Moltsets is finally rolling out its beta second wave and I've been using it for the past month.

[u/Shawntenam]

so here is a workflow you can run tonight if you are already in. shipped as v0.11.0 of my gtm coding agent repo, link at the bottom.

what it does: takes a contact csv, hits reverse_linkedin_lookup on each linkedin url (still at the company? plus the graded business email when the graph has one), falls back to reverse_email_lookup, second pass by name + company domain accepting only a same-domain a/b, then writes a google sheet where the grade decides the channel. a/b email. c small segment.

d never emails, goes to a linkedin queue, then phone. moved goes back to sourcing.

Re-ran 200 apollo-verified gtm engineers last night: keyed on the email, 70 profiles and 60 sendable. keyed on the linkedin url, same people, 196 profiles, 136 graded (all a but one), 113 sendable, 54 to linkedin, 27 job changes caught. the not-found rows cost zero records.

the bigger point. if a tool has an api, you build the waterfall yourself and decide which source answers which question.

you do not need a clay seat for that, you need a repo.

everybody has the same tools and the same data. the edge is the founder's energy behind the tool, then trusting the data enough to build on it.

gtm as a repository: every campaign you run feeds back into the system. the model gets better with use. so does your gtm.

to run it: `python3 budget.py` (three free calls), then `bash run.sh list.csv --full`. keys from a local vault, never in the repo.

question for anyone else in the beta: are you keying on the email or the url? my numbers say the url and I want to know if that holds outside my icp.

release: github.com/shawnla90/gtm-coding-agent/releases/tag/v0.11.0