Skip to main content
Back to Blog
Daily Field Note
AI-curated · auto-published from public sources

Three Sites Built 215,128 Fake 'Best Software' Pages — Perplexity Cited Them

|AlphaForge Editorial|5 min read
AI Search VisibilityGEOLocal MarketingContent StrategyPerplexity

Three sites, 215,128 pages, one goal: get cited by AI

As of September 2026, a report titled "Manufactured Sources Behind AI Recommendations" reached the front page of Hacker News with 72 points and 43 comments. The finding: three websites published a combined 215,128 "best [category] software" pages, and Perplexity was citing those pages when people asked it what to buy. The pages were not written for humans to read. They were written for language models to quote.

This is the part every local business owner needs to sit with. The people running those three sites understood something most Main Street operators still don't: when a customer asks ChatGPT, Claude, or Perplexity for the "best HVAC company in Orlando" or the "best family law firm near me," the model answers from a small set of sources it has decided to trust. Get into that set and you get named. Stay out of it and you are invisible, no matter how good your Google reviews are.

Why the page farm is a dead end anyway

Here is the second story from the same week. A developer shipped Weedout, a $1.99 Safari extension that hides every YouTube video labeled "Made with AI" from your feed, search, and recommendations. It hit 168 points and 73 comments on Hacker News in two days. It uses YouTube's own label rather than a detector, so it only catches what the platform already flagged, but the direction is clear: platforms are labeling machine-made content, and users are paying to filter it out.

Manufactured source farms live in the gap between "AI engines will cite anything structured" and "everyone starts penalizing content built at industrial scale." That gap is closing. Google has run manual actions against scaled content abuse since March 2024. Perplexity and the others will follow, because a recommendation engine that keeps citing 215,128 auto-generated pages loses users. If your AI visibility plan is to out-publish the spam farms, you are buying an asset with a shrinking shelf life.

What actually gets a real business cited

The page farms are gaming a real mechanism. You can use the same mechanism honestly, and it holds up:

  • Consistent business facts everywhere. Name, address, phone, hours, and service list identical across your site, Google Business Profile, Yelp, and the top three or four directories for your trade. Models cross-check. One conflicting phone number and you look less trustworthy than the farm.
  • Real reviews with dates and specifics. Twenty reviews from the last 90 days that name the service and the town beat 200 undated ones. Recency is a signal the models weight.
  • A handful of genuine third-party mentions. A local news writeup, a supplier's "where to buy" page, a chamber listing, a podcast appearance. Three real citations from sites a model already trusts outweigh a thousand pages you published about yourself.
  • Structured data and an agent-readable version of your site. Schema markup for your services, locations, and FAQs, plus a clean text version an agent can parse without fighting your JavaScript. We covered the mechanics of that in our piece on markdown feeds and your website's second audience.

Do this by Friday

Open ChatGPT and Perplexity. Ask each one the exact question your best customer would ask: "best [your category] in [your city]." Write down three things: whether you are named, which competitors are named, and which sources the answer cites. Then click into those sources. If they are directory pages, you need your listing fixed on those specific directories. If they are review aggregators, you have a review-volume problem. If they are manufactured "best of" pages, you now know your category is being gamed and you have a short window to plant real signals before the models tighten up.

That 30-minute check tells you more about your AI visibility than any vendor pitch. It also tells you whether this is a job you can run in-house with a checklist or one that needs someone watching the citation set every week.

What this means if you're weighing AI marketing or an agent build

The mechanism behind AI recommendations is real and gameable, which means honest, well-structured signals work, but the easy exploit is closing fast. The businesses that plant real citations now will hold the position when the spam gets cleared out. Whether you run that yourself or hire it out, start by finding out what the models say about you today.

Get a free AI Visibility Report and see exactly which sources ChatGPT, Claude, and Perplexity cite for your category, and where you stand in them.


Ready to deploy AI agents for your business?

Tell our AI architect what you need. Get a scoped plan in minutes, not weeks.

Talk to the Architect

More from the Blog

Market MovesAI Agents

Enterprises Will Spend $201.9B on AI Agents in 2026 — Here's What SMBs Should Steal From the Playbook

Gartner says enterprises will spend $201.9B on AI agents in 2026. Here's the 3-move playbook SMBs can steal — and deploy for $1,200, not $300K.

·4 min read
StrategyPricing

Stop Selling Automation — Sell Outcomes: The New AI Agency Playbook for 2026

Automation is commoditized. Every agency can spin up a chatbot. The agencies winning in 2026 charge for results — qualified leads, closed deals, measurable ROI. Here is the playbook.

·7 min read
MCPTechnical

MCP Hit 97 Million Downloads — Why This Protocol Is the USB-C of AI Agents

Anthropic's Model Context Protocol is now supported by ChatGPT, Gemini, Copilot, and 10,000+ public servers. One universal connector for AI agents. Here is what it means for your business.

·8 min read
Industry NewsStrategy

Mastercard Just Gave Every Small Business a Virtual CFO — What That Means for AI Agents

Mastercard launched Virtual C-Suite — AI agents acting as CFO, CMO, and COO for small businesses. The biggest companies in the world just validated exactly what we build. Here is why custom beats generic.

·8 min read
Voice AIROI

Voice AI Agents Are Killing the Missed Call — Here's the ROI Math

73% of legal leads go to voicemail. 40% of real estate leads come after hours. Voice AI agents report 3.7x ROI per dollar invested. Here is the math and what it means for your business.

·9 min read
ArchitectureMulti-Agent

Multi-Agent Teams: Why One Agent Is Never Enough

Single agents hit a ceiling fast. Specialized teams of 2-5 agents — each owning one job — outperform generalists by 3-5x on complex workflows. Here is how to architect agent teams that actually scale.

·8 min read
IntegrationMCP

MCP Explained: How Your Agents Connect to Everything

Model Context Protocol is doing for AI agents what USB-C did for devices. One standard protocol to connect any agent to any tool — CRMs, email, databases, APIs. Here is what it is and how we use it.

·7 min read
PricingROI

The Real Cost of AI Agents: What SMBs Actually Pay

AI agent pricing ranges from $0 to $50,000 per month depending on who you ask. Here is a transparent breakdown of what things actually cost — LLM APIs, infrastructure, build time, and ongoing management.

·9 min read
DeploymentInfrastructure

VPS vs. On-Prem: Where Should You Host Your AI Agents?

Your AI agents need a home. We break down the trade-offs between cloud VPS hosting and on-premises deployment — cost, security, latency, and control — so you can pick the right setup.

·6 min read
SecurityOpenClaw

How We Secured Our Agents After CVE-2026-25253

When a critical vulnerability hit the OpenClaw framework, we patched every client agent within 4 hours. Here is what happened, what we did, and the security kit we open-sourced.

·8 min read

Liked this post?

Get agent builder tips, new playbooks, and automation strategies once a month. No spam.