Step 01
Map how you actually sell
AI-led interviews capture how you qualify, chase, and close while we read what the CRM, product data, and billing actually show. The gap between the two is the ramp doc nobody has written: everything an AE would have to shadow you for months to absorb, charted in one map.
Output: your sales motion, mapped and written down
Step 02
Join the deal context
Product usage, CRM, billing, and support join into one account picture in a warehouse you own. The context you carry into every call, what they pay, what they use, what broke last week, becomes a record anyone on the team can pull up in seconds.
Output: founder-grade context on every account
Step 03
Encode your instincts
Your gut calls become explicit rules the system runs: what makes a trial worth a call, when an account has gone quiet too long, which signup you would drop everything for. The morning queue you used to assemble in your head starts arriving assembled.
Output: your instincts, running as scoring and routing
Step 04
Ship the handoff workflows
Routing, follow-up queues, deal-stage alerts, and lifecycle rules ship as code to your repo. When AE one starts, their book, priorities, and call briefs come from the system, so they spend week one selling instead of reverse-engineering your sent folder.
Output: workflows a new AE runs on day one
Step 05
Watch what the machine catches
The weekly report shows what the system surfaced, what got worked, and what moved: the expansion you would have spotted anyway, and the ones you would not have. You stay the best closer on the team without being the only routing layer the company has.
Output: a weekly ledger of what the machine caught
Step 06
Let the team sharpen it
Every closed deal, lost deal, and false positive tunes the model. New AEs adjust thresholds without asking what you meant, and the agents you add later work from the same memory. Your judgment keeps compounding after you step out of the daily pipeline.
Output: a sales memory that outlives the handoff