Nine Bay Area GTM engineers who actually teach: Jared Waxman and Tim Scheuer lead on public evidence

Asked:

“GTM engineer in SF and also sharing good tips online on twitter, linkedin, youtube, or any social”

This is a curated shortlist of 9 practitioners in San Francisco or the wider Bay Area whose current role is GTM engineering, growth engineering, or GTM systems/AI, and whose public content carries concrete, actionable advice. It was scanned on 2026-10-20 across LinkedIn, YouTube, podcasts, personal sites, company blogs, newsletters, and repositories — it is not every GTM engineer in SF.

Who has the most teaching on record

Bar = content references matched in this search corpus (not followers, not quality). Click a bar or name to inspect the person's example tip and links.

Jared Waxman is the strongest pick for structured GTM-engineer training: his GTM Engineer School webinar argues the context layer / “company brain” is the biggest AI unlock for go-to-market teams. youtube.com

Tim Scheuer shares the most reusable architecture: a stealable 4-layer AI-native GTM stack (data, reasoning, action, interface) instead of one agent per job title. explorium.ai

Karim Yahia is the GTM-as-code specialist: express GTM workflows as code a coding agent can run, and build a TAM-enriched account foundation before anything else. deepline.com

Daniel Ahmadizadeh is the tactical outreach pick: his “midbound” framework says to reach out within five minutes of a social engagement, when conversion odds are 21× higher. youtube.com

The full shortlist

Person	Role & company	Location	Where they publish	Example tip	Refs	Links

Method: curated shortlist of 9 GTM/growth-engineering practitioners in San Francisco or the Bay Area, scanned 2026-10-20 across LinkedIn, YouTube, podcasts, personal sites, company blogs, newsletters, and repositories. “Refs” counts content references matched in this search corpus, not followers or quality. Seven independent hosts back the shortlist; the largest, LinkedIn and YouTube, each support 2 of 9 rows (22.2%), so no single host dominates. Location and role are self-reported profile facts; some rows lack a publication date or direct channel URL. Long role titles and topic lists are shortened for space; full tips appear in the explorer above.

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