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AI Prompts, Reviewed

The AI ranked him 23rd of 23. He runs 6 office buildings.

We tested a How I AI networking prep workflow on a made-up cleaning company. It ranked a 6-building facilities director 23rd of 23. Here's the fix.

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AI Prompts, Reviewed · Brokers & Harassment

"Tobiah Wrenfield: seed-stage investor. Low fit. Skip if short on time."

That was row 23 of 23 in an AI networking brief for Quillfeather Commercial Cleaning (a made-up cleaning company). The real Tobiah (made up, like everyone in this test) runs facilities for 6 office buildings. At Quillfeather's $1,450 per building per month, that account is $8,700 a month, or $104,400 a year.

Same name is not the same person.

AI Prompts, Reviewed takes one prompt or workflow from How I AI, Claire Vo's show where guests share their screens and walk through how they really use AI. We run it on a small-business job, score it, and tell you what we'd change.

Credit: Based on "How to Use AI for On-Demand Networking Event Preparation," a workflow from How I AI (hosted by Claire Vo, written up by the ChatPRD team), shown by Rachel Wolan, Webflow CPO, in the episode "How I AI: Webflow CPO Rachel Wolan's AI Chief of Staff & Org Adoption Playbook." Original workflow: https://www.chatprd.ai/how-i-ai/workflows/how-to-use-ai-for-on-demand-networking-event-preparation. Full episode: https://www.chatprd.ai/how-i-ai/webflow-cpo-ai-chief-of-staff-adoption-playbook. Guest site: none listed on the How I AI workflow page.

What the original does

Rachel drops a screenshot of a dinner guest list into her own AI chief-of-staff app. Vision pulls out the names. A research agent runs a web search, a LinkedIn search, and a deeper search on each person. Markdown files about her and her company add context. Out comes a prep doc: priority connections, conversation starters, hot topics, venue details, and sources.

The test

All people and companies here are made up. Quillfeather is in Plano: owner Rosa, 9 cleaners. Event: a chamber mixer, Tuesday, Oct 20, 2026, 5:30 p.m. Goal: 2 new office accounts. The guest list shows 24 names.

Naive run (screenshot plus "research everyone and tell me who to talk to," no context file, no evidence rule):

  1. Same-name merge. Tobiah matched an investor with his name in another state. Cost of skipping him: 6 x $1,450 = $8,700 a month.
  2. Silent OCR. 24 names in, 23 rows out. Nobody counted. "Hollis Fenwright" became "Hollis Fenwick," and the brief profiled a retired dentist.
  3. Old title. Corinne Ashvale is listed as office manager at Brindlecote Dental (made up). She left in March. She now runs a 3-building warehouse.
  4. Wrong top pick. Priority #1 was another cleaning company owner. A competitor, not a buyer.
  5. Creepy starter. "Congrats on selling your house!" Pulled from a public listing.

The page's own runbook already names the fix: "Require role, company, location, and profile evidence; mark the record ambiguous when those signals conflict."

The rerun

Same screenshot, plus a context file: goal (accounts of 3+ buildings), buyers (facilities and operations managers), topics to avoid (pricing, competitors, anything personal). Rules: count names in and rows out, flag unclear spelling, match on role + company + city, date every source.

Result: 24 rows. 20 verified, 3 marked ambiguous, 1 flagged for spelling. That is 20 + 3 + 1 = 24. Top 3: Tobiah (6 buildings), Corinne (3), and a coworking manager. Rosa checks the 4 flagged rows herself.

Verdict: 8/10

Strengths: fits any event with a guest list. The runbook already names misread names, same-name merges, stale titles, and personal details. A ranked list with "why this person" is what a busy owner needs.

Weakness: Rachel built a custom app. Most owners have a chat window. Without your goals, the AI ranks by who sounds interesting, not who buys. No follow-up step.

Founder tweak: tell the AI who signs your contracts, make it count names in and rows out, and never trust a match that shows only a name.

Copy the MCAFax version

This is our own rewrite, not the original prompt. Copy the original from Rachel Wolan on How I AI: https://www.chatprd.ai/how-i-ai/workflows/how-to-use-ai-for-on-demand-networking-event-preparation

You are my event prep researcher for [business name], a local business.
You research and rank. You never contact anyone.
Inputs I will paste:
(A) guest list screenshot or file
(B) event name, date, venue, purpose
(C) what I sell, in 3 lines
(D) who buys from me (job titles, company size, area)
(E) my goal for this event in one line
(F) topics to avoid
Step 1. Extract every name into a table in original order.
 Report: names in image = X, rows in table = Y. If X != Y, stop and tell me.
 Mark any unclear spelling UNSURE. Do not fix it yourself.
Step 2. For each name, find current role, company, city.
 Match only if role + company + city line up with the event.
 If they conflict, label AMBIGUOUS and show both candidates.
 Give a link and a date for every fact. Undated = UNCONFIRMED.
Step 3. Rank the top 5 against (D) and (E). One line on why.
 Competitors go in a separate list, not the top 5.
Step 4. For each top 5: two work-related openers, one question.
 Public professional work only. No family, homes, health, politics.
End with: rows to check by hand (UNSURE, AMBIGUOUS, UNCONFIRMED).

Paste into Claude, ChatGPT, or Gemini with web search on. Attach the screenshot.

Before you walk in

  1. Write down who signs your contracts. Paste that in as (D).
  2. Count the guest list yourself. It should match the table.
  3. Check every AMBIGUOUS row against the company's own site.
  4. Cut any opener you would not say out loud to a stranger.
  5. Follow up within 2 days of the event: https://mcafax.com/notebook/prompts/lead-follow-up-automation

More owner prompts: https://mcafax.com/notebook/prompts

Questions readers actually ask

What do I need for the original workflow?

A guest-list screenshot, event details, Markdown files about you and your company, and authorized web and profile search.

Do I need a custom app like Rachel's?

No. Any AI assistant with image upload and web search can run the MCAFax version.

Why did the AI rank my best prospect last?

It matched a different person with the same name. Require role, company, and city to agree.

How do I catch name-reading mistakes?

Make the AI report names in versus rows out, and mark unclear spellings instead of guessing.

Is it OK to research people before a mixer?

Stick to public professional work. The workflow page says to leave out sensitive personal details.

What should I do after the event?

Send each person you met a short follow-up within 2 days.

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