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—— THE AI-NATIVE GTM SERIES · PART 3 OF 4

Build your signal library and wire it to motion

Episode 3, made runnable. You built the context brain in Episode 2. The signal library is the file that turns it from a reference doc into a system that acts. Define your signals, then wire the freshest to a motion. A signal without a motion is just a dashboard.

Install the whole playbook ↓BUILD BETTER · SERIES 1 Watch the episode →
POWERS UP WITH YOUR STACK
HOW TO CONNECT →
ClayApolloZoomInfoClearbitCognismCommon RoomSalesforceHubSpotAttioPipedriveDynamicsAmplitudeMixpanelPostHogHeapPendoSegmentGmail
1Solve the problem

You have signal everywhere: usage spikes, intent, funding, hiring. And it dies in a dashboard nobody acts on. Worse, most teams never decay it, so their active list quietly fills with six-month-old events. A signal without a motion is just a chart.

RUN THIS AND YOU CAN
  • ✓Build a real signal library: detection, points, decay, and combinations
  • ✓Score the account the signal fired on, so you work the right ones
  • ✓Wire the freshest signal to a touch before it goes stale
  • ✓Route and log the output so the library learns which signals pay
2See it in production

Before you run it: I ran it for real.

This workflow is genericized from a real build. Here is the number it moved, what I actually did, and a way into the whole story.

THE BUILD · PRODUCT-LED MOTION
The Product Channel
~47%
qualified win rate, the highest of any channel
$1M+
in sales-qualified pipeline, built from zero
Best GRR + NRR
of any channel, it retained and expanded best too
414% of plan
the pipeline the channel actually delivered
WHAT I DID ›
01
Map the events first. I mapped what users actually did in the product to what it meant for a sale. Not every event, the ones that predicted buying.
02
Centralize the signal. I centralized our Snowflake product data with enrichment and signal data by implementing Common Room and Deepline, so a usage spike at an account arrived already enriched, already scored, already routed.
03
Build the motion on top. The signals worth acting on, the play that worked them, and the routing that put a real user in front of a real rep with a real reason to talk.

If you sell a product people can use before they buy, you already have a product-led channel. The question is never whether it exists. It is whether your usage data has been turned into context a rep can act on. Map the events first. The motion comes after.

Dig into the full build →
SEE IT RUN

The plain questions, answered in order.

Each step is the plain question you are already asking. The skills answer them in order, one handing its receipt to the next.

Define your signals
“Which signals actually mean now?”
OPEN THE SKILL →
Wire it to motion
Score the account the signal fired on, so you work the right ones, not every ping.
OPEN THE SKILL →
Wire it to motion
Wire the freshest signal to a timely touch before it goes stale.
OPEN THE SKILL →
Wire it to motion
Route the output to the record, channel, or rep, and log it so the library can learn.
OPEN THE SKILL →
EXAMPLE CHATTheo, a RevOps lead, running the loop in one sitting
T
We have intent data, funding alerts, product usage, all of it. And it just sits in dashboards nobody acts on. How do I turn signals into actual pipeline?
D
Define your signals· Build signal library
The problem is not more signals, it is that they are not defined or decayed. I built the library: your 6 highest-intent signals, each with a detection method and points scored against fit, a decay curve so old events stop floating up, and combination bonuses. A Series B plus a new RevOps hire scores 80, not 65.
Signals6, scored and decayed
Combo bonusSeries B + RevOps hire = 80
Receipt
A signal library in context/signal-library.md: 6 signals with detection, points, decay, combinations, and hooks, plus an empty performance log.
T
Okay, the funding-plus-hire combo just fired on 40 accounts. How do I know which to actually work?
W
Wire it to motion· Score against ICP
Scored those 40 against your ICP and the signal weight, so fit and timing combine. 11 are Tier 1 with a fresh combo; the rest are Tier 3 noise or already decayed. Work the 11.
Receipt
40 accounts ranked, 11 Tier-1 fresh-combo accounts surfaced, the stale and low-fit ones filtered out.
T
Great. The top one is a fintech that raised last week and just hired a RevOps lead. What do I send before it goes cold?
W
Wire it to motion· Trigger outreach
Used the hook tied to that combo, not a generic funding congrats. One short touch that names the moment, the new hire, and the one thing that breaks at their stage. Sent while the signal is 6 days old, not 60.
Receipt
A first touch drafted off the signal's own hook, sent inside the freshness window.
T
How do I make sure this does not vanish, and that we can tell what actually worked?
W
Wire it to motion· Route and log
Wrote the touch and the signal that drove it back to the CRM record, pinged the owning rep in Slack, and logged which signal fired so the performance column starts filling. Next episode turns that log into a system that learns.
Receipt, loop opened
Signal wired end to end: defined, scored, acted on fresh, routed to the rep, and logged, ready for Episode 4 to close the loop.
RUN IT YOURSELF

Two steps to run this yourself.

1

Install the skills. Grab the one-command install below. Once installed you never call a skill by name, you just describe your situation and the right skill fires on its own.

2

Paste this to kick off. Swap in your own situation and the skills run in order.

“Here is my situation: [describe your workflow or account in a sentence or two]. Walk me through Build your signal library and wire it to motion step by step, and run each skill as we go.”
3The ideal run, step by step

The workflow that solves it, one step at a time. Each step hands off to the next. Tab through the run.

Build a signal library that fires, decays, and combines.

Define your signals
Build a signal library that fires, decays, and combines.
WHY THIS STEP
Define your signals: detection, points, decay, and combinations. Not a list of alerts.
WHAT IT DOES
Turns "we should watch for funding" into real signals: how you detect each one, what it is worth, how it decays, which combinations score higher, and the hook that earns the reply. The file that makes your context repo act.
YOU GETThe detection method, the points, the decay curve, the combination bonuses, the hooks, and a performance-log stub.
POWER IT UPClayApolloZoomInfoClearbitCognismCommon Room
OPEN THE SKILL →
WHERE YOU LAND

A real signal library with detection, decay, and combinations, then one signal scored, acted on while fresh, and routed back where it belongs.

INSTALL THE WHOLE PLAYBOOK

One plugin. 4 skills, bundled.

The whole playbook installs as a single plugin in Claude Code, no copy-pasting 4 times. Or grab any single step from the run above. It runs on what you paste; connect your stack to go live.

THE AI-NATIVE GTM SERIES · PART 3 OF 4
← PART 2
Build your GTM context brain this week
PART 4 →
Close the loop so your GTM compounds
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