SEO/GEO Training Manual

What You're Walking Into

Kaizen has built — over the last 60 days — a complete SEO/GEO/AEO operating system. The pieces:

• SAGEO Template v1.1 — our productized client deliverable framework (the what we ship)
• Dr. Strange's 4 skills — seo-audit, geo-analysis, seo-content-writer, schema-markup (the how we execute)
• GEO Score — proprietary 0-100 measurement system that tracks AI citation rates (the proof to clients)
• 900+ SME library files — pre-built industry knowledge that seeds Citation Magnet content (the competitive moat)
• ahrefs-intel skill — colony-shared Ahrefs data layer (full keyword, backlink, traffic, SERP, and broken-link intel via API). You never have to open ahrefs.com to do your job. Dr. Strange calls this skill for SEO work; Black Widow and Jarvis use it too. The measurement layer is autonomous.
• Discord-based workflow — every Dr. Strange job posts to #seo-geo for Don's review (the quality gate)

Why GEO Matters Right Now

The market has fundamentally shifted. From a16z's 2025 analysis:

• ChatGPT queries are 23 words on average vs. Google's 4-word average
• Session length in AI search: ~6 minutes vs. Google's 60-90 seconds
• ChatGPT is already driving referral traffic to tens of thousands of distinct domains
• Apple is building Perplexity/Claude into Safari — Google's distribution chokehold is cracking

From Andrew Warner's interview with Zapier (March 2026):

• Zapier is mentioned millions of times per month by LLMs in product recommendations
• The play is no longer "rank on Google" — it's "be the brand the model recommends"

From @denohawari (March 2026):

• His team has driven $30.52M in client revenue using LLM SEO over the past year
• A B2B SaaS scaled from $20k to $100k MRR in 4 months — 760%+ non-branded traffic growth
• Method: "decision pages" — [competitor] vs [your brand], alternatives to [X], best [tool] for [specific use case]

Translation: Traditional SEO still drives ~60% of website discovery, but it's the floor, not the ceiling. The growth vector is GEO/AEO — being cited when someone asks ChatGPT, Perplexity, Claude, or Google AI Overviews for a recommendation in your client's industry.

The ⅓ / ⅔ Heuristic (Calibratable, Not Fixed)

Our current allocation for client work: ⅓ of effort on SEO foundation, ⅔ on GEO/AEO optimization.

This is a starting baseline, not a law. After 3-5 client builds produce real data, we calibrate. Some clients (local service businesses with strong existing SEO) may need 20/80. Brand-new businesses with no web presence may need 50/50 until their SEO floor exists.

The Three Disciplines Defined

His Four Skills

Dr. Strange — run seo-audit:
  client_name: "Rideout Law"
  target_url: "https://rideoutlawgroup.com"
  audit_scope: "full"
  keyword_targets:
    - "California foreclosure attorney"
    - "wrongful foreclosure lawyer"
    - "loan modification attorney California"
  competitor_urls:
    - "https://competitor1.com"
    - "https://competitor2.com"

Dr. Strange — run geo-analysis:
  client_name: "Rideout Law"
  client_url: "https://rideoutlawgroup.com"
  ai_models: ["openai", "grok"]
  test_queries:
    - "best foreclosure attorney in California"
    - "what should I do if I receive a notice of default in California"
    - "Rideout Law Group reviews"
    - "California foreclosure defense lawyer near me"
    - "can I sue my lender for wrongful foreclosure in California"
    - "Rideout Law vs [competitor]"
    - "I just got a foreclosure notice in Orange County, who do I call"
    - "best lawyer for loan modification in California"
    - "California homeowner facing foreclosure what are my options"
    - "specialized foreclosure attorneys Sacramento California"

Dr. Strange — run seo-content-writer:
  client_name: "Rideout Law"
  content_type: "practice_area"
  target_keywords: ["wrongful foreclosure", "foreclosure defense attorney California", "predatory lending lawsuit"]
  word_count_target: 1500
  client_voice: "Professional, authoritative, warm but not casual. Trust-building. Avoid legal jargon — clients are scared homeowners, not lawyers."
  sme_context:
    - "/data/workspace/sme-cowork-library/coworkhive-sme-library-900/foreclosure-defense-sme.md"
  geo_optimize: true

