What buyers of AI products ask AI
These are the prompts we track for AI companies. Each one fans out into several searches behind the scenes, and every search is a chance to be one of the sources the answer is built from.
- best AI agent platform for customer support
- best AI app builder for non-technical founders
- best voice dictation tool for Mac
- AI tools for creating UGC video ads
- open source alternative to ChatGPT for internal docs
- which LLM API is cheapest for high volume classification
- best AI meeting notes tool that works with Zoom and Google Meet
- Cursor vs Windsurf vs Claude Code for a small team
Where AI engines look for AI products
Engines treat practitioner threads as the honest take on a tool. A comparison thread with a few detailed replies is often quoted ahead of the vendor's own site.
They give engines a clean category label and a one-line description per tool, which is exactly the shape a recommendation answer needs.
Query fan-out turns one prompt into several 'best X' searches. The pages ranking for those searches become the shortlist the model works from.
Stars, model cards, READMEs and Spaces are trusted technical signals. For developer tools and open models they are frequently the cited source.
When a buyer asks which model or tool is best at a task, engines reach for anything that looks like a measured comparison, including independent evals and arena-style rankings.
Transcripts are indexed and summarised. A clear demo that names the tool and the use case can be pulled into Gemini and Google AI answers.
Funding news anchors the entity: who the company is, what it does, who backed it. It is rarely the recommendation source but it shapes the description.
The subreddits that matter
01How does ChatGPT decide which AI tools to recommend?
When someone asks ChatGPT, Perplexity or Gemini for the best AI tool for a job, the engine rarely answers from memory alone. It runs query fan-out: the one prompt becomes several searches, such as 'best AI dictation app 2026', 'Wispr Flow alternatives' and 'reddit voice to text Mac'. It retrieves pages from a search index (Bing for ChatGPT and Copilot, Google's own index for Gemini and AI Overviews), then cites the passages that answer most cleanly.
Two consequences follow. First, citation is passage-level: the engine lifts a paragraph or a list item, not your whole page, so the sentence that names your product and its use case has to stand on its own. Second, recommendations come from co-occurrence. If your tool is named alongside the category leaders in Reddit threads, directory categories and ranked lists, the model learns that it belongs in the set. If it only appears on your own site, it does not.
AI is also the category where recency matters most. Engines know the category moves fast, so they weight recent threads and recently updated lists. A list from last year that does not mention you is a liability; a list updated last month that does is worth more than its domain rating suggests.
02How should an AI company use Reddit without getting banned?Grey area
Reddit is the single most important channel for AI companies because AI buyers already live there, and because engines quote it. The play is a campaign of four posts, not one launch post. Each post has a different job: a news or launch post, a build story or technical teardown, a comparison or results post, and a question post that invites the community to argue about the category.
The launch post is built for speed. Reddit ranks new posts by early velocity, so the first hour decides the day. Emergent's Series C post on r/singularity is the example: it reached 8.9K views in 58 minutes and was the #15 post of the day on the subreddit. That does not happen by accident. The title led with the concrete news, the body answered the obvious questions before anyone asked them, and the team was in the comments from minute one.
Comments are where AI companies actually win Reddit. Most recommendation threads ('what are you using for X?') are answered by a handful of people. A founder or engineer who replies with a specific, disclosed, useful answer, including when a competitor is the better fit, builds the kind of thread that engines later quote. Comment-first means months of genuine replies before any account posts about its own product.
- Map subreddits by buyer, not by topic: who in r/LocalLLaMA would actually pay for this?
- Read each subreddit's self-promotion rules and the moderators' recent removals before posting.
- Lead technical subs with numbers, code or a reproducible demo. Lead news subs with the news.
- Answer every top-level comment in the first two hours. Velocity plus engagement is what sustains rank.
- Use the founder's or an engineer's own account, with disclosure in the post or flair.
