Magnetic Energy HR & Staffing Operating Plan

Status: Active implementation plan. Walt approved the isolated setter recruiting build, $10/month GHL WhatsApp, a dedicated HR Supabase project, a dedicated recruiting Voice AI agent/number, and the $150 referral extension. Every production object still requires exact execution/readback; end-to-end canary awaits a real internal test contact.

Human development lead: Walt, coordinating with management and AI development agents.

Planning method: Dependencies, acceptance evidence and approvals — not arbitrary dates.

Executive Summary

Magnetic Energy is connecting recruiting, screening, hiring, provisioning, training, measurement, compensation and offboarding into one auditable staffing operating system.

This revision preserves the original WhatsApp-led recruiting design while adopting the approved GHL, Cloudflare and Supabase architecture: job postings drive prospects first to the WhatsApp Business “Hiring Manager” for conversation and pre-screening; qualified prospects then receive the role-specific GHL application. GHL remains the candidate CRM and native workflow authority; Supabase is the structured HR operations/evidence database for job postings, publication history, WhatsApp conversations, screening evidence and funnel events; GitHub-backed Cloudflare Pages/Workers supply public pages and custom applicant UX; Cloudflare R2 holds approved applicant media; n8n handles conversational AI, screening, training, analysis and cross-system orchestration. The setter lane launches first, with the closer lifecycle mirrored by reference.

Operating center

Production Analytics is the management evidence layer

The production dashboard contains an extensive Call Center Analytics buildout covering setter activity, outcomes, Call Intelligence, Quality Grades, category-safe reporting, time evidence and related management views. Analytics supports evidence-based progression, coaching, remediation, category review and offboarding; authorized humans make personnel decisions.

Current release state: Production at the canonical URL below. Setter reporting is materially built; recruiting/onboarding views and the separate closer section advance as explicit workstreams.

Open production Magnetic Analytics →

Built / operationalBuilt / approval-gatedManualPlannedDecision required

Current Workforce and Target

3Current closers

2Current Supervisor setters

30Target qualified Supervisors

28Setter gap

Setter staffing objective

6.7% of target

2 current Supervisor setters → 30 active Supervisors meeting approved metrics

The target is not 30 accounts. It is 30 trained, certified, appropriately equipped, Analytics-visible Supervisor setters who meet the approved metrics.

Workforce	Current	Target	Planning note
Closers	3	Original target 6	Mirrored recruiting, onboarding and dedicated Analytics lane included by reference
Setter agents — Supervisor	2	30 metric-qualified	Primary staffing objective
Specialist / Manager setters	None stated in this revision	Not separately set	Explicit categories; criteria/compensation require decisions
QA / Support	0 original baseline	1 original baseline	Original role plan unchanged
Canvassers / Setters	0 original baseline	4 original baseline	Original role plan unchanged

Management and Change Control

1 • PlanHuman management defines policy, scope and acceptance.

2 • Build & testAI agents implement only approved, bounded work.

3 • EvidenceAnalytics and verification produce an auditable packet.

4 • DecideWalt or authorized management approves named actions.

Named-person onboarding and offboarding require Walt's explicit manual trigger.
Setter category changes require a documented human decision; categories are never inferred.
Payroll periods require reviewed calculations and human approval until separately approved payout automation exists.
No task becomes ready because a date arrives. Dependencies, tests, ownership, evidence and approval control readiness.

Zero-Budget Global Recruiting Strategy

Since there is no budget for recruitment ads, we will post to every appropriate free channel available worldwide. The primary call to action is “Message our Hiring Manager on WhatsApp”, carrying a posting-specific source code into the conversation. Pre-qualified prospects receive the role-specific GHL application; a direct GHL link remains an accessibility and outage fallback. All positions are remote, so we recruit globally — not just the US.

Approved setter opportunity • version 0.3

Remote, flexible, performance-rewarded — no closing required

Setters make cold outbound introductions using campaign-prequalified data that is not necessarily warm. They do not sell or close a solar transaction. They discover interest or need, then seek a qualified live transfer to a specialist; a firm appointment is the fallback.

Up to $10/hrBase pay

Up to $60Per qualified live transfer

20 hoursMinimum weekly payroll time

14 hrs/dayFlexible call window, 7 days

New Supervisor payroll hours normally start at $8/hour; Walt may manually approve up to $10/hour for demonstrated experience or talent.
Payroll time includes approved human-connected calling, waiting/ready, pause and disposition/wrap. Paid meetings and training are additional every week.
Additional opportunity includes kept-qualified-appointment incentives, individual close bonuses, a weekly performance bonus and an eligible closed-team bonus pool.
No degree, certification, prior solar experience or direct selling is required. Some GHL familiarity and experience with ViciDial, CallTools, ReadyMode, MightyCall or a similar predictive dialer is required; Magnetic Energy trains its specific ViciDial build.
Any Chrome-capable device may qualify if it has a usable keyboard, reliable headset/microphone, basic webcam and a stable VoIP connection. Phone/tablet setups receive a conditional functional test rather than an automatic rejection.

The full presentation is based on the six-tab management workbook surfaced in Production Analytics → Compensation. Examples are illustrations, not guarantees; verified earnings depend on approved time, qualification, outcome tiers, closes, performance and team-pool eligibility.