Dr. Strange — run schema-markup:
  action: "audit_existing"
  client_name: "Rideout Law"
  page_url: "https://rideoutlawgroup.com"

Dr. Strange — run schema-markup:
  action: "generate"
  schema_type: "LegalService"
  client_name: "Rideout Law"
  entity_data:
    name: "Rideout Law Group"
    description: "California foreclosure defense and wrongful foreclosure attorneys"
    url: "https://rideoutlawgroup.com"
    phone: "+19165550101"
    email: "info@rideoutlawgroup.com"
    address:
      street: "..."
      city: "Sacramento"
      state: "CA"
      zip: "95814"
    geo:
      lat: 38.5816
      lng: -121.4944
    services: ["Foreclosure Defense", "Loan Modification", "Wrongful Foreclosure Lawsuits"]
    area_served: ["California", "Sacramento County", "Los Angeles County", "Orange County"]

Phase 1: Discovery + Baseline (Day 1-3)

Goal: Establish where the client currently stands. Build the proof points you'll use to demonstrate ROI later.

Step 1: Load the client context (mandatory, do this BEFORE any audit)

Adapted from @bloggersarvesh's Claude Cowork system. Before you run any Dr. Strange skill, post this context block in #seo-geo:

CLIENT CONTEXT BLOCK — [Client Name]

BUSINESS BASICS:
- Business name:
- Primary URL:
- Address (if local business):
- Phone:
- GBP URL:
- Years in business:
- Team size:

SERVICES + MARKET:
- Primary service:
- Secondary services:
- Service areas:
- Target customer:
- Average customer value:

SEO GOALS:
- Top 5 keywords client wants to rank for:
- Keywords currently ranking for (if known):
- Keywords client should rank for but doesn't:

CURRENT STANDINGS:
- Reviews: [X total, X star rating, X/month]
- GBP monthly views (if known):
- Monthly website traffic (if known):
- Map pack status:
- Biggest SEO problem (one sentence):

COMPETITORS (minimum 3):
1. [name] — [URL] — [GBP if local] — why they're beating us
2. [name] — [URL] — [GBP if local] — why they're beating us
3. [name] — [URL] — [GBP if local] — why they're beating us

WHAT'S ALREADY BEEN TRIED:
- [list prior SEO work, agencies, tools, results]

This context gets referenced by Dr. Strange in every subsequent skill invocation. Do not skip this step. This is the #1 reason agencies produce generic-feeling work — they never load the business context before starting.

Step 2: Run seo-audit (full scope)

This gives you the technical + on-page + local picture.

Step 3: Run geo-analysis (10-20 queries)

This gives you the AI visibility baseline. Save the date — every monthly re-run compares against this.

Step 4: Run schema-markup action audit_existing

This shows you what structured data exists, what's broken, and what's missing.

Step 5: Run ahrefs-intel for the full Ahrefs baseline sweep

This is a shared colony skill — Dr. Strange calls it automatically as part of his SEO audit workflow, but you can also invoke it directly when you need ad-hoc intel.

A full new-client baseline sweep includes:

• domain_overview — DR, traffic, refdomains snapshot
• traffic_history — 6-month organic traffic + refdomains trendline
• top_pages — what's currently driving traffic (don't break these)
• keyword_universe — every keyword the client ranks for, with quick-wins (position 4-20, volume ≥ 50, KD ≤ 50) auto-flagged
• content_gap — keywords competitors rank for that the client doesn't, leverage-scored
• backlink_intel — referring domains, anchor distribution, recent backlinks
• broken_backlinks — broken inbound links with outreach priority — the highest-ROI recovery play
• anchor_intel — over-optimization warnings (>25% exact-match = risk)

You invoke it in #seo-geo:

Dr. Strange — run ahrefs-intel baseline:
  client_name: "Rideout Law"
  target: "rideoutlawgroup.com"
  competitors: ["comp1.com", "comp2.com", "comp3.com"]
  country: "us"
  date_from: "2025-11-17"
  date_to: "2026-05-17"

Unit cost: ~500-800 Ahrefs API units per full client baseline (we have 400K/month — capacity for ~500-800 new client baselines monthly, or ~2,500 active retainers).

