GTM Case Study  ·  Crewm8  ·  AI Systems

I encoded a GTM team as software.

A 32-skill AI go-to-market system that sourced, scored, and personalized a full outbound campaign in a day.

Crewm8 is a pre-launch AI receptionist for local service businesses, and its GTM team is one person. So I turned the process a six-person team would have followed into modular, chainable AI skills with hard quality gates between every stage. Built on Claude Code, recorded in Attio.

RoleFounderGTM team of one
System32 AI skillsthe full funnel
CampaignBarbershops Canada30 leads, live in Attio
StackClaude Code + AttioCRM wired via MCP
TimelineJune 2026about 1 day end to end
  In one screen

A solo founder cannot run a six-person GTM process. Software can.

The problem

Outbound done properly is weeks of work for a full sales team.

Crewm8 is a pre-launch AI receptionist for local service businesses. Zero customers, zero brand, GTM team of one. ICP research, lead sourcing, contact verification, scoring, personalized copy, channel strategy, and compliance take a six-person team weeks. Doing it improperly with generic AI blasts burns the market before launch.

The solution

Turn the process the team would have followed into software.

A 32-skill go-to-market operating system built on Claude Code: modular, chainable AI skills that encode real sales methodology, with hard quality gates between every stage. No stage runs on unverified data from the stage before it. The AI cannot invent a personalization hook, send to an unverified email, or push past a compliance threshold.

The impact

A full campaign sourced, scored, and drafted in about one working day.

30 barbershops sourced, enriched, scored against a 100-point rubric, and given research-backed DMs. The CRM audit trail shows the core pass, from list to scores to drafts, landing inside a two-hour window. The estimated manual equivalent is 3 to 5 solo working days.

32skillssix phases, strategy to analytics
30leadssourced, enriched, scored
6Tier-1sales-ready, 75 to 80 / 100
30DMsresearch-backed, channel-routed
~2 hcore passby CRM timestamps
3–5 dmanual equiv.estimated, labeled as such
01  Architecture

A system, not a pile of prompts.

Anyone can ask a chatbot to write a cold email. The output is generic, unverifiable, and unsafe to send at volume. This suite works differently: it is a pipeline of specialized agents, and each one has a contract.

every connector is a quality gate, not an arrow

Infrastructure readinessNo cold email until SPF, DKIM, and DMARC are verified and the 14-day warmup score reaches 70.Torching domain reputation on day one
Verified-hook contractEvery outreach touch requires a [verified] personalization hook with a cited source.AI hallucinating personalization
Tier labelOnly Tier-1 and Tier-2 leads (score 55+) enter outreach. Tier-1 (75+) gates the sales handoff.Spraying the whole list equally
Confidence floorInbound replies below 0.75 classification confidence route to a human and are never auto-actioned.The bot mishandling a real buyer
Auto-pause thresholdsA 0.3% complaint rate or a 5% bounce rate pauses the campaign on its own.Compliance and deliverability blowups
So what

The system produces outreach a professional SDR manager would sign off on, at AI speed, with an audit trail.

02  Method

Real methodology, encoded as executable rules.

The skills do not just know about sales frameworks. They enforce them. The ICP scorecard is a fixed, weighted 100-point rubric applied identically to every lead.

Pain25 pts
Severity of the problem we solve: missed calls are missed revenue
Trigger20 pts
A recent, citable event that makes now the right time
Willingness to pay20 pts
Evidence they already spend on this problem
Reach15 pts
Can we actually contact a decision-maker?
Time to value10 pts
How fast they would see results
Strategic fit10 pts
Referenceability and segment learning value
Tier-175+

Sales-ready. Gated further by BANT and CHAMP checks before any lead is called hot.

Tier-255–74

Warm. Enters outreach, watched for a trigger that moves it up.

Tier-3< 55

Deprioritized. Never blasted just because the list exists.

