Conversations and appearances.

James examines the rapid rise of the GTM Engineer role — up from effectively zero to 1,400+ open U.S. roles in a year — and what it means for RevOps professionals. The argument: RevOps teams that restrict their value to tooling and reporting will lose ground; those who own strategy and systems thinking will thrive.

James argues that AI initiatives fail not because the technology is inadequate, but because organizations lack clean data and disciplined processes. Companies must fix their operational fundamentals before layering in AI — artificial intelligence amplifies existing strengths and weaknesses alike.

Topline editor Asad (CEO, Sales Talent Agency) cites James — calling him “the sharpest RevOps mind I know” — in a piece arguing that 11X’s fraud doesn’t prove AI SDRs are doomed. James is quoted: “There is going to be a point where they equal all meaningful metrics we can expect from human SDRs. That’s inevitable.”

James discusses why revenue operations has become essential for B2B companies scaling past early growth, the most common mistakes teams make, and what good RevOps actually looks like in practice. Also covers the Canadian startup ecosystem and his path from film studies to founding VEN.

James joins Marcos Rivera (CEO, Pricing I/O) to discuss defining RevOps and its role in the customer journey, the right timing to build a repeatable sales process, CRM data governance, balancing automation with user adoption, and AI's impact on the RevOps profession.

James joins host Ed Porter to discuss how VEN evolved from a failed software startup into a RevOps consultancy, managing CRM data and customer journey stages, and implementing RevOps best practices for early-stage startups.

James covers what RevOps actually encompasses, the most common CRM implementation mistakes, how to transition from founder-led sales to a formal sales team, and why hiring the wrong sales leader stalls growth.

James discusses CRM data quality, building the right tech stack, aligning RevOps with financial planning, and realistic revenue forecasting. Core argument: build your sales process first, then choose your tools.

James identifies four root causes of poor CRM data quality he sees repeatedly across clients: non-technical users struggling with complex systems, inconsistently applied pipeline stages, neglected data maintenance routines, and misalignment between strategy and technical infrastructure.