Free Job Posting Channels (Global)

Channel	Cost	URL / Method
Indeed	Free basic posting	indeed.com/hire (global — 60+ countries)
LinkedIn	Free basic posting	linkedin.com/hiring (global reach)
ZipRecruiter	Free basic posting	ziprecruiter.com/hire
Facebook Groups	Free	Digital nomad groups, remote work groups, solar industry groups, work-from-home communities — global reach
Craigslist	Free (some markets)	craigslist.org (select markets charge $10-25)
Nextdoor	Free local posting	nextdoor.com for local canvasser recruitment
Google for Jobs	Free (via schema markup)	GitHub-backed Cloudflare careers page with schema.org JobPosting markup
Solar Industry Job Boards	Free	SolarPowerWorld, SolarEnergyJobs (some free options)
Veterans Job Boards	Free	Hiring Our Heroes, RecruitMilitary (Veterans focus aligns with company values)
College Job Boards	Free	Local college career centers (canvasser/entry-level roles)
Roam Community	Free	Post in Roam groups (existing team referrals)
Worker Referral Program	$150 after a referred worker passes the two-week trial	Unique non-PII referral code; GHL application/onboarding capture; private referrer registry; Supabase attribution/reward ledger; payout by Zelle, Xoom or Remitly
Remote-Specific Job Boards	Free	WeWorkRemotely, Remote.co, RemoteOK, Working Nomads — ideal for call center agents and closers
Digital Nomad Communities	Free	Facebook digital nomad groups, NomadList forums — candidates with native English, self-motivated, timezone-flexible
Upwork / Fiverr	Free listing	Post contract-to-hire positions — screen for full-time conversion
Reddit	Free	r/forhire, r/remotejobs, r/solar, r/workonline — targeted subreddits for each role

Formal Application (After WhatsApp Pre-Screening)

Every recruitment post’s primary CTA opens the WhatsApp Hiring Manager with a posting-specific source code; qualified prospects receive a prefilled native GHL role form.
Maintain setter, closer, canvasser and QA role configurations while keeping GHL authoritative for candidate identity, pipeline stage, tasks, communications, calendar and human decision.
Use a direct GHL form link as the accessibility/outage fallback, not as the default funnel that bypasses WhatsApp.
Cloudflare Workers/Pages provide custom capabilities GHL cannot supply, including careers presentation, browser recording, technical checks and signed media uploads. All Pages/Workers source lives in GitHub.
Supabase stores the recruitment operating ledger: canonical postings, channel publications, variants, source codes, WhatsApp conversation/messages, screening evidence and funnel events. Candidate-linked rows bind to the immutable GHL contact ID; Supabase does not replace GHL CRM ownership.
Native GHL workflows handle acknowledgement, internal tasks, reminders, stage updates and interview links. Signed WhatsApp/GHL events invoke n8n for conversational AI, screening, training, analysis or cross-system work that truly needs it.

$150 Worker Referral Program

Approved referral contract

Refer a worker • earn $150 after the two-week trial is passed

Every approved referrer receives a unique random code. The candidate may enter it during application or onboarding. The attribution freezes when the authorized two-week trial begins; the reward becomes eligible only after the worker completes the trial and an authorized human records a pass.

$150One-time referral reward

2 weeksTrial must be passed

1 codeOne payable attribution per worker

3 railsZelle • Xoom • Remitly

Component	Operating contract
Referrer page / registry	Private registration and status experience; captures name, contact, country and preferred payout rail; issues a random non-PII code
Candidate capture	Application and onboarding accept the code; job-source code remains separate; a pre-trial Walt override is auditable
Eligibility	One reward per referred worker; no self-referral or duplicate claim; day 14 alone is not a pass
Supabase	Authoritative registry, code, attribution, trial, reward and payout-evidence records with RLS and idempotency
GHL + n8n	GHL stores summary/workflow state; n8n handles signed eligibility and payment-task events after an authorized trial-pass signal
Earnings boundary	Referral rewards are separate from the existing Vici-derived Earnings workflows and do not rebuild or alter that production stack

WhatsApp AI "Hiring Manager" — Pre-Screening Chat (New Layer Before Form)

💬 WHATSAPP AI HIRING MANAGER

Before a prospect ever reaches the GHL application form, they interact with our AI-powered WhatsApp Business chat. This chat is presented to prospects as our "Hiring Manager" — a real person who answers their questions, builds excitement about joining Magnetic Energy, and screens for obvious mismatches. Prospects do not know they are speaking with an AI. By the time they reach the formal application form, they are informed, pre-qualified, and genuinely motivated to complete it.

Why WhatsApp?

Global dominance: WhatsApp has 2+ billion users across 180+ countries. In our target recruiting markets — the Philippines, India, Latin America, Africa, Eastern Europe — WhatsApp IS the primary communication tool. Many candidates use it more than email or phone calls.
US adoption is growing: Even in the US, WhatsApp usage is climbing rapidly, especially among younger demographics and immigrant communities — exactly the talent pools we want to reach.
Lower friction than a web form: Job seekers are far more likely to send a WhatsApp message than navigate to a website and fill out a form. They already have the app. They're already comfortable chatting. No new account, no new website, no friction.
Instant, 24/7/365: The AI Hiring Manager responds instantly regardless of time zone. A prospect in Manila messaging at 3 AM their time gets the same quality engagement as one in Chicago at noon.
Conversational = higher conversion: People commit to things through conversation, not forms. The WhatsApp chat turns a cold job posting into a warm, personalized recruitment conversation.

