Marketing operations and AI systems
I spent sixteen years in B2B marketing operations, managing teams, budgets, martech stacks and campaign execution. Then I started using AI and coding tools to build solutions for business needs.
My background is in running teams, budgets, martech stacks and campaigns. I started building because I wanted better ways to solve challenges in GTM.
My vision is using AI to operate at the speed of strategy, through continual learning applied to business problems.
Production AI systems
These systems went into production, produced work teams could use, and impacted measurable business outcomes.
I built an automated workflow that turns manual account research into a ten-section intelligence report, including an org chart, strategic priorities, earnings-call analysis, discovery questions and slides.
The system tripled lead-to-meeting conversion and produced roughly ten times the typical partner-outreach meeting rate.
Read the case studyI built a form-based tool with Azure OpenAI and Python. Marketers receive multiple banner versions in every required size, matched to the style guide and ready for a larger ABM content engine.
It personalized banners for around 100 accounts in under an hour, with double-digit lifts in ad click-through rate.
Read the case studyI built a three-agent team for technical SEO audits, visibility and keyword-gap reporting, and social drafting. The agents use a project management tool to work with human teams.
The system produced SEO and AEO research, analysis and content, along with a complete plan to improve rankings.
Explore the AI systemsPersonal
Atlas, Sift and Vigil run 24/7 on my own infrastructure, covering research, writing and publishing on their own schedule. I use the system to experiment, learn and see what is applicable.
I also built the monitoring dashboard that handles work assignment, status tracking and cost monitoring.
See how The Pod worksApplied AI for Marketing Ops
My Substack newsletter covers practical AI implementation for operations professionals, including what works inside corporate environments with enterprise constraints.
The four layers behind every AI output, and how each one changed the results when I tested them on a website rewrite.
NewsletterJuly 18, 2026Put your most capable model on the strategy and cheaper models on the review and QA to get better results.
NewsletterJune 19, 2026AI promises to move as fast as your strategy changes. For that to work, you have to know what your strategy actually is.
NewsletterOn Substack, I write about the systems, choices and lessons behind practical AI implementation.
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