What you get back:

• domain_overview.json + domain_overview-summary.md
• traffic_history.json + chart-ready time series
• top_pages.json ranked by traffic
• keyword_universe.json with quick-wins flagged in summary
• content_gap.json sorted by leverage score (run, don't walk, on these)
• backlink_intel.json with anchor distribution
• broken_backlinks.json with outreach priority per link
• anchor_intel.json with over-optimization warnings

Brand Radar (Ahrefs's 2026 AI-mention tracker) is not yet wired into ahrefs-intel v1.0 — its API endpoint availability still needs to be verified. For now, our internal geo-analysis skill is the source of truth for AI citation tracking. Brand Radar will be added in v1.1 if/when its API ships.

You should not need to open ahrefs.com to do your job. If you ever find yourself wanting to (an ad-hoc visualization, a feature we haven't wrapped, exploratory click-through), tell me — we'll either add it to ahrefs-intel or get you a seat.

Deliverable for Phase 1: A client-baseline-report.md posted in #seo-geo that summarizes:

• Overall SEO Score from seo-audit (0-100)
• Overall GEO Score from geo-analysis (0-100)
• Top 5 critical technical issues
• Top 5 keyword gaps
• Top 5 schema gaps
• Competitor position summary
• Recommended deployment model (see Part 4 below)

Phase 2: The Three Re-Architecture Pillars (Week 1-4)

Once you have the baseline, Don approves a deployment model and budget, and you start the actual work. Three pillars run in parallel:

Dr. Strange — run seo-content-writer:
  client_name: "Rideout Law"
  content_type: "service_page"
  target_keywords: ["foreclosure defense California", "stop foreclosure California"]
  word_count_target: 1500
  client_voice: "Professional, authoritative, warm. Trust-building tone for scared homeowners."
  sme_context:
    - "/data/workspace/sme-cowork-library/coworkhive-sme-library-900/foreclosure-defense-sme.md"
    - "/data/workspace/clients/rideout-law/discovery-notes.md"
  geo_optimize: true

Why It Matters

This is the productized offering that separates Kaizen from every other SEO agency. We have 900+ SME library files (industry knowledge bases at 13,000+ words each). No competitor has that raw material. The Citation Magnet is how we turn that moat into client value.

The 4-Part Architecture

1. Industry Knowledge Graph

• Top 50-100 questions in the client's industry
• Each entry: declarative 1-2 sentence answer + statistic + dated citation + primary source link
• Uses DefinedTerm + FAQPage + Speakable schema
• Auto-generatable from the SME library files

2. "AI Audit" Public Page

• Format: "Here's what AI currently says about [topic], and here's what the data actually shows"
• Positions the client as the authority correcting AI misinformation
• Generates backlinks from journalists + industry pros
• Highly citable (AI prefers correction content)

3. Structured Data Feed

• /llms.txt — plain-text overview of the site's authoritative topics
• /knowledge-base/index.json — structured JSON feed of all Q&A pairs
• XML sitemap with <lastmod> dates signaling freshness

4. Monthly "State of [Industry]" Report

• Auto-generated from SME library (human review only, not authoring)
• Published as webpage + downloadable PDF
• Recurring citation target (AI re-crawls fresh content frequently)
• Builds email list (gated PDF)
• Generates social shares + backlinks

Validation Gate (Important)

Before we sell Citation Magnet as a standard deliverable, we need ONE proof-of-concept build that generates a Citation Magnet page from an existing SME library file using Dr. Strange's automated pipeline. If this requires significant human authoring rather than automated generation with human review, we don't ship it as a productized offering yet.