How the Flow Works

1Job PostingProspect sees our listing on Indeed, LinkedIn, Facebook, etc. — includes our WhatsApp number: "Message our Hiring Manager to learn more"

→

2WhatsApp MessageProspect sends a message. AI Hiring Manager responds instantly, 24/7

→

3ConversationAI answers questions, asks qualifying questions, builds rapport and excitement

→

4Pre-QualifiedAI determines the prospect is a fit and is ready → shares the formal application form link

→

5Form CompletedOnly informed, excited, pre-screened prospects reach the form — dramatically higher completion rates

What the AI Hiring Manager Discusses (Friction Removal)

The AI is trained on everything a prospect might want to know before committing to apply. It proactively addresses and answers questions about every common point of friction:

Company OverviewWho Magnetic Energy is, what we do — solar, roofing, AC, energy services

Job DetailsDay-to-day responsibilities, what the work actually looks like in practice

Training ProgramHow training works, AI roleplay simulations, what's provided at no cost

Work SetupFlexible schedule, work-from-home, what equipment we provide vs. what they need

RequirementsEnglish fluency needs, tech requirements (laptop, internet, headset), how strict each is

CompensationPay scales, earning examples, payment methods available globally, weekly pay timeline

Career GrowthAdvancement opportunities, what success looks like, long-term potential

Objections & ConcernsAnything holding them back — the AI handles it with empathy and facts

Pre-Screening Criteria (Embedded in Conversation)

The AI doesn't just answer questions — it actively evaluates every prospect during the natural flow of conversation. By the time the chat concludes, we have structured data on:

English proficiency — AI evaluates written English fluency, grammar, and natural cadence throughout the conversation. This is our #1 hard requirement, and the WhatsApp chat gives us an early read before the formal audio/video recording.

Tech readiness — Can their actual Chrome-capable device, keyboard, headset/microphone, basic webcam and work connection pass the lightweight functional checks? Device price, brand, operating system and form factor are not gates.

Motivation level — Are they serious and engaged, or just browsing? The AI assesses enthusiasm, responsiveness, and depth of questions.

Role understanding — Do they actually understand what the job involves? The AI confirms expectations are aligned before sending them to the form.

Schedule feasibility — Can they commit at least 20 weekly payroll hours somewhere inside the proposed 9 AM–11 PM Eastern / 6 AM–8 PM Pacific call window, seven days a week?

Role fit — Which of our roles (call center, closer, canvasser, QA) best matches their skills and interests?

Example Conversation

💬 WhatsApp — Magnetic Energy Hiring

Prospect

Hi, I saw your job posting for call center agents on Indeed. Is this remote?

Hiring Manager

Hi! Yes — the setter opportunity is remote and globally available. You choose your schedule inside our 14-hour daily call window, seven days a week, and commit at least 20 payroll hours weekly. Where are you located?

Prospect

I'm in the Philippines. Is that okay? And what's the pay like?

Hiring Manager

Yes, we recruit globally. The opportunity offers up to $10/hour base pay and up to $60 per qualified live transfer, plus appointment, close, performance and eligible team-pool bonuses. New Supervisor hours normally start at $8 unless Walt approves a higher rate for experience or talent. Payroll time includes connected calls, waiting/ready, pause and disposition; paid meetings and training are additional. The application includes the complete earnings presentation and eligibility details.

Prospect

I've used a predictive dialer, but I've never sold solar. Is that a problem?

Hiring Manager

No. This is cold calling, but you are not expected to sell or close anything. You make the introduction, discover interest, and connect an interested homeowner to a specialist, with appointment booking as the fallback. We train our specific ViciDial workflow. You need native-level functional English, a Chrome-capable device with a keyboard, a reliable headset/microphone and webcam, a stable VoIP connection, and at least 20 available payroll hours. Would you like the short application?

Prospect

Yes please!

Hiring Manager

Awesome! Here's your application link: [link]. It takes about 10 minutes — you'll record a short audio clip reading a script and answer a few questions. I'll be here if you have any questions while you fill it out. Welcome to the team! 🎉

Design Principles

Warm and human: The AI is genuinely enthusiastic, professional, and caring. It never feels like a form or a bot — it feels like a conversation with a hiring manager who wants you on the team.
Adaptive: It reads what the prospect cares about most. If they're worried about pay, it dives deep on compensation. If they're nervous about training, it reassures them about the AI roleplay system. It follows the prospect's lead.
Creates urgency and excitement: "We're actively hiring right now," "You'd be a great fit for our team," "I'd love to get your application in front of the team today." It sells the opportunity.
Handles objections naturally: "I've never done sales" → "That's what our training is for." "I'm not sure about the pay" → breaks down the earning math with a concrete example. "I need to think about it" → "Totally understand — what questions can I answer to help?"
Always drives toward conversion: Every conversation has one goal — getting the prospect informed, excited, and through the application form link. The AI is a closer.
Maintains the illusion: At no point does the AI reveal it is automated. It presents as a human hiring manager with a name, personality, and genuine investment in the prospect's success.

Technical Implementation

Platform: Meta WhatsApp Business API connected to a recruiting assistant and GHL candidate record.
GHL-first orchestration: Native GHL workflows own acknowledgement, status, tasks, reminders and human follow-up.
n8n extension: Signed GHL/WhatsApp webhooks invoke n8n only for conversational AI, structured pre-screening, transcription, training or analysis.
Storage: GHL stores authoritative candidate identity, pipeline state, communication summary, tasks and human decision. Supabase stores the full WhatsApp conversation/message history, structured pre-screening evidence, posting/source lineage and screening runs. Cloudflare R2 stores approved audio/video under retention controls. Supabase rows bind to the immutable GHL contact ID once created.
Form handoff: A role-specific GHL form link is prefilled with available name, phone, source and role-interest values.
Human escalation: Any uncertain assessment, unanswered question or candidate request for a person creates a named GHL task for human handling.

WHY THIS IS A GAME-CHANGER: Every incomplete application is a lost hire. Traditional job posting → web form funnels have 70-80% abandonment rates. The WhatsApp AI Hiring Manager transforms this funnel — by the time a prospect reaches our application form, they have had a personalized conversation, all their questions answered, all their concerns addressed, and their excitement built. They are pre-qualified. They are motivated. Getting them to complete the form IS making a sale — and the WhatsApp chat is our best salesperson, working 24/7/365, scaling to thousands of simultaneous conversations at zero additional cost.

Without talented staff, we cannot succeed. This layer ensures we don't lose great candidates to friction, confusion, or unanswered questions — the three things that kill applications.

