What does a Fractional GTM Engineer do?

I build and optimize the AI systems that power your go-to-market — automated outbound, enriched pipelines, smarter CRM, and support automation. I focus on sales, marketing, and support teams because that's where most companies have the most repetitive work that AI can take over. I write the playbooks so your team runs it without me.

What AI consulting services do you offer?

AI Sales Development (lead enrichment, scoring, drafted outreach on arrival), AI Customer Support (automated triage, knowledge base management), AI Sales Enablement (meeting prep, post-call analysis), CRM & Data Enrichment (structured data extraction, deal monitoring), AI Content & Demand Generation (content workflows, outbound sequences), and AI Training for Non-Engineers (hands-on Claude Code training for PMs, marketers, and ops).

How much does AI consulting cost?

The AI Workshop is $5,000 for a one-day intensive. You get a full audit of your current AI usage, a list of quick wins, and a 90-day roadmap. Ongoing Advisory is $8,000/month with a 3-month minimum, then month-to-month. That covers strategy, team coaching, workflow prototyping, and async Slack/email support.

How long does it take to see results from AI consulting?

Quick wins usually land within the first 30 days. Measurable results across your sales, support, or marketing workflows typically show up by day 90. How fast depends on your team's readiness and which workflows we go after first.

Do you build the AI systems yourself?

I design the systems and write the playbooks. Your team builds. I'll prototype workflows and stick around as a fractional advisor to fix what breaks and adjust what's slow, but the goal is always to hand off ownership to your people.

What kinds of companies do you work with?

B2B companies with sales, marketing, and support teams that are ready to adopt AI. My background is 15+ years at Tesla, Mapbox, and HubSpot across growth, operations, and product management. The common thread is teams losing time to manual work that AI can handle.

Blog

Notes on AI strategy, team enablement, and the future of work.

April

Use technographic data to qualify accounts before your reps waste a single call

Firmographics tell you the company fits on paper. Technographics tell you whether they'll actually buy your product. Here's how to turn tech stack data into a qualification signal that routes the right accounts to your pipeline.

Blog

2026

April

Use technographic data to qualify accounts before your reps waste a single call

The Three Kinds of AI Work Your Company Is Actually Doing

Why the ROI Framing Kills Good AI Projects

What Responsible AI Actually Requires Operationally

Job postings are your best free source of buying intent — here's how to use them

The AI Literacy Gap Is a Leadership Problem

How to Scope an AI Project Before You Quote It

The Staffing Model for AI Is Broken

Build a competitor analyzer that keeps your CRM honest

The Six Things Every AI Strategy Document Should Answer

How to Think About AI Risk Without Paralyzing Your Team

What I Look for in the First Week of an AI Engagement

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The Fractional AI Model: Why It's Replacing Full-Time AI Hires

Build an email sequence writer that actually sounds like you wrote it

What a Good AI Proof of Concept Looks Like

How to Train Your Team to Use AI Without Making It Mandatory

March

Judgment Work Is Safe (For Now)

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What Good AI Governance Looks Like for a 50-Person Company

How to Run an AI Sprint in a Non-Technical Company

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Build a data cleaner that stops your GTM workflows from eating garbage

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When to Build vs. Buy AI (The Framework I Actually Use)

Why AI Projects Need a Product Manager, Not a Project Manager

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Build an AI-powered ICP scorer that handles the fuzzy stuff

AI ROI: Why Most Companies Measure It Wrong

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What I Tell Every Company in the First Meeting

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The Difference Between an AI Strategy and an AI Plan

The Rise of Agent-Centered Design

Why Your AI Pilot Failed (and How to Fix It)

Build a company research agent that replaces 12 open tabs

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