Humans of Martech

Business & Economics Podcasts

Future-proofing the humans behind the tech. Follow Phil Gamache and Darrell Alfonso on their mission to help future-proof the humans behind the tech and have successful careers in the constantly expanding universe of martech.

Episodes

238: The System to make your prospects the hero before they buy, with Aditya Vempaty

237: Designing the utopian marketing leadership role, with Mary Keough

236: What AI replaces in data work and when not to reach for it with, Julie Beynon

235: Why consent banners, tags and privacy policies never match, with Stéphane Hamel

234: How to run a marketing ops audit and turn it into a roadmap with Kelsie Dube

233: 4 Mindsets that modern marketing leaders need for unpredictable markets, with author Kathleen Schaub

232: How taste can be codified into systems and is no longer a durable skill, and what's next with Sharon Gai

231: Why Lattice careers and communication skills are built for the AI era, with Michele Martin from Ticketmaster

230: Zero-click marketing broke the measurement layer, so what should ops teams do now, with Amanda Natividad

229: The Privacy lawsuits coming for every marketing team, with Cara Caruso and Dustin Taylor

228: The Dispatch tower (The Dungeon of martech architecture, part 4)

227: The Correlation masquerade (The Dungeon of martech architecture, part 3)

226: The Eye of context (The Dungeon of martech architecture, part 2)

225: The Fall of CRM gravity (The Dungeon of martech architecture, part 1)

224: Keith Jones: How OpenAI’s GTM leader structures teams and spots standout candidates

223: Lindsay Rothlisberger: How Zapier uses a shared brain to manage AI context and skills

222: Ashley Langford: How Senior MOps Practitioners Are Navigating the 2026 Job Search

221: Jason Dobbs: You need Minimum Viable Readiness for AI because perfect data doesn't exist

220: Alex Halliday: How to build content engineering systems that get cited and scale without slop

219: Elizabeth Dobbs: Inside Databricks' stack with 3 AI agents, 1 lakehouse, and 6 years of data work