Architecture revision: The recruiting design is preserved in function but re-homed. The retired non-GHL recruiting stack is removed. GHL and GitHub-backed Cloudflare are the only recruiting/onboarding content platforms; n8n is an orchestration extension, not the primary form or candidate system.

Connected HR Operating Architecture

Candidate funnel • launch first

Tracked free recruiting posts

WhatsApp Hiring Manager

Questionnaire + systems check

Voice sample analysis

Live AI homeowner phone interview

Scorecard + human review

Role operating tracks

Setter: GHL + ViciDial + training

Closer: mirrored GHL onboarding

Role-specific certification

Production Analytics

Human lifecycle decisions

Data and automation

Supabase recruitment ledger

GHL native workflows

n8n conversation/screening analysis

GitHub-backed Cloudflare + R2

Auditable lifecycle controls

System	HR responsibility	State / rule
WhatsApp Business	Primary first-contact funnel, job questions, conversational qualification, objection handling and warm handoff to the formal application	First funnel layer
GHL	Authoritative candidate/contact CRM, forms, recruitment pipeline, communications summary, tasks, calendars, interviewer feedback, offer/onboarding status and native workflows; preferred host for a dedicated workflow-scoped Voice AI homeowner simulation after tenant verification	Primary workflow platform
Supabase PostgreSQL	Recruitment/referral operations and evidence: postings, publication ledger, WhatsApp messages, questionnaires, systems checks, voice samples, AI phone-interview sessions/transcripts/scorecards, referrers, codes, attributions, two-week trials, rewards, payout evidence and funnel events; candidate rows link to immutable GHL contact ID	Required HR database
Cloudflare Pages/Workers + GitHub	Version-controlled careers pages, custom applicant UX, technical checks, signed webhooks/uploads and role-specific portals	Native Git deployments only
Cloudflare R2	Approved applicant audio/video and other binary evidence under a defined retention/deletion policy	Media store
n8n	WhatsApp conversational AI, recruit screening, transcription, evidence-cited voice/AI-phone scoring, referral eligibility/payment-task orchestration, training analysis and cross-system orchestration from signed events	Extension, not system of record
ViciDial `/agc-next`	Setter user/phone/workspace, calls, recordings and authoritative call evidence after hire	Named onboarding built
Production Magnetic Analytics	Extensive setter/call-center analytics now; recruiting/onboarding views and a separate closer section by explicit build	Production
Roam / Tik Tik	Approved team communications, training and manual membership where applicable	Mixed / manual
Existing Earnings stack	Built GHL workflows, n8n workflows, Cloudflare Workers and Production Analytics remain authoritative for setter earnings calculation, approval, evidence and reporting	Built / integrate by reference

AI and Automation Strategy

AI Application Screening

WhatsApp is the primary first-contact and pre-screening layer. Supabase records the posting/source lineage, full conversation and structured evidence; GHL receives the qualified prospect/application and owns candidate CRM identity, role, stage, tasks, calendar and human decision.
A signed GHL webhook invokes n8n for transcription and role-specific scoring only when the required evidence is present.
AI writes a structured recommendation with rubric evidence; uncertain, incomplete or conflicting results route to human review.
No candidate is hired, rejected, promoted or offboarded solely by an AI score.
Native GHL workflows handle acknowledgement, tasks, reminders, interview links and approved stage changes.

Training and Certification

The `/agc-next` training package, 30-question certification quiz, instructor key, quick-reference guide, sandbox exercises and instructor materials are built.
Current written passing requirement and live demonstration remain part of certification.
AI roleplay and full training-record automation remain planned where not implemented.
Weekly Roam On-Air training adds continuous human-led reinforcement.

Analytics-Assisted Management

Production Magnetic Analytics contains the extensive Call Center Analytics buildout for setters, including activity, outcomes, Call Intelligence, Quality Grades, time evidence and category-safe views.
Specialist, Supervisor, Manager and Unclassified setter categories remain explicit; Administration & Management remains separate.
Recruit / onboard / trainee views will connect GHL pipeline, screening, certification and early performance evidence.
A separate closer Analytics section is a mirrored requirement with role-appropriate denominators and permissions; it is not reported as built until deployed and verified.

Detailed Workstream Planner

No timeline: workstreams advance by prerequisites and acceptance gates. The preserved recruiting block retains its original phase label, but no calendar duration is assigned.

Workstream A • Recruiting Pipeline

Active build specification

WhatsApp-first Setter Recruiting Pipeline

1.1 Posting Inventory and Distribution

Version approved setter/closer job content in GitHub and create one canonical posting record in Supabase.
Log every publication in job_posting_publications: channel, market, external URL/post ID, source code, variant, state, published/expiry dates, last verification and owner.
Every public post’s primary CTA opens the WhatsApp Hiring Manager with its source code. Direct GHL application is the accessibility/outage fallback.
Publish GitHub-backed Cloudflare careers pages with schema.org JobPosting markup and role-specific WhatsApp deep links.

1.2 WhatsApp Conversation and Pre-Screening

WhatsApp Business receives the prospect first and answers role/company/training/requirements/compensation questions from approved versioned knowledge.
n8n maintains conversation context, collects role, availability, equipment, English-writing evidence, motivation and questions, and writes messages plus structured evidence to Supabase.
Uncertainty, policy gaps, candidate request or sensitive question creates a named human task in GHL; it never invents an answer.
Qualified prospects receive a source-preserving, role-specific GHL form prefilled with known identity and interest. Unqualified/uncertain prospects remain human-reviewable; no AI-only permanent rejection.