Don will tell you which client gets the pilot. Don't promise Citation Magnet to a new client until pilot status is confirmed with Don.

Model A: Greenfield Build (Full SAGEO)

When: New business, no existing site, or existing site is beyond salvaging.

• Full Astro 6 hybrid architecture on Cloudflare Pages
• Complete dual-audience page design
• Citation Magnet architecture included
• 90-day launch sequence
• Price range: $8K–$15K + $1K–$2K/mo retainer

Model B: Migration (Existing → Astro)

When: Client has WordPress/Squarespace/Wix with valuable content but a platform that limits SAGEO.

• Phased content migration to Astro
• URL mapping + 301 redirect plan
• Preserve existing SEO equity during transition
• Citation Magnet added in Phase 2
• Price range: $5K–$12K + $1K–$2K/mo retainer

Model C: SAGEO Overlay (Keep Existing Platform)

When: Budget-conscious SMB. Most common entry point. Don's preferred starter.

• Add JSON-LD to existing pages (works on any platform)
• Publish /llms.txt and knowledge-base/index.json
• Build Citation Magnet pages as subdirectory/subdomain
• Add FAQ schema to existing service pages
• Implement Speakable markup
• Monthly GEO audits + optimization
• Price range: $2K–$5K + $500–$1K/mo retainer

The SAGEO Audit as Sales Tool

Standalone GEO Audit (geo-analysis run): $500–$1,000

• Show prospect their current AI visibility score (likely low)
• Show where competitors are being cited instead
• Propose Overlay or Build to close the gap

Cost to Kaizen per audit: ~$0.30 in API calls. High-margin, demo-ready, urgency-creating. This is your lead-gen weapon.

All pricing is currently placeholder. Validate ranges after 3 completed pilot builds. Adjust based on hours invested and client willingness to pay.

Tactic 1: Reddit (Highest ROI for GEO)

• LLMs heavily weight Reddit content because moderators vet answers over time
• Older posts are more valuable — LLMs trust them more
• Use a house account (Zapier uses zapier_dave)
• Answer questions that customers are likely to type into LLMs
• Ask questions that customers are likely to type into LLMs (then answer your own questions)
• Don't obsess over upvotes — Zapier found little correlation between vote counts and GEO utility
• It's a volume play — spread across hundreds of threads, not viral on one

Tactic 2: YouTube

• Gemini uses YouTube heavily; other LLMs are influenced by it indirectly
• Create your own videos, especially for B2B (less competition in B2B video)
• Work with both big creators (polished, high-reach) AND small creators (outsized LLM influence per view)
• Example from Warner's interview: a 835-view video earned 5.9% of the question citation share in its niche

Tactic 3: Correct Outdated Articles

• Older articles about the client continue to influence LLM responses long after they're outdated
• Message publishers with outdated info; ask for updates
• Publishers often comply because they want credible content
• Track which 3rd-party articles AI is citing → systematically refresh them

Tactic 4: Tools for Measuring LLM Citations

Beyond our internal geo-analysis:

• Profound — monitor prompts, track citation rates vs. competitors
• Petra Labs — similar to Profound, more customizable
• Amplitude — customer journey funnel analytics, citation changes over time
• Ahrefs Brand Radar (2026 feature) — built-in AI mention tracking

Success Metrics (90-day targets)

Monthly Report Template

MONTHLY SAGEO REPORT — [Client Name]
Month: [Month Year]

YOUR AI VISIBILITY SCORE: [X]/100 (↑/↓ from last month)

WHEN CUSTOMERS ASK AI ABOUT YOUR INDUSTRY:
- [X] of [Y] questions: AI recommends YOUR business ✅
- [X] of [Y] questions: AI mentions you but not first 🔶
- [X] of [Y] questions: AI doesn't mention you yet 🔴

TOP WINS THIS MONTH:
- "[Query]" — ChatGPT now cites [Client] (was absent last month)
- "[Query]" — moved from mention to direct recommendation

PRIORITY TARGETS NEXT MONTH:
- "[Query]" — competitor [X] is being cited; here's our plan to earn that spot

