The One-Sitting Motion
You are bolting AI onto outbound and you do not have four weeks to build it step by step. This is the condensed version of the AI-Native GTM Series: the same score, enrich, watch, and learn moves run in one sitting instead of across four episodes.
DIRECTIONS
- 1Run the icp scoring
Score and stack-rank the market, channel-fair.
COOK WITH AN ICP SCORING · OURS: icp-scoring · OR YOUR OWN
MEDIA · STEP 1 SCREENSHOTWhat this step's output looks like - 2Run the enrichment analyst
Fill the gaps so the score has data to run on.
COOK WITH AN ENRICHMENT ANALYST · OURS: enrichment-analyst · OR YOUR OWN
MEDIA · STEP 2 SCREENSHOTWhat this step's output looks like - 3Run the icp scoring
Re-run the score on the newly-enriched Tier 1, so the rank reflects real data instead of the pre-enrichment guess.
COOK WITH AN ICP SCORING · OURS: icp-scoring · OR YOUR OWN
MEDIA · STEP 3 SCREENSHOTWhat this step's output looks like - 4Run the product usage analyst
Turn usage into a signal a rep can act on.
COOK WITH A PRODUCT USAGE ANALYST · OURS: product-usage-analyst · OR YOUR OWN
MEDIA · STEP 4 SCREENSHOTWhat this step's output looks like - 5Run the qa agent
Watch the motion and turn every miss into a lesson.
COOK WITH A QA AGENT · OURS: qa-agent · OR YOUR OWN
MEDIA · STEP 5 SCREENSHOTWhat this step's output looks like - 6Run the evolution agent
Close the loop so the system improves itself.
COOK WITH AN EVOLUTION AGENT · OURS: evolution-agent · OR YOUR OWN
MEDIA · STEP 6 SCREENSHOTWhat this step's output looks like
THE FINISHED DISH · WHAT YOU SERVE
In one pass, not four episodes: a scored market, enriched accounts, a fresh re-score on real data, a product-usage read, a QA agent that watches it, and a loop that learns.
GO DEEPER · The full playbook page carries the guide, the proof build, and the receipts. Read it.