1.3 Formal Application, Questionnaire, Systems Check and Voice Sample

GHL form creates/updates one Staff-type candidate and one role-scoped opportunity using an idempotency key, captures the short role questionnaire and required consent, and accepts a referral code separately from the job-source code. Onboarding accepts or corrects the code until it freezes at authorized trial start.
The systems check is functional rather than brand- or price-based: current Chrome on any capable device, a usable keyboard, reliable headset/microphone, basic webcam, email/payment readiness, 20-hour availability and a three-minute WebRTC test. Hard network floor: 5 Mbps down, 2 Mbps up, median RTT ≤180 ms, jitter ≤40 ms and packet loss ≤2%; preferred 10/5 Mbps, RTT ≤120 ms, jitter ≤30 ms and loss ≤1%. Phone/tablet is conditional on the complete real-workflow compatibility canary.
Cloudflare Pages/Workers provide browser recording and technical checks where GHL cannot; R2 holds approved media, while Supabase stores immutable evidence metadata.
The required setter voice sample is analyzed for job-relevant intelligibility, clarity, pace/cadence, tone/tonality, vocal strength/confidence and audio quality. Accent is evaluated only for demonstrated intelligibility impact in the target call environment—never as ethnicity, nationality or another protected proxy.
Use role templates: setter audio; closer video; canvasser video; QA multi-part audio.

1.4 Final Automated Gate — Live AI Homeowner Phone Interview

The candidate completes a short, engaged live call with an AI-simulated homeowner, pitches the approved service, follows the versioned setter script, responds to versioned objections and attempts the scenario’s defined positive next step.
Prefer a dedicated, non-primary, workflow-scoped GHL Voice AI agent after exact tenant capability, isolation and recording/export readback. It must be restricted to recruiting candidates, use no real homeowner data, create no real appointment, and never intercept unrelated conversations.
The AI homeowner follows the assigned scenario and does not coach, reveal the rubric or rescue the candidate during the graded call. The candidate receives recording/automated-analysis disclosure and consent before the call.
Persist the recording/transcript, scenario and rubric versions, outcome, exact evidence citations, confidence and 0–5 anchored ratings. Weighted dimensions are intro/hook 15, energy and enthusiasm 10, focus and directness 10, warmth and friendliness 10, persuasiveness 15, trust factor 10, objection handling 15, and resolution/closing 15. Compliance is not a recruiting-score dimension or veto.

Setter screening gate	Evidence	Progression rule
Short questionnaire	Role understanding, availability, experience, consent and objective requirements	Complete and internally consistent, or human clarification
Systems readiness	Hardware/software/OS/browser/headset/microphone/network/tool results	Approved minimums pass; remediable failures may retry
Voice sample	Recording, transcript and job-relevant communication dimensions	Evidence-cited analysis; no protected-trait inference or AI-only rejection
AI homeowner role-play	Versioned scenario, full call, transcript, objections, script behavior and defined outcome	Versioned scorecard reaches human review
Human decision	Complete packet plus reviewer reason	Interview, retry, hold or rejection

1.5 Analysis and Human Review

Signed WhatsApp/GHL/Voice AI events invoke n8n for transcription and versioned role-rubric analysis.
n8n writes questionnaire, systems, voice and role-play evidence; score, confidence and flags to Supabase; and summary fields/tasks to GHL.
Each screening type allows one initial attempt plus five remediation retries. Invalid uploads, platform failures and low-confidence analyses do not consume a retry. Passing every gate opens Walt’s interview booking; an unresolved fifth retry, uncertainty, conflict or rejection recommendation creates a Walt review task. No accent/voice trait, AI score or simulated outcome permanently rejects a candidate.

Primary flow: tracked job post → WhatsApp Hiring Manager → Supabase conversation/evidence → pre-qualified handoff → GHL form/questionnaire → systems check → voice sample → live GHL AI homeowner phone interview → n8n evidence-cited scorecard → human review → GHL calendar/interview.

1.6 Interview and Offer

Setter interviews route to Walt; closer interviews route to Michael unless management changes the assignment.
Use GHL calendars, native reminders and a GHL interviewer feedback form.
Track offer, acceptance, compliance readiness and human hire decision in GHL.
Provision no staff systems until Walt manually triggers the named onboarding procedure with role/category confirmed.

Launch gate: one approved internal identity must pass tracked post/deep link, WhatsApp conversation, Supabase writes, dedupe, GHL handoff, questionnaire, systems check, voice sample, isolated AI homeowner phone interview, evidence-cited scorecard, authorized human review, stage movement, calendar, recording/AI disclosure, opt-out/privacy and cleanup before public volume.

Workstream B • Hire Decision & Compliance

Planned

Define the candidate-to-staff transition and immutable decision audit.
Validate jurisdiction and worker classification before presenting forms.
Collect approved identity, agreement, tax/payment and emergency records securely.
Record human hire approval, initial category, compensation policy version and required systems.
Produce a named onboarding packet for Walt's explicit trigger; never provision from a webhook, roster change, scheduler or pipeline stage alone.

Acceptance gate: authorized candidate, required records complete, explicit category and compensation version, named approval.

Workstream C • Setter Technology Onboarding

Procedure built

Item	Current reality	Completion evidence
Identity + category	Explicitly validated; never inferred	Approved named record
GHL user	Approved setter permission template; assigned-data-only	User ID, permissions, login
ViciDial user + phone	Controlled named-agent creation	User, phone, level and sign-in
Analytics access	Separate own-agent-only credential	Own data works; cross-agent denied
Roam visitor badge	Badge plus selected approved groups	Badge and exact groups verified
WhatsApp group	Manual admin add	Admin confirmation
Tik Tik	Staff downloads; admin shares group	Install and group access
GHL / Cloudflare HR content	Candidate record and onboarding content are role-scoped	GHL stage, content access and repository deployment verified
GHL follower branch	Dedicated named-setter workflow branch	Routing verified
Welcome	Email + approved team announcement	Delivery evidence

Sequence: validate → snapshot/preflight → GHL → ViciDial/phone → production Analytics → Roam → WhatsApp → Tik Tik → role-scoped GHL/Cloudflare content → workflow → welcome → end-to-end verification.

