through an approval model rather than by doing the work myself.
The key design choice was guardrails, not just autonomy: safe fixes shipped on their own; anything ambiguous blocked until I approved it.
— Design principle · Tier 1 / Tier 2 modelKeystone topology.
Triggers fire the agent. The agent drives the toolchain against a live enterprise site. Safe work ships autonomously (Tier 1); ambiguous work escalates to a human-approval gate and loops back (Tier 2).
Two crons trigger the agent. Keystone drives the toolchain — WordPress VIP, Rank Math, GitHub, Ahrefs, Search Console, Cloudflare, and Sheets as the system of record — against the live production site. Safe fixes execute on the Tier 1 path automatically. Ambiguous work is logged with an assessment and routed to the Tier 2 human-approval gate, which loops the approval back to the agent every four hours. Every change is backed up, written, then verified.
Agent Runtime
Site & Platform
SEO Layer
CDN / Cache
Audit / Data
Ops
Six workstreams. One agent. Owned end to end.
Every workstream a human team would split up, Keystone ran as defined workflows — each with its own system of record, each verified against the live site.
Broken internal and external link networks found, repaired, and re-verified against the live site.
Backlog clearedThe blog archive’s references converted to academic citation format, post by post, unattended.
Standardized site-wideOrganization and FAQ markup deployed through the SEO layer and validated on the production site — near-total coverage across the archive.
Validated liveScattered topic anchors consolidated to canonical hubs over consecutive unattended days — the long, boring work agents are for.
Consolidated to hubsA platform sitemap bug chased below the CMS surface and root-caused to the exact non-firing WordPress hook.
Root-causedA CDN cache regression that had quietly persisted for weeks — surfaced because the agent was watching, not because anyone was looking.
Regression caughtDiscovery discipline over vanity counts: suspected “404s” were verified before touching them, bot-blocking false positives were correctly identified and left alone, and the standout catch — a hidden performance regression — was found by watching, not by being asked. The full audit backlog closed with zero production incidents.
What the agent did — and what it didn't.
Two separate ledgers. The left is this sprint’s work. The right is four years of engagement context, shown to frame the surface Keystone operated on — not attributable to this sprint.
A clean, closed audit backlog on a live enterprise site.
- Internal link network repaired — the full backlog, verified live.
- Citations standardized to academic format across the blog archive, on a daily cron.
- Schema deployed and validated live — organization profiles site-wide, FAQ coverage taken to near-total.
- Sitemap-cache bug root-caused to a non-firing WordPress hook.
- Hidden CDN performance regression surfaced after weeks unseen.
- Executed autonomously on a daily schedule, full backups, write-then-verify — zero production incidents.
The broader Dr. Berg engagement (May 2022 – Apr 2026).
- Organic traffic roughly tripled over the engagement (Ahrefs, full period).
- Multi-million-dollar organic revenue attributed in GA4 across the engagement.
- A full content library published through a separate AI content system.
- Domain Rating climbed steadily over the engagement.
- Clean record: zero Google penalties, zero manual actions, zero FDA/FTC incidents.
These are engagement-wide outcomes shown as context — not results of the March sprint. They are not attributable to the Keystone agent.
Three fixes, at a glance.
How one run unfolds.
Keystone wakes, reads its memory files, and pulls the current audit state from Ahrefs and the tracking sheets.
Broken links repaired, citations reformatted, sitemaps and schema checked. Every change is backed up, then written, then verified against the live site.
Anything not clearly safe is logged with an assessment and blocked — routed to the human-approval gate rather than guessed at.
A run report lands in Slack: what shipped, what's pending, what needs a decision.
An approval cron checks for my sign-off. Once I mark an item "Approved," the agent unblocks and executes on the next pass.
I built the machine and ran it.
I designed the agent and every workflow, defined the Tier 1 / Tier 2 guardrail model, and wired it into the site’s toolchain.
I set the safety rules — backups-before-edits, write-then-verify, dev-before-prod, repo-as-read-only routed through the client’s developer — and supervised through approvals. I was the operator and architect; the agent was the execution layer I built and ran.