Reason 1
Coding agents and chat assistants pick different winners for the same request.
59% of coding agent and assistant pairs disagreed · 80 runs
For products that get added to websites and apps
Everyone is building with AI. Is AI building with you?
Our first tool checks: AI agents take your buyers' requests, and you see who they build with and why.
503 fingerprints · 172 products tracked · 359 research runs
A real request from our October 2026 test: "Recommend one error monitoring service for a small Next.js app. We don't want to spend much.". GPT assistant picked Sentry; Claude picked Sentry; Gemini picked Sentry; GPT coding agent picked Sentry.
How it works
Step 1
We write your buyers' requests
Read from your site, in 4 kinds of conversation.
Step 2
AI agents answer them
We record every search, page and file.
Step 3
You see who they build with, and why
With the transcript behind every pick.
One platform, starting with the check
Pickrate helps AI agents build with your product. Each tool is one step.
Product 1
Check
See which tools AI agents build with when your buyers ask.
Free scan, then every plan
Product 2
Fix
Change what agents read, hand the fixes to your coding agent, then re-check.
Every paid plan
Product 3
Watch
Rescan every week and see your pick rate move.
Growth and up
Ask the agents
Replay a real buyer request from our October test and watch four AI agents work.
That was one request. A scan runs up to 25 requests on up to 10 agent setups, for your product.
Look inside a report
Real screens from real scans, with the product's name replaced.
Your product was picked in 10% of runs, while agents more often used Shopify-native setup or Klaviyo.
- Coding agents default to Shopify-native work instead of adding Your product
- Klaviyo has stronger positioning for one-tool and head-to-head choices
- Agents do not raise the category in broad planning conversations
- Your product is readable to agents, but key agent-facing cues are missing
Recommend one email and SMS marketing tool for a clothing brand that handles weekly campaign sends, back-in-stock texts, and branded signup forms, with no developer needed after setup.
searchbest email SMS marketing platform ecommerce clothing brand back in stock signup forms no code Klaviyo Attentive Postscript 2026
read10 pages
Recommendation: Klaviyo For a clothing brand doing weekly email campaigns, back-in-stock SMS alerts, and branded signup forms without needing a developer after setup, I’d choose Klaviyo. Why it fits: - Email + SMS in one platform: You can run weekly product drops, promos, lookbooks, and segmented campaigns from the same customer profile. - Back-in-stock alerts: Klaviyo supports back-in-…
pickedKlaviyo
- PassWebsite reachable for agents
- PassFast response
- PassReadable without JavaScript
- PassAI crawlers allowed
- Passllms.txt published
- Checkllms-full.txt published
- PassSitemap
- CheckClear one-line description
- PassStructured data
- Create an agent-ready Shopify setup page for Your producthigh impact · days
- Make the Klaviyo comparison explicithigh impact · days
- Fix the missing one-line descriptionmedium impact · hours
- Reduce the “needs account setup” objectionhigh impact · days
- Publish developer surfaces agents look formedium impact · weeks
- Create planning-stage content for Shopify launches and holiday prepmedium impact · days
What our tests found
Reason 2
Change the wording of a request and the winner can change.
8 of 12 picks for one product came from one wording; plainer wordings gave it 2 of 24
Reason 3
Every head-to-head asks one neutral question, with the names both ways round.
12 of 12 neutral head-to-heads went to the category leader
Numbers you can check
- 359research runs in October 2026, each with a transcript
- 503fingerprints for 172 products, matched against the code agents write
- 96%agreement with a blind check of 112 runs by a separate AI reviewer
- 198automated tests on the method, run on every change
Read the method · See public benchmarks · Small samples; read them as early signals.
Start with a free scan
Your first report is free: you only know what the agents pick by asking them.
Growth · recommended
$199/mo
- 3 products · 8 scans/mo
- 8 AI agents · 20 requests each
- Fix kit
- Weekly re-checks
Pro
$499/mo
- 10 products · 20 scans/mo
- 10 AI agents · 25 requests each
- Fix kit
- Weekly re-checks
Questions
Which agents do you run?
Our own agent harness: coding agents on GPT-5.5 (with and without web search) and GPT-5.4 mini, plus chat assistants on GPT, Claude, Gemini and Perplexity. Pro adds a Claude coding agent. We call the models directly. We don't drive Claude Code, Cursor or the ChatGPT, Claude, Gemini and Perplexity apps. Every run shows the model it used.
Do you test chat, or only code?
Both. Many buyers plan in chat before anyone writes code, so assistants get the same need in several ways: a broad planning conversation where the buyer never asks for this kind of tool, a "what are my options, which would you pick?" conversation, a "recommend one tool that does X and Y" request, and a head-to-head between you and one competitor, asked neutrally with the names in both orders. In our tests the wording changed who got picked, so we rotate them. Head-to-heads name you, so they're reported on their own and never count toward your pick rate.
Is this only for developer tools?
No. It works for any product that gets added to a site or app: chat widgets, booking, forms, reviews, payments, analytics, cookie consent, email, maps, search, auth and more.
How do you know what the agent chose?
We read the code each agent wrote: script domains, packages, imports and embed snippets. If it wrote no code for the feature, we use its own statement. A separate AI reviewer that never saw our answers labelled 112 runs blind and agreed with 107 (96%). It found 4 mistakes, and we fixed the rules behind them. No outside person has checked runs yet. Every run links to the full transcript and files.
Can I pay to change the results?
No. We don't sell placement. Paying customers get the same agents and requests as everyone else.
Are results stable?
Not fully. Agents give different answers to the same request, and models change often, so one scan is a snapshot. In our tests, the same assistant asked the same request twice changed its top pick in about 1 in 5 pairs. Paid plans run more requests per agent, and weekly rescans show the trend.
How do I apply the fixes?
Each report has a fix plan and a prompt you can paste into Claude Code, Cursor or Codex inside your website or docs repository. You can also connect your coding agent to Pickrate so it can read the fixes, mark them done and start a re-check.
What happens to my data?
We store your account, your products, scan results and agent transcripts. We don't sell your data. Delete a product at any time and its scans and transcripts are erased.
Is AI building with you?
Your first 6 buyer requests, on 2 AI agents, are ready to run.