For AI agents: a documentation index is available at /llms.txt
Editorial standards
No AI slop
WorkPods holds every GEO, AXO (agent experience optimization) and technical SEO deliverable to one No AI slop standard. AI agents do only the repetitive checks and first drafts; operators check every source, rewrite in plain language for your buyers, and wait for your approval before anything ships.
In today's fast-moving landscape, AI is changing everything about how buyers search.
Google users clicked a result on 8% of visits with an AI summary, against 15% without (Pew Research Center, 2025).
Sourced, plain, and checked by an operator.
01
Keep unedited AI output off your website
Unedited AI output never reaches your site, because every page fix, comparison guide and technical file goes through an operator's edit first. In our view, generic AI copy costs a brand trust with executive readers and gives answer engines little worth citing.
Our AI agents do the mechanical work. They check how six AI engines answer your buyers' questions and scan your HTML for missing labels. Operators make every judgement call, find and check the sources, and write the prose.
02
Enforce five editorial rules on every deliverable
Five rules apply to every page draft, comparison table, JSON-LD patch and llms.txt file (a short file telling AI tools what your site covers), and to structured data (labels telling machines what a page is) and MCP tool descriptions too. If a draft breaks a rule, the operator rewrites it before your team sees it.
- Every fact has a source: we name the primary source in the sentence and never invent numbers, clients, results, quotes, dates, partners, certifications or features. When a sentence needs an unverified fact, we cut the claim and write a simpler sentence.
- An operator edits every draft: AI agents help with research checks and first drafts. A senior operator then edits every deliverable line by line before it enters your workspace.
- Plain words: we write in direct business language, explain technical terms the first time they appear, and cut hype words and empty adjectives.
- Written for your buyers: every section answers its buyer question in the first two sentences. The first sentence gives the answer, and the second gives the reason.
- Nothing ships without approval: your team approves every change before release, and each sign-off is recorded in our approval log under how WorkPods works.
03
Replace vague machine prose with sourced facts
An operator edit removes vague machine claims and puts dated, named sources in their place. A worked example shows what that looks like.
Consider a hypothetical draft sentence explaining why a B2B company needs GEO and SEO together. An unedited machine draft writes that AI search is transforming the digital landscape and brands must revolutionise their content strategy to win top placements. An operator deletes that sentence because it states no source, uses hype words and implies guaranteed placements. Instead, the operator cites Pew Research Center (22 Jul 2025): users clicked a result on 8% of visits with an AI summary versus 15% without. The operator pairs that with Ahrefs (2 Mar 2026) finding that 37.9% of URLs cited in AI Overviews rank in Google's top 10.
The same discipline applies when we measure results before and after each fix:
- Named means your brand appears in the AI answer, Cited means your page is a source, and Cited instead names the sources used instead.
- Each AXO check on our technical files and MCP tool annotations (such as readOnlyHint and destructiveHint) is scored Pass, Partial, Fail or Not applicable. A missing optional file like llms.txt is Not applicable, never a fail, and only a present, broken file gets Fail.
04
Inspect the source, reviewer and approval log
For any deliverable, you can ask us to show the primary source, the operator who edited it and its entry in the approval log. Each page on our own site names its author and reviewer, and clients can see the same detail for their work.
- The source for any factual claim: ask where any statistic or product statement came from, and we will point to the primary document.
- The operator sign-off: see which operator edited the page draft, JSON-LD patch, robots.txt policy or WebMCP markup (an emerging standard for browser-agent tools).
- The approval log record: inspect what was proposed, who approved it under role-based access, and what changed in the before-and-after retest.
To see these standards applied to your own domain, request a free GEO and AXO audit, delivered within 3 working days.
Questions
Questions buyers ask
Do you ever publish unedited AI-generated content on client websites?
No. WorkPods never publishes unedited AI drafts on your site or hands them over as finished work. Our AI agents run the repetitive research checks and put together first drafts. An operator then edits every sentence, checks every source and reviews every technical file before it reaches your approval queue.
What happens if a draft needs a statistic or fact that cannot be verified?
The operator deletes the claim and writes a simpler sentence. A fact needs a source, either your approved facts or a named study. We never invent numbers, client outcomes, timelines, partnerships or product features to make a page sound more persuasive.
How does your two-sentence structure help both CMOs and AI answer engines?
Putting the answer first and the reason second gives a busy executive the point straight away, and gives AI engines a clear passage to quote. We think clear opening answers improve a page's chances of being Cited in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews and AI Mode, though no one can guarantee it.
Do the five No AI slop rules apply to technical files like llms.txt and schema patches?
Yes. The same five rules cover every file we prepare, including llms.txt guides, robots.txt and Content-Signal rules, JSON-LD labels, WebMCP markup and MCP tool descriptions. Each AXO check is scored Pass, Partial, Fail or Not applicable, and an operator verifies every field before your team reviews it.
Who authors and reviews the work at WorkPods?
Pages on this site are written and reviewed by our founders and technical advisor: Himanshu Sirohi (Co-founder, Strategy), Naman Gupta (Co-founder, Operations), Prateek Tomar (Co-founder, Technology) and Shefali Munjal (Technical Advisor). Each page names its author and reviewer. Client work is edited by an operator, and you can ask which one.
How do we keep final editorial control over our brand voice?
Nothing goes live without your team's explicit approval. You review every edited page, comparison table and technical patch in your workspace and ask for any changes your brand or legal team wants. You then sign off in our role-based approval log before your web team ships the update.