Programmatic SEO is broken — December 2025's Helpful Content Update wiped 60–87% of traffic from thin programmatic sites. We build the version that survives: first-party data, human edit layer, real schema, real internal-link graph. 1,000 pages live in 90 days, then six months of monthly iteration to lift winners and rewrite losers.
Templated pages with thin variable substitution worked for a decade. They don't anymore. Google's December 2025 update specifically targeted the «doorway-shaped» pattern: a single template, swapped variables, no real data underneath, no editorial judgment on top. Sites lost 60–87% of organic traffic in a single weekend. The agencies that sold them are quietly rebranding.
What survived — and in some cases accelerated through the update — has three things in common: first-party data the page actually depends on, a human edit layer that sets the angle, headline, and conclusion, and real E-E-A-T signals (author, schema, source links, primary research). That's the build we ship.
JobCannon is our own B2C career-assessment platform — and the live proof of this exact playbook. Built on a real database of 2,500+ careers and 1,500+ skills, every page is anchored in first-party data: actual scoring models, real graph relationships, real user results.
Through the December 2025 Helpful Content Update we didn't lose traffic — we kept indexing. Pages keep moving from «submitted» to «indexed» weekly. Schema-engineered, AEO-optimized for ChatGPT/Claude/Perplexity citation. Locale infrastructure for 5 additional languages staged in code, ready to activate per client market.
Live GSC dashboard available on the intro call. We screen-share the real numbers — clicks, impressions, indexed-page count, ranking distribution — not a sanitized PDF.
The fastest way to understand programmatic SEO is to click into it. Every card below opens a real, ranking page generated from a database — not a marketing screenshot.
2,536 career pages. Each one generated from a database of skills, education paths, salary bands, and related careers. Same template, real data, distinct page per career.
View live page →1,533 skill pages. Each one connected to careers via a 64,000-edge skill→career graph. Pages depend on the graph data — pull the data, the page collapses. That's the survival rule.
View live page →50+ psychometric test pages. Each anchored in a real scoring model with FAQ, Speakable schema, and an internal-link cluster engineered for ChatGPT/Claude/Perplexity citation.
View live page →MIR · Agency itself runs on the same engine — we eat our own dog food. Service × industry × location matrix, 100+ pages live. Same template logic, different facets.
9 services × 9 verticals = ~80 pages. Each one tailored to the industry's specific GTM motion, regulatory context, and SERP patterns.
View live page →Same service template, different geo signals — local schema, currency, regulatory framing. London, Dubai, San Francisco, New York, Singapore, Berlin, Amsterdam, Tel Aviv.
View live page →Same playbook, different brand and vertical (custom engineering, not marketing). 175 pages live. Demonstrates engine portability across separate companies and ICPs.
View site →The engine separates content (database) from presentation (template) and copy (locale file). Adding a language is a locale file plus a hreflang map — not a re-architecture. Six locales are wired into the production codebase; English is currently shipped, the rest activate per client market.
Production locale. All 4,000+ JobCannon pages, both MIR sites. Tier-1 EN markets are 56% of JC's organic traffic — the highest-ROI starting point for most B2B builds.
Locale files staged in code, hreflang map ready. Typical client fits: fintech targeting UA/RU diaspora, real-estate platforms in Israel, e-comm with Russian-speaking audiences in Israel/Cyprus/UAE.
Spanish + Portuguese locale infrastructure staged. Largest under-served EN-shadow market for B2B SaaS — most agencies skip it, leaving a wide-open SERP for serious programmatic builds.
On the intro call: we screen-share the live JobCannon Google Search Console dashboard — clicks, impressions, indexed-page count by template, query distribution, ranking trajectory through the December 2025 Helpful Content Update. Real numbers, not a sanitized PDF.
Generated from your first-party data, structured around hub-and-spoke topical authority — not a flat keyword list. Each page passes a quality gate before it ships.
Rankings appear in 60–90 days. Then we rewrite the bottom 10%, double down on the top 10%, and use GSC behavior data to lift the middle. 6 months is the right window — 3 is too short to see results, 12 is too much for a first commitment.
JSON-LD on every page (Article, FAQ, BreadcrumbList, Speakable), explicit internal linking graph, robots/sitemap engineered for crawl efficiency, GPTBot/PerplexityBot/ClaudeBot allowed for AI-search citation.
We work with your existing database — products, locations, comparisons, profiles, reviews, calculations — and build pages that depend on that data. No data, no template. That's the survival rule.
Every page gets a real human-set headline, angle, and conclusion. AI does the long middle. The headline-and-frame is what Google's quality signals reward post-HCU — and what an LLM still can't do reliably alone.
You see the same dashboard we see — clicks, impressions, indexed pages, query distribution, page-level performance. No monthly «report» — a live URL.
Programmatic SEO only works when there's real first-party data underneath. If you have a database of products, locations, profiles, comparisons, or calculations, this is for you.
B2B SaaS with feature × use-case × integration matrix. Series A–C, $1M–$30M ARR.
See the playbook →Embedded finance, payments, wealth, comparison-shopping for financial products.
See the playbook →AI-native B2B: model comparison, prompt libraries, evaluation, applied-AI vertical SaaS.
See the playbook →Two-sided marketplaces with listings, locations, categories, and provider profiles.
See the playbook →Job boards, ATS platforms, talent marketplaces with role × location × industry inventory.
See the playbook →Comparison and directory businesses with product × feature × price × review graph.
See the playbook →Two differences. First, we run programmatic SEO on our own product (JobCannon) — our reference build is live, post-HCU, and we screen-share GSC on the intro call. Most agencies show pre-HCU case studies that aren't representative anymore. Second, we work directly with your first-party data, not just keyword lists — that's what survived the December 2025 update.
Pricing on request — depends on scope (1,000 pages is the baseline; larger taxonomies scale up), data complexity, and whether you need us to build the data layer or you already have it. Recurring monthly billing across 6 months. Book a 15-min call and we'll quote on the same call.
Then programmatic isn't the right play yet. We'll tell you on the call. Sometimes the right answer is 50 hand-written pages with topical authority, not 1,000 programmatic ones. We don't sell what doesn't fit.
First impressions in GSC: 30–60 days. First clicks: 60–90 days. Compounding curve: months 4–6. If you need traffic in 30 days, the answer is paid acquisition, not SEO — we'll say so.
The build is engineered around the survival rule (first-party data + human edit layer + real E-E-A-T). That's what passed the December 2025 update — and what every documented post-update analysis points to. No one can guarantee future updates, but we ship the version with the highest survival probability.
The engine supports 6 locales (EN, RU, UA, HE, ES, PT). EN is our largest production reference (JobCannon — 4,000+ pages) and where post-HCU upside is largest today. Other locales are wired into the architecture — locale files staged, hreflang map ready — and activate per client market. We'll tell you on the call whether your target market is EN-first or locale-led.
We screen-share the live JobCannon GSC dashboard, hear your data, and quote on the same call. No follow-up deck.
