§01.01
Your JS framework hides the page from AI parsers.
Most LLM crawlers don’t execute JavaScript the way Googlebot eventually does. Your hero copy, schema, and even the H1 can render perfectly in a browser, and look like an empty shell to GPTBot.
Service · Technical GEO & SEO
Technical GEO & SEO: make your site readable to crawlers and to AI.
Googlebot still matters. So does GPTBot, ClaudeBot, PerplexityBot, and the citation parsers downstream. We fix the crawl, render, and schema layer for both, and add the AI readability signals (llms.txt, structured citations, parser-friendly markup) most technical programs skip entirely.
One URL · four bots · two failuresDIAGNOSED
URL
/pricing
§01 · Crawl
200 OK
§02 · Render
JS-blocked
§03 · Parse
No schema
§04 · Surface
Not cited
Crawl OK ≠ CitedRender + Parse decide it
62%
of B2B SaaS sites we audit have JS-rendering issues
Last 30 audits
8/10
ship with at least one critical schema bug
First-pass crawls
0.41s
median LCP improvement, post-engagement
Field data
94%
of pages cited by AI also pass our render audit
Citation correlation
§00: The definitionWhat technical GEO
What technical GEO
actually is.
Technical GEO is the engineering layer of generative engine optimization: the crawl access, rendering, structured data, and content architecture that determine whether an AI engine can reach your pages, parse them correctly, and quote them accurately in an answer. It is distinct from technical SEO in one respect. Technical SEO asks whether a page can be indexed and ranked. Technical GEO asks whether a passage can be retrieved and cited.
Six components make up the scope. The order matters: each one is gated by the one above it, which is why teams that start with schema and skip crawl access see no movement.
01Crawl access
Whether GPTBot, PerplexityBot, ClaudeBot, Google-Extended and CCBot are allowed in robots.txt, and whether your server actually serves them rather than rate-limiting unfamiliar agents. This is the gate. Everything below it is irrelevant if a bot never arrives.
02Render parity
Whether the HTML a bot receives contains your content. Most AI crawlers execute little or no JavaScript, so a client-rendered page returns an empty shell. A page can rank in Google, because Googlebot renders JS, and be invisible to every other engine.
03Structured data
Schema that is semantically correct rather than merely valid. Entity consistency across Organization, Article, Author and Product, so an engine can resolve who published a claim and whether they are credible.
04Passage architecture
Whether any single block of your page answers a question completely without surrounding context. Retrieval happens at passage level, so a page that half-answers eight questions wins none of them.
05Citation hygiene
Canonical consistency, stable URLs, llms.txt, and clean sitemaps, so the thing an engine cites still resolves months later and attribution lands on you.
06Delivery
Core Web Vitals and time to first byte, measured on the crawl path rather than in a lab. Slow origins get sampled less by every crawler, which quietly caps how much of your site is ever seen.
For the implementation detail behind each of these, including code examples and bot-by-bot configuration, the technical GEO guide is the long-form version. The 12-item checklist is the ship order, and technical GEO vs technical SEO covers what carries over from an existing setup.
§01: Where technical SEO breaks nowThree new failure modes
Three new failure modes
that didn’t exist in 2022.
§01.02
Your schema is technically valid and semantically wrong.
Product schema on a comparison page. FAQ schema on a landing page with no FAQs. Article schema with no author entity. Validators pass; Google’s rich results don’t fire; AI parsers ignore the markup.
§01.03
Your site is crawled fine and never cited anyway.
Crawl budget is healthy, status codes are clean, sitemap submits, and you’re still missing from AI answers. The bottleneck isn’t crawl. It’s the citation-friendly markup AI looks for and you haven’t shipped.
§02: The technical stack we runSix layers,
Six layers,
audited and shipped.
Crawl
Crawl & index health
Crawl budget, status-code anomalies, redirect chains, soft-404s, robots.txt and meta-robots conflicts, sitemap hygiene, log-file analysis where the volume justifies it.
Render
JS rendering parity
Server-side render audit across the four bots that matter (Googlebot, GPTBot, ClaudeBot, PerplexityBot). Hydration timing, lazy-load conflicts, client-only critical content moved server-side.
Schema
Structured data, AI-aware
Organization, Product, Article, FAQ, Author, Breadcrumb. Entity consistency across pages. JSON-LD for AI parsers, microdata for rich results, OpenGraph for social.
AI
AI readability layer
llms.txt setup with section-level granularity, citation-friendly markup (clear quotes, bylines, dates), source-page format that LLMs prefer to lift from. The piece nobody else is shipping yet.
Perf
Core Web Vitals, on real devices
Field LCP/INP/CLS, render-blocking diagnostics, edge-cache and image-format improvements. Tied to revenue impact, not synthetic Lighthouse scores.
Arch
Information architecture
Internal link graph, topic clusters, orphan pages, faceted-nav explosions, canonical and hreflang sanity, multi-language and multi-region site structure.
§03: The bots that decide whether you’re citedFive crawlers,
Five crawlers,
five quirks.
None of them behave like Googlebot used to. We tune for all five, because the ones you ignore decide what AI cites.
