Cheap Seats

A read-only copy of Cheap Seats measuring itself, updated hourly. Run your own.

Quick wins

The fix lists from the latest run of every prompt set, core sets first, then fastest expected ranking gain: prompts a fix could flip per working day, each weighted by what it has left to win (one minus its recommended rate over the last two weeks; named, for an info prompt). Mark a fix with the commit or pull request you submitted for it; open leaves out the ones you have. A later fix for the same page stays open, with what was tried before.

Statusall 8open 5accepted 3

Priorityall 5urgent 1high 1medium 2low 1

Siteall 5elsewhere 5

Gapall 5documentation 4third-party 1

Setall 28Finding out whether AI assistants recommend us 5Getting recommended instead of a competitor 7Choosing an AI visibility tool 7Cheap Seats head to heads 5Open-source and self-hosted AI visibility 4

Get Popcorn listed in Rankability's best AI search visibility tracking tools article urgent third-party effort S flips 5 Finding out whether AI assistants recommend us

Where: https://rankability.com/blog/best-ai-search-visibility-tracking-tools/
Must say: Ask the editor to add Popcorn as the open-source, self-hosted option. Supply a one-paragraph entry: MIT licensed, a single Docker container, asks Claude and OpenAI models on search and recall tracks, grades recommended/mentioned/absent with share of voice, and outputs a ranked fix list. Link github.com/metcalfc/popcorn.
Done when: The Rankability article lists Popcorn, and a re-run of prompt 5 or 8 cites the article with Popcorn in the answer.
Displaces: https://rankability.com/blog/best-ai-search-visibility-tracking-tools/
Why: Rankability shaped the search answers in P1, P2, P5, P8 (twice), P11 and P12. P8 top pick was Peec AI.

Prompt for Claude Code
# Get Popcorn listed in Rankability's best AI search visibility tracking tools article

When buyers ask an AI assistant the questions below, it doesn't recommend us, or recommends us for the wrong reasons. This is a third-party gap: the roundups and comparisons the model reads leave us out.

## The questions it affects
- Our organic traffic is down and I suspect ChatGPT and Google AI Overviews. How do I check whether AI search is what's taking it?
- What tools track how often AI assistants like ChatGPT, Claude, Perplexity and Gemini mention a brand?
- How do I monitor whether AI search engines cite our website?
- Which questions should we track to measure AI visibility, and how many prompts do we need before the numbers mean anything?
- How can I see which web pages AI assistants rely on when they answer questions in my category?

## What the assistant said
Rankability shaped the search answers in P1, P2, P5, P8 (twice), P11 and P12. P8 top pick was Peec AI.

## Who wins the question today
https://rankability.com/blog/best-ai-search-visibility-tracking-tools/. Read it and make sure our version answers everything it does, better.

## Your task
We need to be included on https://rankability.com/blog/best-ai-search-visibility-tracking-tools/. Read that page first, work out the right way in (editor contact, submission form, PR, comments), and draft exactly what to send: a short, factual pitch covering the points below, in the page's own format.

## What it must say
Ask the editor to add Popcorn as the open-source, self-hosted option. Supply a one-paragraph entry: MIT licensed, a single Docker container, asks Claude and OpenAI models on search and recall tracks, grades recommended/mentioned/absent with share of voice, and outputs a ranked fix list. Link github.com/metcalfc/popcorn.

## Done when
The Rankability article lists Popcorn, and a re-run of prompt 5 or 8 cites the article with Popcorn in the answer.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run

Publish popcorn.zone/docs/guides/prove-content-impact on daily runs and fix-to-prompt proof high documentation effort S flips 2 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/prove-content-impact
Must say: Explain how to re-check and report change. Set a daily run within a daily budget, watch the day-by-day share-of-voice rank and rates, and tie each shipped fix to the prompts it was meant to flip. Report those prompts before and after, with the stored answers and citations as proof. Include a sample leadership one-pager built from the fix list's 'prompts it should flip' field.
Done when: A re-run of prompt 14 or 15 cites this page.
Displaces: https://help.otterly.ai/monitoring-interval
Why: P14 claude search: top pick 'Otterly.AI'. Codex cited help.otterly.ai/monitoring-interval.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/prove-content-impact on daily runs and fix-to-prompt proof

When buyers ask an AI assistant the questions below, it explains the topic without naming us or citing our pages. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- How often should we re-check whether AI assistants recommend us, and how do we track changes over time?
- How do I prove to leadership whether our content work is changing what AI assistants recommend?

## What the assistant said
P14 claude search: top pick 'Otterly.AI'. Codex cited help.otterly.ai/monitoring-interval.

## Who wins the question today
https://help.otterly.ai/monitoring-interval. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/prove-content-impact so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Explain how to re-check and report change. Set a daily run within a daily budget, watch the day-by-day share-of-voice rank and rates, and tie each shipped fix to the prompts it was meant to flip. Report those prompts before and after, with the stored answers and citations as proof. Include a sample leadership one-pager built from the fix list's 'prompts it should flip' field.

