The GTM Engineer bridge.
Resolve AI closed $125M at a $1B valuation in December, with Coinbase, DoorDash, and MSCI already in the logo book. Ben is 5 months into building the commercial motion from scratch, and the data, ops, and growth plumbing under it lands on you. I run the GTM Engineer function next to you while you hire so the layer under the next AE wave is actually wired before they ramp.
The enterprise plays are closing faster than the system under them can absorb.
Coinbase, DoorDash, and MSCI did not close on a repeatable motion. They closed on founder-led conviction and an early AE. The next 20 enterprise deals will not. Without the playbook reverse-engineered, the signals wired into CRM, and the handoffs codified, every new AE rebuilds the motion from memory and growth becomes a hiring problem instead of a system problem.
Three things only an internal builder can fix.
3 anchor logos, 0 reusable playbook
Coinbase, DoorDash, and MSCI each have a story that needs to be pulled apart into personas, objections, and proof points. Right now that lives in Ben's head and a few Gong calls. New AEs cannot ramp off that.
Signals are not yet CRM-shaped
At a 1B valuation buying signals exist (funding, exec moves, infra events). None of it is wired into stage logic, rep alerts, or outbound sequences. Growth has to build that layer before the AE team can act on it.
Ops carries the build alone
Data and Ops sitting under Growth means you own the plumbing under sales, marketing, and CS at once. That is a 3-person job. A GTME alongside you compresses the runway.
Reverse-engineer the enterprise motion, then wire the signal layer under it.
- Weeks 1 to 2
Pull Coinbase, DoorDash, MSCI into a playbook
Sit with Ben and the AE who ran each cycle. Map personas, objection pattern, proof points, and timeline into a single doc the next 5 AEs can ramp against.
- Weeks 3 to 4
Wire the signal-to-CRM layer
Equipment-event triggers, hiring signals, infra moves into HubSpot or whatever sits underneath. Rep alerts, outbound sequences, and stage logic so the AE wave walks into qualified pipeline, not a blank list.
Six production signals, shipped in 2 weeks.
Daylit closed Series A and needed an AE-ready territory before the first NA hire ramped. I built the ICP signal layer. Six buying signals piped from raw data sources (theirstack, Crustdata, news APIs) through Anthropic evidence-chain classifiers into HubSpot, with Slack alerts on high-fidelity hits. The first AE walked into a defined territory, not a cold start. 2 weeks. Same fixed-fee discipline.
Same play I would run for Resolve AI. Different stack, same fixed-fee discipline.
$15,000, fixed. 6 weeks. One invoice.
- Signal architecture
- Account list and buying-committee map
- Sequence build, live send, and deliverability infrastructure
Documentation and handoff included, not billed. If volume justifies it after the bridge, $25,000 / 90-day retainer extends the system. Your call, not mine.
Reply if this maps to where you are.
Send me a sentence on what is most exposed right now (playbook, signals, or handoffs) and I will reply within a day with a 1-page scope and an honest read on whether this fits.