03Which AI directories and 'best AI tools' lists actually matter?Grey area
AI tool directories are low glamour and high leverage. There's An AI For That, Futurepedia, Toolify, Product Hunt and category-specific lists give the engine a short, structured description of your product in the right category. That is the raw material of an answer like 'the best AI tools for UGC video are...'.
Listicles are the bigger lever. The play is to find every page that ranks for your 'best AI X' queries and that engines already cite, then earn a place on it: by pitching the author with a real differentiator, offering a demo account, or supplying a screenshot and a one-line verdict they can paste. Affogato AI's position at #4 in ChatGPT's top 10 AI tools for ads and UGC video is the outcome this work aims for.
Then publish your own. A 'best AI tools for X' page on your site that includes your product, with honest criteria and fair verdicts on competitors, is a legitimate grey-hat asset. Engines retrieve it for the same fan-out queries. It only works if it is genuinely useful: rank yourself where you belong, and say who should pick someone else.
04Do GitHub stars and Hugging Face pages affect AI citations?
For developer tools, models and infrastructure, yes. GitHub READMEs and Hugging Face model cards are crawled, ranked and trusted. When a buyer asks 'best open source model for code review' or 'self-hosted alternative to X', those pages are often the cited source, and stars, downloads and trending lists act as social proof the model can repeat.
Treat the README and model card as AEO pages. The first paragraph should say what the thing is, who it is for and how it compares, in plain words. Add a short benchmark table with the method stated. A Hugging Face Space or a Colab that lets people try it in one click earns links from Reddit and newsletters that a landing page never will.
Benchmarks are the AI category's link bait. A clearly documented eval, with the dataset, prompts and scoring published, gets cited by engines when buyers ask which tool is best at a task. Publishing an eval where you do not win every row is more credible, and more cited, than one where you do.
05What should an AI company's own site publish to get cited?
Your site's job is to be the cleanest source for facts about you. Engines check entity consistency: if your homepage says 'AI agent platform', your directory listing says 'chatbot builder' and your G2 page says 'customer service software', the model is less sure what you are and less likely to recommend you.
The pages that get cited are answer-shaped: a use-case page per buyer job ('AI voice dictation for doctors'), comparison and alternatives pages, a pricing page with real numbers, an integrations page, and a changelog that proves the product is alive. Each one opens with a two-sentence answer the engine can lift.
Willow's result, ChatGPT listing it first for 'best voice dictation tool', reflects this combination: a clear category claim, repeated consistently across the sources ChatGPT retrieves, with the product's own pages agreeing with everyone else.
- One category phrase, used identically on site, directories, social bios and press.
- Use-case pages that match the exact prompts buyers type.
- Alternatives and 'vs' pages that are fair enough to be quoted.
- Organization and SoftwareApplication schema, and an llms.txt that points to the canonical pages.
- Server-rendered HTML: several AI crawlers do not execute JavaScript.
06How do you turn a funding round or launch into lasting AI visibility?
A funding announcement is a one-day spike in attention and a permanent change to how engines describe you. The press release sets the entity description; the Reddit thread, the founder's LinkedIn post and the YouTube demo that go out the same day decide whether people discuss it.
The play is to stage it. Press under embargo, a Reddit post timed for the subreddit's active hours, a launch video with a modest paid boost so it clears the first-day threshold, founder posts on LinkedIn and X that link to the thread rather than the press release, then follow-up posts in the following weeks that answer the questions the launch raised. The Emergent post is one piece of that system, and the reason it worked is that the rest of the system was ready to catch the traffic.
Running AI visibility for ai companies?
Book 30 minutes with Prithvi. We run your buyers' prompts first, so the call starts with where you stand.
One story, four channels
How we run each channel for ai companies. Reddit leads, because it is where AI goes for recommendations.
RedditLeads
- Four-post campaigns per launch: news, build story, comparison, open question.
- Founder and engineer accounts, disclosed, with months of genuine comment history first.
- Answer 'what are you using for X' threads with specific, honest recommendations, including competitors where they fit.
- Post reproducible benchmarks and code in r/LocalLLaMA; never marketing copy.