## Done when
A re-run of prompt 14 or 15 cites this page.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run

Publish popcorn.zone/docs/guides/search-vs-recall explaining both tracks with an example medium documentation effort S flips 1 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/search-vs-recall
Must say: Explain that each question can be asked with web search forced on or with no tools at all. The two give different answers because one reflects current web pages and the other reflects training data. Show how Popcorn runs both tracks on every prompt and reports them side by side. Include a real anonymised example where the two tracks disagree; pick it from a Popcorn run first.
Done when: A re-run of prompt 13 cites this page in at least one search answer.
Displaces: https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool
Why: P13: every search answer was shaped by vendor API docs and generic tool lists. No source explained measuring both modes.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/search-vs-recall explaining both tracks with an example

When buyers ask an AI assistant the questions below, it explains the topic without naming us or citing our pages. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Do ChatGPT and Claude say different things about a product with web search on versus from training data alone, and how do I measure both?

## What the assistant said
P13: every search answer was shaped by vendor API docs and generic tool lists. No source explained measuring both modes.

## Who wins the question today
https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/search-vs-recall so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Explain that each question can be asked with web search forced on or with no tools at all. The two give different answers because one reflects current web pages and the other reflects training data. Show how Popcorn runs both tracks on every prompt and reports them side by side. Include a real anonymised example where the two tracks disagree; pick it from a Popcorn run first.

## Done when
A re-run of prompt 13 cites this page in at least one search answer.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run

Publish popcorn.zone/docs/guides/diagnose-ai-traffic-loss: GSC, Bing, GA4 then Popcorn medium documentation effort M flips 2 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/diagnose-ai-traffic-loss
Must say: Cover the free first-party checks: Search Console generative AI performance reports, Bing Webmaster Tools AI Performance, and GA4 referrals with utm_source=chatgpt.com. Then explain the gap those leave: they show clicks and impressions, not whether the assistant recommends you or a competitor. Close that gap by running the buyer questions on Popcorn's search track for AI Overviews-style answers and its recall track for model belief.
Done when: A re-run of prompt 1 or 7 cites this page in at least one search answer.
Displaces: https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports
Why: P7 codex search: top pick 'Ahrefs Brand Radar', shaped by support.google.com/webmasters/answer/16984139.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/diagnose-ai-traffic-loss: GSC, Bing, GA4 then Popcorn

When buyers ask an AI assistant the questions below, it doesn't recommend us, or recommends us for the wrong reasons. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Our organic traffic is down and I suspect ChatGPT and Google AI Overviews. How do I check whether AI search is what's taking it?
- How can I tell whether Google AI Overviews and AI Mode mention our brand for the topics we care about?

## What the assistant said
P7 codex search: top pick 'Ahrefs Brand Radar', shaped by support.google.com/webmasters/answer/16984139.

## Who wins the question today
https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/diagnose-ai-traffic-loss so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Cover the free first-party checks: Search Console generative AI performance reports, Bing Webmaster Tools AI Performance, and GA4 referrals with utm_source=chatgpt.com. Then explain the gap those leave: they show clicks and impressions, not whether the assistant recommends you or a competitor. Close that gap by running the buyer questions on Popcorn's search track for AI Overviews-style answers and its recall track for model belief.

## Done when
A re-run of prompt 1 or 7 cites this page in at least one search answer.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run

Publish popcorn.zone/docs/guides/choosing-prompts with measured prompt-count variance low documentation effort M flips 1 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/choosing-prompts
Must say: Give a method for picking buyer questions: split them into category, comparison, problem and info prompts, and store them as TOML files changed through pull requests. Give sample-size guidance only after measuring it: run one prompt set repeatedly in Popcorn and publish the observed run-to-run variance in the recommended rate. Do not cite a prompt count without that data.
Done when: A re-run of prompt 11 cites this page.
Displaces: https://cloro.dev/blog/ai-visibility-sample-size/
Why: P11 codex search: top pick 'Ahrefs Brand Radar', shaped by ahrefs.com/aeo/choose-prompts-to-track.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/choosing-prompts with measured prompt-count variance

When buyers ask an AI assistant the questions below, it explains the topic without naming us or citing our pages. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Which questions should we track to measure AI visibility, and how many prompts do we need before the numbers mean anything?

## What the assistant said
P11 codex search: top pick 'Ahrefs Brand Radar', shaped by ahrefs.com/aeo/choose-prompts-to-track.

## Who wins the question today
https://cloro.dev/blog/ai-visibility-sample-size/. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/choosing-prompts so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Give a method for picking buyer questions: split them into category, comparison, problem and info prompts, and store them as TOML files changed through pull requests. Give sample-size guidance only after measuring it: run one prompt set repeatedly in Popcorn and publish the observed run-to-run variance in the recommended rate. Do not cite a prompt count without that data.

## Done when
A re-run of prompt 11 cites this page.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run