Acceptance gate: least-privilege access works in every required system and each manual step has a named confirmation.

Workstream D • Initial Certification

Core package built

Assign current script, workflow and technical curriculum.
Complete guided instruction and sandbox exercises.
Pass the current written threshold and supervised live demonstration.
Record attempts, scores, instructor, remediation and recertification.
Hold production progression if evidence is incomplete.

Acceptance gate: written pass, live-demo pass, complete evidence and human authorization for the next stage.

Workstream E • Weekly Roam On-Air Setter Training

Recurring plan

Cadence: weekly and ongoing. Management chooses the standing day/time and authorized host. This page does not create the event series.

1 • ReadAnalytics trends and denominators

2 • ReviewAccess-appropriate call examples

3 • PracticeSkill focus + roleplay

4 • CommitKnowledge check + coaching actions

Standard agenda

Metrics briefing from Analytics.
Privacy-safe Call Intelligence and Quality Grades review.
One script, objection, transition, qualification, compliance or tool skill.
Instructor-led/peer roleplay; AI homeowner simulation when available.
ViciDial, GHL, Maps/solar tools, notes, dispositions or workflow clinic.
Short quiz, scenario or live demonstration.
Named coaching actions, remediation and next evidence review.

Evidence contract

Evidence	Source	Use
Event/host/start/end	Roam On-Air	Training record
RSVP + join duration	Roam attendance	Participation only—not competence
Module/version	Training record	Standard taught
Quiz/demo	Instructor/system	Certification/remediation
Coaching action	HR case	Owner and closure
Post-training window	Analytics	Observed change with denominator

Pilot gate: host/schedule, guest rule, privacy/recording policy, attendance sync, agenda, evidence schema, missed-session process and remediation process approved before one verified pilot; recurring series follows only after pilot acceptance.

Workstream F • Analytics-Governed Setter Lifecycle

Production setter analytics + planned HR views

Production source: https://magnetic-ads-dashboard.pages.dev/. Its extensive Call Center Analytics section is the setter evidence baseline. Recruiting/onboarding views are additive and do not weaken existing privacy, category or human-decision controls.

Magnetic Analytics evidence
identity • category • range • campaign scope • denominators • quality • outcomes • time • training • coaching

Progress / Upgrade
Human approves stage or category

Coach / Remediate
Manager defines action and review window

Offboard Review
Explicit named trigger required

Decision	Analytics role	Human control
Onboarding progression	Readiness and early evidence when pipeline view exists	Walt approves named person/stage
Specialist → Supervisor	Sustained approved metrics, quality, certification and reliability	Management approves category + compensation
Supervisor → Manager	Manager/QA capability evidence	Management approves role, level + compensation
Remediation	Evidence-backed gap and trend	Manager defines plan/window
Offboarding	Complete packet; never one metric	Explicit named trigger

Guardrails: zero-call active users remain visible; inactive users are excluded; categories are explicit; payroll time does not substitute for quality; detailed calls/coaching remain private; missing data and denominators remain visible.

HR-view gate: exact reviewed recruiting/onboarding candidate, GHL identity join, access/privacy verification, immutable preview, rollback and explicit approval. Existing production Call Center Analytics remains the current baseline.

Workstream F2 • Mirrored Closer Recruiting, Onboarding & Analytics

Required mirror • role-specific

Inclusion by reference: Every lifecycle control defined for setters—source attribution, dedupe, screening evidence, human decisions, onboarding proof, training records, access control, coaching, remediation and offboarding—also applies to closers. The implementation is mirrored in control, not copied blindly: closer tools, permissions, rubrics, compensation and denominators remain role-specific.

Lane	Closer implementation	Acceptance evidence
Recruiting	Closer-specific GHL form; 60–90 second video pitch/objection exercise through Cloudflare/R2 when required; Michael review route	Role/source/dedupe, media reference, rubric evidence and human decision
Onboarding	GHL closer user/permissions, assigned pipeline access, calendar + Google Meet readiness, approved communication groups and role content	Least-privilege login, test opportunity, meeting, follow-up and access-denial checks
Training	Closer script, discovery/presentation, objection handling, follow-up, pipeline hygiene, compliance and roleplay/call review	Module/version, attendance, quiz/demo, coach and closure
Analytics	Dedicated closer section separate from setter analytics: assigned opportunities, speed-to-contact, follow-up completion, meeting attendance, discovery/presentation progression, close outcomes, cycle time, quality/coaching and approved compensation evidence	Role-scoped denominators, source/date filters, drilldown privacy and reconciliation to GHL
Lifecycle	Human-approved progression, remediation, compensation review and named offboarding	Decision packet and post-change access verification

Current-state boundary: the production dashboard’s extensive Call Center Analytics section is built for setters. The dedicated closer Analytics section is a required mirrored workstream and must not be represented as live until its GHL contracts, role permissions, metrics, UI and reconciliation tests pass.

Mirror gate: reuse shared controls and components by reference, but require separate closer acceptance tests, role permissions, Analytics navigation and human sign-off.

Workstream G • Existing Earnings + Referral Rewards

Earnings built • referral extension approved

Setter categories

Category	Meaning	Compensation authority	Default level
Specialist	Entry / commission-only setter	Separate structure TBD	1
Supervisor	Standard setter	Current Supervisor policy/workbook	1
Manager	QA/override setter duties	Separate structure TBD	2
Unclassified	Awaiting explicit classification	No assumptions	Never inferred

Approved recruiting presentation

Up to $10/hour base pay + up to $60 per qualified live transfer

New Supervisor payroll hours normally start at $8. Walt may manually approve up to $10 for experience or talent. The complete opportunity includes kept-qualified-appointment incentives, individual close bonuses, a weekly performance bonus and an eligible closed-team bonus pool.