- Revive old, still-ranking recommendation threads with a genuinely useful update when the product changes.
YouTube
- Short demos titled with the exact buyer prompt, e.g. 'best AI dictation app for Mac, tested'.
- Chapters and an accurate transcript so engines can lift a specific segment.
- A small paid boost on launch videos so they gather first-day views and comments.
- Sponsor or supply review units to creators who already review tools in your category.
- Founder posts that share build decisions and numbers, linking to the Reddit thread or demo.
- LinkedIn articles that restate your category claim and comparison, borrowing LinkedIn's domain authority.
- Employee posts at launch so the announcement reaches several networks in the same hour.
X (Twitter)
- Launch threads with a 30-second demo clip native to the platform.
- Reply to AI researchers and builders with data, not pitches.
- Build-in-public updates that become the changelog engines read for recency.
Link bait that works in this market
Assets built to be cited: by journalists, by other sites, and by the AI engines that read both.
Open benchmark or eval
A documented test of tools in your category, with prompts and scoring published. Engines cite it when buyers ask which tool is best at a task.
Self-published 'best AI tools for X' guideGrey area
A ranked list with honest criteria that includes your product. Retrieved for the same fan-out queries as third-party lists.
Prompt or template library
A free library tied to your use case. Earns links from newsletters and Reddit, and gives engines a page to cite for 'how do I' prompts.
Hugging Face Space or free mini-tool
A one-click way to try the core capability. Gets linked from threads and directories far more than a landing page.
Model and pricing trackerGrey area
A regularly updated page comparing prices or capabilities across vendors. Recency makes it a frequent citation.
White hat, grey hat, and the line
AI visibility rewards whoever shows up in the sources first. Some of the fastest moves sit in a grey zone. Here is exactly where we stand.
White hat
What we do every time
- AEO use-case, comparison and pricing pages with answer-first passages
- Directory and listicle placements earned by pitching real differentiators
- Open benchmarks with published methodology
- Genuine, disclosed Reddit participation by the team
- README, model card and docs written to be quoted
Slightly grey
What we do with care, in the open
- Your own 'best AI tools for X' list that includes you, with fair criteria
- Alternatives pages for every major competitor
- LinkedIn, Medium and GitHub posts that borrow their domain authority
- Seeding a recommendation question on Reddit that your team then answers with disclosure
- Paid boosts on launch videos and posts to clear the first-hour threshold
Never
The line we do not cross
- Undisclosed sockpuppet accounts or AI-generated fake users
- Bought upvotes, vote rings or engagement pods on Reddit
- Fake reviews on Product Hunt, G2 or directories
- Fabricated benchmark numbers or cherry-picked evals presented as complete
- Private blog networks or paid links on spam sites
Questions from ai companies
How long does it take for an AI tool to show up in ChatGPT recommendations?
Retrieval-based answers can change within weeks once your product is on the pages engines already cite. Changes to what a model knows without search take longer and depend on training cycles, which is why we work on the retrieved sources first.
Is Reddit or SEO more important for AI startups?
Both, because they feed each other. Reddit threads are quoted directly, and Google ranks Reddit highly, so a strong thread also wins classic search. SEO and AEO pages on your site supply the clean facts engines check against.
Do AI tool directories still matter?
Yes, as structured category signals. They rarely drive buyers on their own, but they give engines a consistent one-line description of your product in the right category.
Can we get listed in 'best AI tools' lists we do not control?
Usually. Most authors update their lists and want a real differentiator, a demo account and a clean screenshot. Pitch with that, not with a link exchange.
What results has Shown delivered for AI companies?
Willow is listed first by ChatGPT for 'best voice dictation tool', Affogato AI is #4 in ChatGPT's top 10 AI tools for ads and UGC video, and Emergent's Series C post on r/singularity reached 8.9K views in 58 minutes as the #15 post of the day.
Do you use fake accounts on Reddit?
No. We work through founder, employee and brand accounts with disclosure. Sockpuppets get caught, and a ban removes the very threads that engines would have cited.