One
Reply broadly, contact narrowly. This is a working operator's routine for turning engagement on their own posts into candidates. The qualification rules are the operator's and survive intact — the change is in what is done for them and what is not.
SIMULATED Synthetic data. The shape of the week is the point.
| The step | What it becomes |
|---|---|
| Find the top posts, recent first then analytics | Unchanged, and it stays with the operator. The funnel below is built from a week they gathered. |
| Reply to every commenter who is not spam | 278 drafts, each grounded in the actual comment and the full post. Substantive, never filler. A person sends them. |
| Qualify by the DM criteria | 14 match — then checked against dated records, not headlines. One of the rules turns out to be two years stale. |
| Add to CRM, send the connection note | 10 notes ready, each character-counted before anyone sees it. A person clicks send. |
Calendar, mail, conference lists, and public company filings — things already on your machine or already public. A professional profile site is not consulted, and nothing is bought from a data broker, because a broker list is a claim you cannot show a source for. What replaces it is better: a calendar entry with two attendees is a dated fact you hold, and a company filing naming two officers is authoritative.
Two
The objective, as the operator wrote it: Assemble a balanced
product-engineering team with evidence-backed candidates and credible
introduction paths.
Senior product engineers, United States or remote,
verified technical depth. A relationship path is preferred, not required.
SIMULATED Twenty synthetic candidates. The decisions on them are the point.
FACT, from a dated sourceCLAIM that nobody has corroborated yetCONFLICT)Backend 4 · Frontend 5 · Full-stack 3 · Mobile 2 · Platform 2 · Quality 2 · Data 1 · Security 1
| Candidate | Seat | Fit | Evidence | Path via | Outcome |
|---|---|---|---|---|---|
| Nadia FloresStaff backend engineer · Seattle, Washington | Backend | 94 | FACT | Elena Park | Ready |
| Marcus WebbSenior frontend engineer · Austin, Texas | Frontend | 92 | FACT | Drew Collins | Ready |
| Isha RamanSenior full-stack engineer · New York, New York | Full-stack | 91 | FACT | Priya Shah | Ready |
| Owen BrooksStaff platform engineer · Denver, Colorado | Platform | 90 | FACT | Alex Morgan | Ready |
| Mei ChenSenior iOS engineer · San Francisco, California | Mobile | 89 | FACT | Taylor Reed | Ready |
| Andre SilvaSenior backend engineer · Boston, Massachusetts | Backend | 88 | FACT | Morgan Lee | Ready |
| Leila HaddadSenior Android engineer · Chicago, Illinois | Mobile | 87 | FACT | Sam Rivera | Ready |
| Caleb JohnsonSenior QA automation engineer · Atlanta, Georgia | Quality | 86 | FACT | Drew Collins | Ready |
| Sofia AlvarezSenior frontend engineer · Miami, Florida | Frontend | 85 | FACT | Elena Park | Ready |
| Ethan KimSenior full-stack engineer · Portland, Oregon | Full-stack | 84 | FACT | Alex Morgan | Ready |
| Amara OkoyeData engineer · Washington, DC | Data | 83 | FACT | Priya Shah | Ready |
| Jonah SteinApplication security engineer · Raleigh, North Carolina | Security | 82 | FACT | Morgan Lee | Ready |
| Fatima NoorBackend engineer · Remote, United States | Backend | 81 | FACT | Sam Rivera | Ready |
| Theo GrantFrontend engineer · Philadelphia, Pennsylvania | Frontend | 80 | FACT | Taylor Reed | Ready |
| Grace LiuFull-stack engineer · Los Angeles, California | Full-stack | 77 | CLAIM | Elena Park | Review |
| Malik TurnerBackend engineer · Detroit, Michigan | Backend | 76 | CLAIM | Drew Collins | Review |
| Anika PatelFrontend engineer · Remote, United States | Frontend | 74 | CLAIM | Alex Morgan | Review |
| Diego MoralesQA engineer · Phoenix, Arizona | Quality | 73 | CLAIM | Morgan Lee | Review |
| Rachel FordPlatform engineer · Dallas, Texas | Platform | 62 | CONFLICT | Taylor Reed | Blocked |
| Benjamin ChoFrontend engineer · San Diego, California | Frontend | 58 | CONFLICT | Sam Rivera | Blocked |
Each row names someone in the operator's network who might make the introduction, and each carries the same open question: does that person know the candidate well enough to introduce them? The software does not answer that. The operator does. OWNER_REQUIRED
Filling every seat would have meant putting forward two people whose current employer the sources disagree on. So the honest team is eighteen, not twenty, and it says so. Seniority gets the same treatment: ten of the twenty hold a senior or staff title, and the other ten are listed with the title they actually have, not promoted to fit the brief.
Three
Every path in the team above is a question. This is what answering one looks like: a single request, worked end to end. A warm introduction to the founder of a logistics company, needed by end of week.
relationship_path.insufficient_evidence
The company is identified beyond doubt and every hop carries a source. It still will not make this introduction, because the strongest tie in the chain is two people who once sat at the same table.
Four
Six posts, 341 commenters, one pass. Reply broadly, contact narrowly. The narrowing step is where the work is.
The numbers above are the same 341 rows below. Filter, then click anyone to see what was actually checked.
Paper copy: the filters and the per-person detail are on the live deck at groundtrace-pitch.pages.dev. The rows printed below are the first of 341.
Showing 341 of 341
✓ note ready ✕ refused ! blocked on identity * your criteria would have skipped them · replied, no note
Pick someone to see what was checked.
relationship_path.insufficient_evidence
identity.claim_unverified
evidence_assertion.sources_empty
A buyer, skipped by a rule that was right last year
Maren Halvorsen's headline reads "Founder & CEO." Your criteria disqualify founders, so the rule skips her. The rule was correct when it was written.
The company filing says she incorporated in 2023, resigned in August 2024, and is now a Director at exactly the kind of company you sell to. She is not a founder. She is a buyer, and the headline is two years stale.
A rule that reads a headline will skip her. A record with a date on it finds her. No login, no scrape, no guess — an authoritative record instead of a self-reported one.
LinkedIn rejects notes over 300 characters without warning. Every draft is counted in code, and the count travels with it.
Five
The obvious question, answered plainly rather than with a claim of "automated". The short version: everything except the fetching and the sending.
| Step | Who | Note |
|---|---|---|
| Gather the week from your posts | You | Unchanged. Nothing in this touches the network |
| Deduplicate across posts and weeks | Machine | Two suppressed |
| Filter non-substantive comments | Machine | 61 filtered, each one listed and reversible |
| Write a grounded reply draft | Machine | 278 written, none sent |
| Match your DM criteria on role | Machine, then a person | 14 matched; the stale headline was caught by a record, not the rule |
| Resolve identity across sources | Machine | One blocked: two candidates, no way to tell them apart |
| Count note length | Machine | Every draft, before it is offered — no silent rejections |
| Decide a person is worth contacting | You | Three refused rather than queued |
| Write to a CRM | You | Prepared only, with a receipt per approval |
| Send anything on the network | You | Every reply, note and request |
| Collecting the week | by hand, on your machine |
| Reading 278 comments, writing a reply to each | machine |
| Judging 14 candidates against your criteria | machine, then you |
| Deciding on 3 refusals and 1 blocked identity | you |
| Sending 10 connection notes | you |
The sending is the only small part of the week. Everything above it is where the hours were, and all of it is either done or reviewable.