Open Production Analytics Compensation →

Production Earnings authority — already built

Existing GHL workflows, n8n workflows, Cloudflare Workers and Production Analytics already implement earnings approval, evidence, calculation and reporting. The GHL approval chain emits the approved signal; n8n normalizes identity and uses ViciDial call evidence as authority for setter APPT/LXFER events; Cloudflare/Analytics retain the ledger and management views. HR links to this stack and does not create a competing formula, approval path or earnings ledger.

Integration rule: preserve the existing Earnings contracts and exact idempotency/authority rules. Recruiting and onboarding may display approved earnings information and link the hired staff identity, but must not rewrite production Earnings logic.

$150 referral reward — separate extension

Capture and validate the referral code during application or onboarding; freeze the attribution at authorized trial start.
After two weeks, require an authorized human `trial_passed` decision; elapsed time alone does not create a reward.
n8n idempotently creates one $150 eligible reward/payment task per referred worker.
Pay the approved referrer through Zelle, Xoom or Remitly and record approval, payout reference and paid timestamp in the referral ledger.
Keep referral rewards separate from the Vici-derived setter Earnings event flow.

Acceptance gate: existing Earnings readback remains unchanged; referral code, attribution, trial-pass, reward and payment-state replays are idempotent; no canary transmits real money.

Workstream H • Staff Management & Offboarding

Procedure built / UI planned

Maintain staff status, category history, manager, training state, system identities and compensation policy version.
Add time-off and availability records.
Trigger offboarding only from Walt/Michael's explicit named instruction.
Snapshot access; deactivate rather than delete where history must remain.
Revoke/deactivate Analytics, ViciDial/phone, GHL, Roam, workflow, WhatsApp, Tik Tik, role-scoped Cloudflare access and other applicable access.
Preserve historical Analytics and payroll records; verify authentication denial afterward.

Acceptance gate: named approval, complete access inventory, final payroll state, deactivation evidence, retained history and post-change verification.

Data and Integration Planner

Database decision: Supabase is the required PostgreSQL HR operations/evidence database. GHL owns candidate CRM/workflow state; Supabase owns the recruitment/posting/evidence ledger. GitHub owns versioned public content/code; Cloudflare Pages/Workers deliver it; R2 owns approved binary media.

Supabase record	Purpose
`job_postings`	Canonical role posting, approved content/version, owner, markets, status and lifecycle dates
`job_posting_variants`	Channel/market copy variants and version-to-canonical relationship
`job_posting_publications`	Channel, external post ID/URL, source code, publication/expiry dates, state, last verification, owner and evidence
`recruitment_sources`	Stable posting-source taxonomy and WhatsApp deep-link attribution; kept separate from referral codes
`referrers` / `referral_codes`	Private referrer registry; contact/country/preferred payout rail; random non-PII code; status, issuance, expiry/revocation and audit history
`referral_attributions`	One candidate/worker to one payable referrer; capture source, validation, freeze-at-trial-start, duplicate/self-referral rejection and approved override evidence
`worker_trial_periods`	Authorized start, two-week eligibility date, status, evidence and human trial-pass/fail decision; elapsed time alone is not a pass
`referral_rewards` / `referral_payouts`	One idempotent $150 reward per eligible worker; approval, Zelle/Xoom/Remitly method snapshot, payment task, payout reference and paid timestamp
`candidate_links`	Minimal join projection: recruitment conversation UUID/phone to immutable GHL contact ID; not a duplicate CRM
`whatsapp_conversations` / `whatsapp_messages`	Full message history, consent/opt-out state, role/source lineage, timestamps and human escalation
`candidate_questionnaires` / `systems_check_runs` / `voice_sample_runs`	Versioned answers, objective minimum checks, retries, recording/transcript references and job-relevant voice evidence
`ai_roleplay_sessions` / `ai_roleplay_turns` / `ai_roleplay_scorecards`	GHL agent/workflow, scenario/rubric versions, complete conversation, objections, defined outcome, evidence-cited dimension scores, confidence and flags
`screening_runs` / `screening_evidence`	Cross-gate evidence packet, recommendation, confidence, human disposition/reason and immutable source references
`recruitment_funnel_events`	Post viewed/contacted, WhatsApp engaged, form offered/submitted, interview, hire, training, certification and active identity events
`onboarding_tasks` / `onboarding_forms`	Role-specific onboarding requirements, secure-record references, completion/verification evidence
`training_modules` / `training_completions`	Versioned training content, attempts, evidence, human review and certification state
`staff_system_access`	External IDs, roles/scopes, state and provision/verify/revoke evidence
`staff_category_history`	From/to category, evidence packet, approver and effective date
`training_events` / `training_attendance`	Roam event/module/version and RSVP/join/completion evidence
`hr_decision_packets`	Evidence range, metrics, recommendation and human decision/reason
`existing_earnings_links`	Immutable staff/contact linkage to the already-built GHL/n8n/Cloudflare/Analytics Earnings records; no duplicate HR payroll ledger

Boundary: no public browser writes directly to Supabase with privileged credentials. Cloudflare Workers or n8n perform signed, least-privilege writes; RLS, retention, deletion, audit fields and idempotency are required. Reuse an existing company-owned Supabase project only after ownership, access and retention readback; otherwise create a dedicated HR project.

Workstream Readiness Gates — No Timeline

G0Plan approved

G1Contracts + owners

G2Security + privacy

G3Build + tests

G4Pilot / UAT

G5Named production approval

G6–7Operate, monitor, learn

A workstream may progress when its prerequisites are met. Elapsed time never waives a gate.

