I build AI systems inside your revenue stack.
Embedded with your team, working in your tools, shipping production agents from week one. Not advising from the outside. Building from the inside.
Stack agnostic. Model agnostic. Outcome obsessed.
Four hats. One operator.
Not prototypes. Not pilots that die in a sandbox. Production systems your revenue team runs every day.
Forward Deployed Engineer
Working inside your CRM, your data, your workflows. Production systems your team owns, not pilots that stall in a sandbox.
GTM Engineer
AI SDR motions, lead scoring, enrichment, competitive intel. RevOps that runs itself instead of running your team.
Builder with AI
Agents, custom skills, MCP integrations, multi-model pipelines. If it ships and runs without me, it's done.
Embedded Teacher
Workshops, leadership sessions, and side-by-side enablement until your team builds without me.
No prescribed toolkit.
No default model.
Your stack is the starting point
I build into the tools you already run, not around them.
Fit to your circumstances
Team skills, budget, security posture, stage. The solution matches all four.
Models chosen per use case
Reasoning depth, latency, cost, context window. Never loyalty.
Everything transfers
Docs, training, handoff. Your team owns what we build.
The right model for the job. Every job.
Anthropic Claude
Skills, MCP, and the Agents API power most of what ships.
OpenAI
Drafting, classification, and high-volume generation where throughput wins.
Google Gemini
Long-context analysis and synthesis across big document sets.
Perplexity
Live, cited web research at the front of pipelines.
New models are benchmarked on real client workloads and swapped in when the numbers say so.
A working catalog, not a wishlist.
Every agent here has shipped inside a real revenue team.
01AI SDR & Multi-Persona Outbound
Segmented outbound that sounds like your best rep.
02Lead Scoring & Routing
Signals in, prioritized pipeline out.
03Account Research & Planning
Briefs that land before the call does.
04Competitive Intelligence
Battlecards that update themselves.
05Content Production
Brand-voice content with the author in the loop.
06Customer Success Watchers
Accounts flagged before they churn.
07LinkedIn Engagement
Presence that compounds without the daily grind.
08Meeting Intelligence & CRM Hygiene
Every call becomes clean CRM data.
09Agent Advisory Blueprints
The build plan, even if your team builds it.
Running today, inside revenue teams.
Account Intelligence System
Pre-call research briefs assembled automatically and delivered before every meeting.
AI SDR System
Segmented, multi-persona outbound with a human review gate before anything sends.
Named Account Research System
Automated account briefs delivered where the team already works.
Competitive Intelligence System
Live battlecards and dashboards that track competitors as they move.
Content OS
A brand-voice content operation with the author in the loop.
RevOps Automation System
Meetings become CRM updates, weekly reports, and client comms. Automatically.
Embedded, not advisory.
Inside the Team
Weekly cadence in your Slack, your standups, your tools. I work where your team works.
Ship Week One
The first production system goes live in days. Momentum from the start, not after a discovery phase.
Build → Teach → Transfer
Documentation and enablement ship with every system. Your team owns it when I step back.
Ways to engage
Series A through enterprise, across B2B.
Classic plays, rebuilt AI-native.
Every play here started as a motion someone ran by hand. Today they run live inside client revenue stacks, tagged by the industries using them.
Closed-Lost Re-Engagement
Forget the 9-month re-engagement timer. An agent watches closed-lost accounts for stacked signals, like a new VP landing or the blocker leaving the company. When enough stack, it pulls the last call transcript and finds the objection that actually killed the deal, then drafts outreach about what changed since. Tier 1 routes to a rep. The rest sends itself.
Micro-Campaigns via AI Agents
The agent spots the pattern a human used to spot. When multiple signals stack on a set of accounts inside a short window, it builds a scored micro-list of 50 to 100 contacts and writes copy for that exact moment, then stages everything for approval or just runs it. The campaign didn't exist yesterday and won't be relevant in three weeks.
Champion Tracking + Warm Intros
Three relationship plays running on one graph. The agent maps champions and past champions, their job changes, their prior companies scored for ICP fit, and your investor overlap. When any node moves, it evaluates every warm path into the account and ranks them by likelihood, then drafts the specific ask. A promotion counts too: more budget authority deserves a bigger re-engage.
Competitor Displacement
A job posting naming a competitor tool is interesting. A negative G2 review from the same account makes it a displacement opportunity. The agent pulls the specific pain out of reviews and posts, maps it against your differentiators, then writes outreach around what the prospect's team is actually saying. The battlecard stays in the drawer.
Pre-Call Brief + Meeting Deck
Thirty minutes before every first call, an agent drops two deliverables in the rep's Slack: a one-page research brief with conversation starters and likely objections, plus a short deck built for that specific prospect. Every rep walks in as prepared as your best rep. After the call, the transcript feeds back in and the brief gets smarter.
Account Planning Agent
One command pulls the full Salesforce bundle, twelve months of Gong transcripts, and cited public research for an account, then cross-references it into ARR trajectory, open commitments, and stakeholder gaps. Out comes a 2 to 3 page plan in the team's own template, rendered for the role reading it. Refreshes append what changed instead of overwriting human edits.
Custom Data Dashboards
The modern BI playbook. Data from across your stack lands in one flat layer on Supabase and Pinecone, where custom AI agents can actually query it. Dashboards ship to secure hosting on Netlify or Vercel and answer questions static reports never could.
Whatever you run, I build in it.
Fifteen years in B2B go-to-market. Now building inside it.
Three-time VP of Marketing. Two-time founder, including a technical founder run building identity verification on the blockchain. Today: an embedded fractional GTM engineer shipping AI systems inside revenue teams.
Instructor at Pavilion, Athena Alliance, and Xapa. Publishes on YouTube, LinkedIn, and Substack.
Questions buyers actually ask.
What is a Forward Deployed Engineer for GTM?
An engineer embedded inside your revenue team who builds AI systems directly in your stack. Not an advisor with a deck. The first production system typically ships in week one, and everything transfers to your team with documentation and training.
How fast does the first system go live?
Week one. The work starts inside your existing tools instead of with a discovery phase, so the first production system is usually live within days and expands from there.
Do I need a specific CRM, stack, or AI model?
No. Your stack is the starting point, and solutions are built into the tools you already run. Models are chosen per use case based on reasoning depth, latency, cost, and context window. Evaluation over allegiance.
What kinds of systems do you build?
Production systems for pipeline generation, account research, competitive intelligence, content, and RevOps. The play library above is the working catalog, not a wishlist. If it ships and runs without me, it's done.
How do engagements work?
Pick the shape that fits: a fractional retainer with embedded weekly work, a scoped project SOW for a defined system, or workshops that level your team up hands on keyboard. Most clients start with one system and expand.
Who owns the systems after you leave?
Your team does. Documentation and enablement ship with every system, and the goal from day one is that everything runs without me. Build, teach, transfer.