TRADITIONAL SEO:
- Google rankings: [X] keywords in top 10 (was Y last month)
- Website traffic: [X] visits (+Y% vs last month)
- Leads from website: [X] ([Y] mentioned finding you through AI)

THIS MONTH'S WORK:
- [List of pages updated, schemas added, content shipped]

NEXT MONTH'S PRIORITIES:
- [List of upcoming work, tied to specific GEO Score gaps]

The Revenue Attribution Reality Check

Honest caveat to know going in: the chain from "AI cited the client" → "customer walked in the door" is imperfect. Most AI-driven visits don't carry UTM parameters. Your three best proxies:

1. The "How did you find us?" intake form field (include "AI assistant: ChatGPT/Perplexity/Claude/etc.")
2. GEO Score trends (rising = more AI mentions = more downstream brand recall)
3. Anecdotal feedback ("a customer told me ChatGPT recommended you")

Don't oversell attribution precision to clients. The honest pitch: "AI is increasingly how your customers research. Our job is to make sure when they ask, you're the answer. Here's how we measure that."

Technical: The 2MB Rule (Charles Floate, March 2026)

• Googlebot fetches only the first 2MB of HTML. Everything after that = invisible to Google.
• Place these AS HIGH IN THE DOCUMENT AS POSSIBLE: <title>, <meta> tags, canonicals, all structured data (JSON-LD).
• External CSS/JS files get their own 2MB limit per file.
• PDFs get 64MB. Use PDFs for resource downloads that need to be indexed.
• WRS (Web Rendering Service) is stateless — it clears localStorage + session data between requests. If your content depends on session state to render, Google can't see it.

Technical: Shopify Quietly Blocks AI Crawlers

If a client is on Shopify, their robots.txt likely blocks GPTBot, ChatGPT-User, ClaudeBot, anthropic-ai, PerplexityBot, CCBot by default (Shopify update, early 2026). To fix:

1. Online Store → Themes → Edit code
2. Add robots.txt.liquid to templates folder
3. Remove the AI bot disallow blocks OR explicitly Allow: / for AI user agents
4. Keep /admin, /cart, /checkout, /account disallowed

Google's Own Guidance on AI Optimization (Source: Google Search Central, 2026)

What Google explicitly says NOT to do (debunking SEO myths):

• ❌ Don't create special "machine-readable files" or rewrite content specifically for AI systems
• ❌ Don't "chunk" content into tiny pieces for AI
• ❌ Don't try to manipulate AI algorithms
• ❌ Don't create excessive pages targeting specific AI keywords

What Google says TO do:

• ✅ Create unique content with a distinct perspective (first-hand reviews, expertise-driven)
• ✅ Non-commodity content > commodity content (avoid generic "7 Tips for X" pieces)
• ✅ People-first content that satisfies user needs
• ✅ Standard semantic HTML, proper JavaScript handling, indexable + crawlable
• ✅ Good UX across devices
• ✅ Merchant Center + Google Business Profiles for product + local data

The synthesis: GEO is not about anti-SEO tactics. It's about doing SEO better — with more uniqueness, more first-hand expertise, more declarative structure, more entity clarity. The same content that wins in AI search wins in Google search. There's no "AI-only" content track.

Voice: The Most Common Mistake

When writing client copy, the failure mode is writing in Don's voice or Sebastian's voice instead of the client's voice. Always pressure-test:

• Does this sound like the client? Or like a consultant?
• Is the formality calibrated? (Law firm ≠ SaaS startup ≠ medical practice ≠ tea shop)
• Are industry-specific terms used correctly?
• Would the client's existing site feel consistent with this?

If client_voice is vague when you brief Dr. Strange, stop and clarify with Don before generating. Generic voice is worse than no voice.

The Kalicube "First-Failing Gate" Rule (Jason Barnard, April 2026)

The AI engine pipeline has 10 gates between "discovered" and "won." Confidence passes multiplicatively — 90% at each of 10 gates = 35% at the end. A single weak gate destroys everything downstream.

