Alex breaks down what content engineering actually means: building the systems infrastructure to maintain quality, freshness, and brand accuracy across everything a company has ever put online. He makes the counterintuitive case that great content engineering puts more humans into the content process.More
Category Archives: career
219: Elizabeth Dobbs: Inside Databricks’ stack with 3 AI agents, 1 lakehouse, and 6 years of data work
Liz spent 6 years at Databricks building the data infrastructure before deploying any AI on top of it. She’s shipped 3 production agents (Marge, Tagatha, and Atlas) and she’ll tell you exactly what broke first and why the team kept going anyway. You’ll hear how a marketing lakehouse becomes the foundation that makes every agent actually work, why the agent label debate is a distraction.More
218: Tata Maytesyan: Build a marketing career that survives AI as a deep generalist
Tata breaks down why the best AI automation targets are the boring, repeatable tasks nobody talks about on LinkedIn, and why the specialist-to-generalist shift in marketing is already happening whether your org chart reflects it or not. She also gets direct about the 10,000-hour threshold for building genuine competence across domains, and the self-preservation fear she hears from leaders every week. More
217: How to interview a company before you take the job (The Martech job hunt survival guide, part 3)
Darrell shares a firsthand account of taking a job under financial pressure, ignoring red flags he recognized in the moment, and landing in a toxic environment within months. What follows is a structured set of interview questions across 6 categories, from leadership self-awareness to what happened to the last person in the role, designed to help you separate the job offer from the job reality.More
216: How to stand out as a candidate with AI prep, portfolios and tools (The Martech job hunt survival guide, part 2)
What actually moves the needle when you’re searching for a role: building the portfolio that almost no marketing ops professional bothers to save, navigating the AI experience question, knowing when to take a contract role instead of holding out, and skipping the AI job-search tools that make you look like everyone else.More
215: How to find hidden job opportunities (The Martech job hunt survival guide, part 1)
This episode is a guide for martech and marketing ops professionals navigating one of the toughest job markets in years. Phil and Darrell cover the tactical mechanics of finding roles most candidates never see. From the Ashby Google search hack to VC job boards, staffing firm pipelines, and stealth startup cold outreach, the counterintuitive moves are the most useful ones here.More
207: Building a career that doesn’t hollow you out (50 Operators share the systems that keep them happy, part 3)
Treat your career as something you design, not something that just happens to you. You’ll ship a lot of stuff in your life. You only get one self, one mind, one body, and a short list of things that genuinely light you up. Building a career that does not hollow you out starts when you let those things set the terms. More
206: The people who keep you standing (50 Operators share the systems that keep them happy, part 2)
Think about the relationships that matter most to you and treat them like they are part of your happiness infrastructure. Protect dinner where phones stay facedown. Call the person who steadies your nervous system instead of refreshing your inbox when stress spikes. Work will fill your calendar. But your humans will keep you upright.More
201: Scott Brinker: If he reset his career today, where would he focus?
Scott Brinker would build one deep specialty to judge AI’s confident mistakes, grow cross-functional range to bridge marketing and engineering, and lean into technical skills like SQL and APIs to turn ideas into working systems. More
179: Tiankai Feng: The comeback of data quality and how NLP is changing the data analyst role
Data governance feels like the Jedi Council, steady with its rules, while marketing ops moves like the Rebel Alliance, quick to adapt when perfect data never arrives. Tiankai believes progress comes from blending discipline with curiosity, bringing data in early as a partner, not a critic.More