01
GooglebotJS execution. Render queue. Long-standing playbook.
02
GPTBotOpenAI’s crawler. No JS. Aggressive markup parsing.
03
ClaudeBotAnthropic’s crawler. Respects robots. Markup-first.
04
PerplexityBotCitation parser. Reads structured quotes and bylines.
05
Google-ExtendedAI Overviews + Gemini training. Separate UA.
§04: Why the 2022 technical playbook leaksTechnical SEO was built for one bot.
Technical SEO was built for one bot.
Now there are five.
2022 technical SEO
Geology technical SEO + GEO
Goal
Crawled and indexed
Crawled, parsed, and cited
Render
Optional: Google handles it
Mandatory SSR for the AI bots that don’t
Schema
Validator-passing
AI-parser-friendly + entity-consistent
llms.txt
Doesn’t exist in the playbook
First-class deliverable
CWV
Lighthouse green
Field LCP, INP, CLS tied to revenue
Audit cadence
Annual
Quarterly with bot-traffic monitoring
§05: Common questionsWhat technical leads
What technical leads
actually ask.
What is technical GEO?
Technical GEO is the engineering layer of generative engine optimization: the crawl access, rendering, structured data, and content architecture that determine whether an AI engine can reach your pages, parse them correctly, and quote them accurately in an answer. It is distinct from technical SEO in one respect. Technical SEO asks whether a page can be indexed and ranked. Technical GEO asks whether a passage can be retrieved and cited.
What is included in technical GEO?
Six components: crawl access for AI bots, render parity so bots receive your content in HTML, semantically correct structured data, passage-level content architecture, citation hygiene through canonicals and stable URLs, and delivery performance on the crawl path. They are sequential. Schema work on a page that AI crawlers cannot reach or render returns nothing.
What are the main technical GEO factors?
The factors that change outcomes most are robots.txt access for GPTBot, PerplexityBot, ClaudeBot and Google-Extended; server-side rendering so bots that do not execute JavaScript still receive content; entity-consistent schema across Organization, Article and Author; self-contained passages that answer one question completely; and canonical stability so citations keep resolving. Core Web Vitals matter, but less than the first four.
How do you do technical GEO?
Start by confirming AI crawlers are allowed and actually served, then check what those crawlers receive by fetching your pages without JavaScript. Fix render gaps before touching schema. Then make structured data semantically correct rather than just valid, restructure key pages so individual passages answer questions standalone, and finally tighten canonicals, sitemaps and llms.txt. Measure by citation share in AI answers, not by rankings.
What are the basics of technical GEO?
The basics are crawl access and render parity. If AI bots are blocked in robots.txt, or your pages only assemble content client-side, nothing else you do will register. Most sites that appear invisible in AI answers fail on one of those two before any content or authority question arises.
How is technical GEO different from technical SEO?
Roughly 70 percent overlaps: crawlability, sitemaps, server-side rendering, page speed and canonical hygiene serve both. The difference is the target. Technical SEO optimises for a page being indexed and ranked; technical GEO optimises for a passage being retrieved and quoted. That shifts emphasis onto AI-specific crawl tokens, passage-level structure, and entity consistency, which traditional technical SEO treats as optional.
Our site is on Next.js / React / Vue. Are we already fine?
Maybe, depends on whether you’re actually rendering server-side and how. Next.js with SSG or SSR, configured properly, is usually safe. App Router with default RSC is solid for Googlebot and decent for GPTBot. SPA-style React with client-only data fetching is almost always a problem for the non-Google bots. We test it directly rather than guess.
Do we really need llms.txt?
It’s not yet a hard ranking factor and won’t be the difference on its own. But it’s a low-cost signal that meaningfully helps AI crawlers index the right sections of your site, and we’ve seen citation lift correlated with shipping it well. We treat it as cheap, low-risk, and on the standard stack.
Can you fix Core Web Vitals on a JS-heavy site?
Yes, and it’s usually less invasive than the dev team fears. Most of our CWV wins come from edge caching, image-format swaps, render-path cleanup, and decoupling above-the-fold critical content from the framework hydration cycle. Full SSR migrations are sometimes the right call but they’re the exception.
How does this overlap with the GEO Optimization service?
Technical SEO is the technical layer of GEO. If you’re engaging on GEO Optimization, the technical work is included. This page is for clients who want only the technical scope, typically because their content and off-site work is already in good hands and they want a focused engagement on the crawl/render/schema/AI-readability layer.
What does the deliverable look like?
Same format as our SEO Audit deliverable: a prioritized fix list by week, by owner, by expected impact. Pre-written tickets for your tracker. A 90-minute hand-off call. We stay on Slack for 30 days for blockers.
Will fixing technical SEO move pipeline on its own?
Sometimes. More often it removes a ceiling. Most sites we audit have content and brand that should be ranking and being cited far more than they are, and the technical layer is what’s holding it back. Fix the technical layer and the existing content compounds.
Get started
Crawl OK isn't cited.
Book a 30-minute technical review. We'll run your URLs through the four AI bots that matter, surface the render and schema gaps, and tell you what we'd ship in the first 30 days.