The rule: Locate the earliest gate where confidence drops below threshold and fix THAT one first. Investing in citation quality when pages don't render properly = waste. Investing in third-party corroboration when entity isn't disambiguated = waste.

Common first-failing gates:

1. Rendering — pages don't load / JS fails / 2MB cutoff hits
2. Indexability — robots.txt or meta noindex blocks
3. Annotation — schema is missing or broken
4. Entity disambiguation — Google/LLMs can't tell which "Smith Law" we're talking about (fix with sameAs links to Wikipedia, Wikidata, LinkedIn, GBP)
5. Extraction — content is written discursively, not in Claim-Frame-Prove blocks
6. Citation — no statistics, no dated sources, no authoritative anchors

Always diagnose before you act. Your first GEO Analysis run tells you the symptom; your seo-audit + schema audit tells you which gate is failing.

The "Hidden Salesforce" Frame (For Client Conversations)

When selling GEO to skeptical clients, the most effective frame (per Kalicube):

"Seven AI platforms — Google, ChatGPT, Perplexity, Claude, Copilot, Siri, Alexa — are working 24/7 either for you or for your competitors. Untrained, they default to whichever competitor has the best-corroborated content. Trained, they become the most scalable sales channel a business has ever had. The question isn't whether AI is recommending businesses in your space. It's whose business it's recommending."

CEOs understand the salesforce argument in ~8 seconds. Use it.

Content Drift vs. Corroboration Decay (Governance)

Most agencies monitor content drift (your own content going stale). They miss corroboration decay — 3rd-party references that supported your credibility get rewritten, drop off, or get superseded by competitor-favorable articles. Your site hasn't changed; the evidence base under you has.

Add to monthly retainer scope:

• Track full brand footprint, not just owned site
• Refresh third-party content on a deliberate cadence (quarterly minimum)
• Set Google Alerts for client name + key terms; flag any new article that contradicts or supersedes our positioning
• Reach out to publishers proactively (correction requests, refresh offers)

Decision Pages > Top-of-Funnel Content

From @denohawari's $30M case study:

"Don't write 'what is HR software?' — that's broad keyword content where giants always win. Write '[competitor] vs [your brand]', 'alternatives to [competitor]', 'best [tool] for [specific use case]'. These pages directly match the questions buyers ask AI. AI rewards specificity, not authority age."

For every client, build at minimum:

• 1 [client] vs [top competitor] page
• 2-3 best [service] for [specific customer profile] pages
• 1 alternatives to [competitor] page (if the competitor is gettable)

The Karpathy "Untrained Salesforce" Insight (Operating Note)

Some of the most important content on a well-built website is rarely visited by humans, because it exists to teach the AI what the brand is. The seven AI platforms read that content to form their understanding of the client even when no human ever clicks the page.

Don't prune low-traffic pages purely on analytics. If the page exists to feed the entity understanding (about page, technical service definitions, methodology pages), it earns its place even with zero human visits. AI eats it.

Where to Post What

The Quality Gate (Non-Negotiable)

Every Dr. Strange output goes to #seo-geo for Don's review before client delivery. No exceptions.

This includes:

• Audit reports
• GEO Analysis reports
• Generated copy
• Generated schemas
• Proposed roadmaps

Why: this is how we catch voice misfires, factual errors, and over-promising before they hit the client. Dr. Strange is fast but not perfect. The review gate is what makes the system trustworthy.

Daily / Weekly / Monthly Rhythm

Daily:

• Check #seo-geo for any Dr. Strange runs awaiting your review
• Triage new client requests in #research-queue (if SEO-related)
• Track active client tasks in shared task queue

Weekly:

• Run Ahrefs Site Audit on each active retainer client (automated; just review issues)
• Review Rank Tracker movement
• Brief Dr. Strange on the next batch of pages/schemas/audits

Monthly:

• Re-run geo-analysis for every retainer client
• Generate monthly SAGEO report per client (template in Part 6)
• Update historical trend data
• Review 3rd-party corroboration decay (Google Alerts queue)