About

I build systems that make marketing and operations smarter.

My path: 10 years in marketing operations → data pipeline architecture → AI implementation. I’ve managed $2M+ ad budgets, built CRM-to-analytics pipelines, and now I’m designing intelligent workflows using LLMs, multi-agent systems, and automation frameworks.

I’m reporting from the edge of the AI evolution—exploring automation, intelligence, and the systems that shape our future. Through field notes, build logs, and mental models, I document what I’m learning at the intersection of AI and practical application.

Currently focused on AI agents, automation workflows, and the cognitive tools that amplify human intelligence. Join me on this frontier.

What I Do

Current work: Building production GenAI systems—document analysis with GPT-4, research automation with RAG architecture, workflow orchestration via Claude Code and MCP integrations. I focus on practical AI implementation for organizations that need it to actually work, not just pilot.

Background: Marketing operations gave me deep understanding of where business processes break. Data pipeline architecture taught me how to build infrastructure that scales. Now I’m bringing both to AI implementation—connecting what the technology can do with what organizations actually need.

Focus areas:

  • LLM orchestration and prompt engineering
  • Data pipeline architecture (BigQuery, Cloud Functions, ETL design)
  • Marketing technology and CRM automation
  • Strategic frameworks for AI adoption

The Three Horizons Framework

I developed the Three Horizons Philosophy to map how AI integration evolves across personal, team, and organizational levels. It’s a strategic thinking tool for understanding where we are, where we’re going, and what capabilities to build now.

This isn’t reactive documentation—it’s predictive architecture. Organizations that develop systematic approaches to AI integration now will have significant advantages as these patterns become widespread.

How I Think

Research on cognitive styles in technology shows that INTJ patterns are the most overrepresented in tech careers—17.72% vs. 2.1% in the general population. The Ni-Te function stack (Introverted Intuition + Extraverted Thinking) is particularly prevalent in software and systems work.

This isn’t personality test trivia. It’s a functional description of how I process problems:

  • Ni (Introverted Intuition): I see patterns and trajectories before specifics. The direction of a solution often becomes clear before its content.
  • Te (Extraverted Thinking): I drive to structure and systematize—turning intuitive vision into actionable frameworks.

The result is what I call the Scaffolding Method: build provisional structures first, iterate as clarity emerges, stabilize into production systems. Clarity comes through building, not before it.

INTJ Cognitive Alignment with AI and Tech Careers — Deeper analysis of how cognitive patterns align with AI work.

Currently

Pursuing AWS Solutions Architect certification. Building GenAI tools. Exploring how AI amplifies rather than replaces human judgment.

Philosophy & Approach

Predictive Architecture over Reactive Analysis: I build intellectual infrastructure for emerging realities rather than documenting current states. This approach recognizes that strategic frameworks must map territories that don’t fully exist yet but are inevitable based on systematic pattern recognition.

Human-AI Collaboration Focus: AI’s greatest potential lies in strategic amplification of human judgment, vision, and values—not replacement. The most valuable applications emerge from understanding how human-AI collaboration evolves across personal, team, and organizational levels.

Early-Adopter Strategic Positioning: Organizations that develop systematic approaches to AI integration will achieve significant competitive advantages. This site develops the strategic thinking tools needed for effective navigation of this transformation.

Let’s Connect

Currently open to opportunities in AI implementation, marketing technology, and strategic consulting. I’m particularly interested in organizations navigating AI adoption—especially mid-market companies that need practical, deployable solutions rather than experimental pilots.

Email: dspjson@gmail.com GitHub: @jasonleinart LinkedIn: Connect with me

If you’re building at the intersection of AI and business operations, or working on strategic frameworks for AI adoption, I’d love to hear from you.

About This Site

This site is built with Jekyll and the Hydejack PRO theme, hosted on GitHub Pages, and continuously evolved as I experiment with AI-assisted content creation and curation workflows.

It’s part research notebook, part project documentation, part public learning experiment. The goal is to demonstrate that you can maintain authenticity and depth while leveraging AI tools to enhance (not replace) human thinking and creativity.

Content types:

  • Field Notes - Research paper analysis and insight extraction
  • Build Logs - Technical project documentation
  • Mental Models - Strategic frameworks and big-picture thinking
  • Now - Current focus and evolution tracking