AI Enablement
Applied AI for your GTM team.
Most revenue teams bought AI tools and saw nothing change. Everyone has the same models now. What separates teams is an owned system that gets smarter every week - your context, your workflows, your evals. We embed for 4-8 weeks and build it with your team.
Book a CallThe same tools, wildly different teams.
Nearly every sales org uses AI now. Most leaders will tell you it hasn't moved the number. What separates the teams pulling ahead is what they built underneath the tools - a system that owns their context, deploys to the whole team, and gets measured every week.
Chat
Reps use ChatGPT to write cold emails. The output is faster, but worse. Nothing about the workflow changes. AEs re-upload context from their sales calls into a new Claude session every day. Most teams are here, and think they have climbed.
Tooling
The team writes reusable prompts, Clay tables, and skill files. Tools get connected with Zapier and n8n, and lists get generated faster. Real gains - but the leverage sits with whoever built it, not the whole team.
Applied AI
The team runs GTM like an Applied AI org. One centralized context layer feeds every workflow, so the AI knows your ICP, your messaging, and your wins. Systems are deployed to the whole team, not trapped on one laptop. Every output is checked against evals, so quality is measured, not hoped for. This is what the top 1% of revenue teams have built, and almost no one else has.
The distance between the teams compounding and everyone else widens every quarter. More tools won't close it. An owned system will.
We build the capability, then hand it over.
Most AI training teaches prompting in isolation. It doesn't stick. People sit through a workshop, go back to their inbox, and nothing changes.
What sticks is building real workflows on your real problems, with us in the room, then documenting them so your team can evolve them after we leave.
And the work is never finished. Models change every few months, costs shift, and a workflow that worked last quarter breaks. A system someone hands you goes stale the moment the ground moves. A team that can rebuild it doesn't.
That's the whole difference. When a traditional agency leaves, you start from zero. When we leave, your team has the working systems, the SOPs they wrote, and the muscle to build the next thing themselves. Retention should come from wanting our speed, not needing our knowledge.
One system, centralized. Built by a few, run by the whole team.
The systems team
Your Applied AI owners
A small group builds and maintains the workflows, the integrations, and the evals - the engine the rest of the team runs on. Their build is not marginally better than a rep's weekend prompt. It is an order of magnitude better.
The whole GTM team
Reps, AEs, marketing, ops
Everyone draws on the same centralized system where they already work, in plain language. One shared context layer, one set of workflows. They get the leverage without having to build it.
The engagement
Four to eight weeks. Built on your data, not generic examples.
Assessment
Leadership commits to one measurable goal. We map each role's real workflow, find where AI is and isn't helping, and pick 3-5 high-impact problems to solve.
Foundations
Your core systems set up and connected to your CRM, email, and Slack. Your team encodes its ICP, messaging, and positioning into a shared context layer the whole team draws on - the onboarding doc your AI reads every session.
Co-build
Each week: pick a problem, design the workflow, build it live as a team, test on real data, write the SOP. We lead the hard parts. Your team owns the output.
Handoff
Every workflow has an SOP your team wrote, not us. Then the independence test: each person builds a new workflow from scratch, with us out of the room.
What a real GTM system on AI actually looks like.
Most teams that call themselves "AI-native" are drafting emails faster. This is the difference - a full walkthrough of running GTM on a real system:
- Scoring tens of thousands of prospects in minutes
- Pulling sales call transcripts into context automatically
- Prospect research your $15K B2B database can't give you
- When to build it yourself vs. when to buy
What your team owns when we leave.
- Working AI workflows built on your data
- An SOP for every workflow, written by your team and reviewed by us
- A centralized context layer that encodes your GTM intelligence
- Custom tools your systems team built, that the whole team runs
- The ability to build the next workflow without us in the room
Stop renting AI capability. Build it in-house.
We embed with your team for 4-8 weeks to co-build AI workflows on real problems - and leave them able to build their own.
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