Copywriting is equally constrained: the CCQ framework (Context, Connection, Question) with Pain-Trigger-Outcome openers, mobile-first formatting, and a hard ban on cliche openers like “Hope this finds you well.” Touch 1 must open with the prospect’s verified pain, not our product.

So what

Consistency at scale. Lead #30 gets the same rigor as lead #1, something even good human teams drift on by Friday afternoon.

03  Strategy

The call that shaped the campaign: skipping email entirely.

The obvious move for Barbershops Canada was a cold email sequence, and the suite has a full skill for it. I did not use it, for three reasons.

The audience is not at a desk.

Barbershop owners live on Instagram, which is their portfolio, and Facebook, which is their booking inbox. An email from a stranger is invisible. A DM is native.

The infrastructure gate said no.

Cold email requires a warmed dedicated domain, 14 days minimum. For a 30-lead local campaign that is the wrong cost-benefit, and the system's own email-infrastructure gate makes this explicit instead of letting you skip it.

Compliance is different in Canada.

CASL is stricter than CAN-SPAM. Conversational DMs with a soft opt-out and no link in the first message fit both the law and the culture.

The play, instead

Instagram and Facebook Messenger DMs routed to each prospect’s strongest channel, call-first for Tier-1 leads with a verified phone number. All of it in founder voice (“I’m building this, be one of the first”), leading with Crewm8’s wedge: the missed call during a haircut is lost revenue.

So what

The system recommends, but strategy decides. Knowing when not to use a tool you built is the actual GTM skill.

04  Evidence

What’s actually in the CRM: the receipts.

Everything the system produced lives in Attio as versioned, timestamped records, not in a chat log. Here is one Tier-1 lead, City Barber in Edmonton, moving through the whole machine, then the score rationale and the DM that came out the other side. All from the live workspace, phone number masked.

one lead, end to end ·  City Barber ·  Edmonton, AB · id web-ca-recept-20260619-028
01Sourcedlead-sourcing-web
found on
Booksy listing + open web
trigger
booking-friction-review
phone
pending enrichment
cost
$0 · no paid database

Sourced from a WebSearch query, provenance cited.

02Enricheddata-enrichment
phone
+1-780-758-•••• · [H] on citybarber.ca
domain
citybarber.ca (owned)
address
5590 Windermere Blvd, Edmonton
hook
cited review: online booker left waiting

Contactable. The hook is quoted, not invented.

03Scoredlead-scoring
score
80 / 100 · Tier-1
breakdown
pain 20.5 · trigger 18.0 · wtp 14.4 · reach 12.0 · ttv 7.5 · strategic 7.5
gates
all 4 SAL gates passed

Same 100-point rubric as all 30 leads.

04Pushedattio adapter
record
Attio · Companies
record_id
5ad52b5e-db38-4b52-9fe0-d993aa00b4b8
created
2026-06-19
state
live · versioned · auditable

The row you can open in the CRM today.

scoring note · 80 / 100 · Tier-1attio · verbatim

Scored vs ICP 100-pt scorecard (run web-ca-recept-20260619). Confidence: H. SAL gates: all 4 passed. Need = confirmed (the only lead with a real trigger: a public review about an online-booking client left waiting). Phone [H] confirmed. Strongest-evidence lead.

Every one of the 30 leads carries a note like this: the score, the confidence, which gates passed, and the evidence behind it.

DevangDM v1 · draft
hey! i'm devang, building an AI receptionist for barbershops. saw a review mention someone waiting after booking online while walk-ins went ahead. that phone/booking juggle is exactly what i'm trying to kill. when a call comes in mid-cut, where does it go right now?
channel: FB Messenger or CALL (phone verified, redacted)angle: founder, cites a real reviewstatus: draft · researched-by: Devang

Notice what the DM is doing. It opens with a real, citable observation the enrichment stage captured with its source, connects it to the exact pain Crewm8 solves, and ends with a low-pressure diagnostic question. CCQ, executed. No link, no pitch, CASL-safe.

