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Kushagar Garg — AI Visibility Report

Kushagar Garg (dreamstick.dev) scores 28/100 for AI visibility — mentioned in 0 of 10 engine answers, site readiness 70/100, scanned Sep 5, 2026.

Kushagar Garg · dreamstick.devScanned Sep 5, 2026Track weekly →

AI Visibility Grade

D
28OF 100
AI visibility0
Site readiness70

When buyers ask AI the questions below, Kushagar Garg appears in 0 of 10 answers — and the site is missing 3 of the signals engines read.

Invisible on ChatGPTInvisible on Gemini

Where engine answers come from — the hosts AI cited

01github.com×7
02mongodb.com×5
03conductor-oss.github.io×1
04deepwiki.com×1
05docs.kernel.org×1
06docs.scipy.org×1

Engine coverage — free scan covers 2 of 6

The questions your buyers ask AI

How do I build a self-hosted multi-model agent conductor for local AI development?
What are the best practices for contributing to major open-source scientific Python and cloud infrastructure projects?
How can I implement RAG pipelines using MongoDB vectors and Voyage embeddings for grounded AI answers?
What is the current state of independent nonprofit AI labs and their role in open-source machine learning?
How do I debug and contribute patches to complex CLI tools and cloud infrastructure codebases?

Columns: ChatGPT · Gemini — ✓ you were mentioned

What ChatGPT told your buyer

Asked: “What is the current state of independent nonprofit AI labs and their role in open-source machine learning?

Independent nonprofit AI labs are facing significant challenges in the current landscape, particularly due to the rise of well-funded for-profit entities like OpenAI. These nonprofits historically focused on AI safety, alignment research, and open-access tools, relying on philanthropic funding and government grants. However, as for-profit companies attract…”
You’re not in this answer. Your competitors are.
Sources it trustedfailurefirst.org ×1huggingface.co ×1shuvo24news.com ×1stateofopensource.ai ×1

Site fixes — what your site is missingReadiness 70/100

llms.txtMissingTell AI crawlers what your site is — generate one in 30s
JSON-LD schemaPresentStructured data helps engines classify you
AI crawler accessAll allowedrobots.txt allows all 4 AI crawlers
Buyer-question content4 of 5 answeredYour homepage addresses 4 of the 5 buyer questions
Comparison contentNo “vs” pagesEngines cite competitors' comparisons — publish your own RankBull writes and publishes these — see plans
Sitemap.xmlMissingEngines discover pages through your sitemap
Meta & OG tagsPresentTitle, description and social cards look good
Crawlable HTMLOKContent renders server-side; engines can read it

Is this your site? See exactly what buyers hear — run your own free scan.

Buyers are asking. Engines are answering with your competitors. Track these questions weekly, fix the missing signals, and publish the answers that change it.Track this weekly — from $29/moScan your own site free →

About this report

This is a free AI-visibility scan of dreamstick.dev, run by RankBull. We ask ChatGPT and Gemini the questions a real buyer would ask before choosing a product like Kushagar Garg's, record the verbatim answers, and check whether the brand appears in them. Alongside that, a site audit reads the on-page signals AI engines rely on — llms.txt, JSON-LD schema, crawler access, sitemap and content coverage — and turns each gap into a concrete fix. The two dials combine into the letter grade above: visibility weighted 60%, readiness 40%.

This report is a snapshot — the answers were collected on Sep 5, 2026, and AI answers drift as models retrain and their sources change. The free scan covers two engines; paid tracking extends the same questions to Perplexity, Claude, Grok and Google AI Overviews, and re-asks them every week. Read how the checks work in the methodology or fix the basics yourself with the free tools.