One morning, by CRM timestamps
10:57

30-lead list pushed to Attio

11:40

All 30 leads scored, each with a rationale note

12:59

All 30 channel-routed DM drafts logged

List to scores to 30 finished drafts in two hours and two minutes, all logged before anything is sent.

  • 30 barbershops in the Barbershops Canada list, created June 19, 2026
  • 6 Tier-1 leads at 75 to 80 / 100, the majority Tier-2 warm, remainder Tier-3
  • One channel-routed DM draft logged per prospect: IG, FB Messenger, or call-first
  • v1 is never overwritten. Updates append as v2, so the copy's evolution stays auditable
So what

This is the difference between “I used AI for outreach” and “I ran a professionally instrumented campaign.” Every claim on this page traces to a timestamped record.

05  Safety

Guardrails are the feature, not the fine print.

The most powerful thing the skills do is refuse.

The DM helper refuses to invent.

If a logged DM exists, it returns it verbatim. If none exists, it does not generate one. It asks for research on that prospect and waits. Human research in, AI drafting out. That single rule is why every DM in the campaign cites something real.

Campaigns pause themselves.

Reply, bounce, and complaint rates are watched against hard thresholds, per Google and Microsoft's 2024 bulk-sender rules. Open rates are treated as noise, because Apple Mail Privacy makes them meaningless, and the system knows this.

Every block ships with an override.

A shared Clarification Protocol across all 32 skills means the AI never dead-ends. When a rule blocks an action it presents the options, the risk, and a recommendation. The human decides.

Compliance is encoded, not remembered.

CASL, CAN-SPAM, GDPR, LinkedIn rate limits, TCPA calling rules, and RFC 8058 one-click unsubscribe each live inside the skill that needs them.

AI leverage without guardrails is a liability generator. This system’s default answer to “should the AI just do it?” is only if it can prove it is safe, which is exactly what makes it usable for a real company’s reputation.

06  Impact

The honest version.

The campaign has not launched, so there are no reply metrics to report, and I will not invent any. Here is what is real and what is estimated.

Real · verifiable in the CRM today
  • A 32-skill GTM system, built and operational, spanning the full funnel
  • A 30-lead campaign sourced, enriched, scored, and fully drafted in about one working day; the core pass took roughly 2 hours by CRM timestamps
  • 6 Tier-1 leads identified with evidence-backed rationale, so outreach effort concentrates where conversion odds are highest
  • 100% of DMs carry a verified, source-cited personalization hook. Zero template blasts
Estimated · labeled, with assumptions
  • Time saved: 3 to 5 solo working days per 30-lead campaign.Assumes 30 to 45 minutes per lead for manual research, scoring, and a personalized draft of this quality.
  • Reply-rate expectation: 3% single-channel, 6% multi-channel by day 10.These are the system's own floors, the thresholds the campaign will be held to. They are not results.
  • Repeatability: the marginal cost of campaign #2 is near zero.The ICP, scorecard, copy frameworks, and CRM plumbing are already encoded. Only the research per lead is new.

GTM strategy

ICP definition, channel selection against the grain of my own tooling, wedge-based positioning, and compliance-aware sequencing.

AI systems engineering

32 composable skills with typed contracts, hard gates, provenance tracking, and CRM integration through Attio via MCP.

Judgment

Knowing where the human belongs in the loop (research, strategy, the final send) and encoding that boundary so the system cannot drift past it.

So what

The system’s proven value today is speed with rigor: team-grade GTM process at founder-of-one cost. The reply data comes next, and the icp-refinement-loop skill is already built to recalibrate the scorecard once about 30 outcomes exist.

  Crewm8 · 32-skill GTM engine

Want a GTM engine like this, or the person who builds them?

GTM strategyAI agentsClaude Code skillsLead scoringOutboundCRM automationCompliance

All campaign data referenced on this page is from Crewm8’s live Attio workspace. Phone numbers and personal contact details are masked. Estimates are labeled as such throughout.