Success Measures

30Qualified Supervisor setters

100%Named onboarding evidence

WeeklyRoam training rhythm

0Unapproved automatic payouts

Staffing reporting distinguishes applicants, screened candidates, hired, provisioned, certified, active and metric-qualified Supervisors.
Manual WhatsApp and Tik Tik steps remain visible until truly automated; GHL/Cloudflare steps require deployment/readback evidence.
Initial certification and weekly training evidence are visible by staff member.
Personnel recommendations include denominator, evidence period, quality, outcomes, training and human rationale.
Every proposed payout reproduces from a versioned rule and immutable evidence.

Management Decision Register

Decision	State
Setter objective	Confirmed: 30 metric-qualified Supervisors
Current setters	Confirmed: 2 Supervisors
Current closers	Confirmed: 3
Specialist / Manager compensation	Decision required
Supervisor qualification thresholds/evidence window	Decision required
Roam On-Air host/day/time and recording/attendance policy	Decision required before event creation
Existing Earnings implementation	Built: GHL workflows + n8n workflows + Cloudflare Workers + Production Analytics; HR integrates by reference and does not rebuild
Setter recruiting definition	Approved: connected calling + waiting/ready + pause + disposition/wrap; meetings/training additional
Worker referral program	Approved: $150 after referred worker completes and human-passes the two-week trial; onboarding accepts code; Supabase registry; Zelle/Xoom/Remitly
GHL WhatsApp	Approved: $10/month with dedicated recruiting path/number; activation/readback pending
Dedicated HR Supabase + Voice AI/number	Approved: isolated build; canary pending real contact
Worker jurisdictions/classification	Legal/management decision required

TODAY — Prospective Setter Launch Action Plan

Day 0 objective

Open one verified WhatsApp-first setter funnel with the complete six-gate screening path today

Today is complete only when one tracked test prospect reaches WhatsApp, GHL questionnaire, minimum systems check, required voice sample, isolated live AI homeowner phone interview, evidence-cited scorecard and authorized human review without touching unrelated contacts or real homeowner/appointment data.

Order	Do today	Owner / system	Done when
1	Completed in source: freeze setter opportunity version 0.3, existing-Earnings integration boundary, compensation headlines, 20-hour minimum, systems thresholds, voice prompt, eight-dimension AI phone-interview scorecard, one-initial-plus-five-retries policy, $150 referral contract, disclosure/consent and Walt routing.	Walt • approved contract	The versioned source package and live plan agree
2	Preserve and link the existing Earnings stack—GHL workflows, n8n workflows, Cloudflare Workers and Production Analytics—without rebuilding it. Complete the already-approved GHL/WhatsApp/Supabase/Voice AI asset readback and safe test scope.	System audit	Earnings boundary and recruiting inventory are saved
3	Create the dedicated HR Supabase recruitment/referral ledger: questionnaires, systems checks, voice samples, AI phone-interview sessions/turns/scorecards, screening evidence, referrers, referral codes, attributions, worker trials, rewards, payouts and funnel events. Apply RLS, least privilege, retention, audit fields and idempotency.	Supabase	Schema/access tests pass; no public privileged key exists
4	Configure the WhatsApp Hiring Manager as the primary funnel. Every post/deep link carries a source code; the assistant uses approved knowledge, records conversation/evidence, escalates uncertainty and hands qualified prospects to GHL.	WhatsApp + n8n	Test conversation is attributable, persisted and human-escalatable
5	Establish the GHL Staff-candidate contract and build the role form/workflow with questionnaire, referral code, consent, evidence links, screening state, tasks, reminders and Walt routing. Application and onboarding both accept the code; freeze it at trial start.	GHL	One submission creates one candidate, one attribution and one workflow run
6	Implement the functional systems check: Chrome-capable device, keyboard, headset/mic, webcam, 5/2 Mbps minimum, RTT ≤180 ms, jitter ≤40 ms, packet loss ≤2%, three-minute WebRTC stability, required accounts and 20-hour availability. Permit conditional phone/tablet pass only after the full compatibility canary; return exact remediation and up to five retries.	Cloudflare Worker/Page + GHL	Pass, controlled-fail, phone/tablet and retry-exhaustion tests produce correct evidence
7	Implement the approved 60–90 second voice prompt and rubric. Recommend pass at 75/100 with English intelligibility/functional fluency ≥24/30, clarity ≥14/20, audio quality ≥3/5 and confidence ≥0.75. Spanish is a separate strength; accent is considered only through demonstrated intelligibility impact.	Cloudflare/R2 + n8n	Recording, transcript, evidence, score thresholds and attempt state persist
8	Build the dedicated non-primary GHL Voice AI homeowner phone interview. Use 0–5 anchored evidence ratings for intro/hook 15, energy/enthusiasm 10, focus/directness 10, warmth/friendliness 10, persuasiveness 15, trust 10, objections 15 and resolution/closing 15. Compliance is not a score dimension or veto.	GHL Voice AI	Only the approved test candidate can enter; score totals 100; unrelated contacts and real customer/calendar data are unreachable
9	Publish inactive/idempotent n8n drafts for screening analysis, referral attribution, authorized two-week trial-pass eligibility and $150 payment tasks. Persist transcript evidence and GHL summaries; keep referral rewards separate from the existing Earnings workflow.	n8n	Replays create no duplicate score, attribution, reward or payment task
10	Create the GitHub-backed Cloudflare `/careers/setter`, screening and private referrer registration/status UX with approved opportunity copy, tracked WhatsApp CTA, GHL fallback, referral-code capture, privacy and recording/analysis disclosure.	GitHub + Cloudflare Pages/Workers	Production UX loads, claims match version 0.3 and both source/referral attribution survive every handoff
11	Run screening and referral canaries after a real internal contact is supplied: tracked source → WhatsApp → Supabase → GHL/referral capture → systems → voice → AI phone interview → scorecard → Walt calendar; plus referrer registration → code → onboarding freeze → simulated authorized trial pass → one $150 eligible payment task. No real money is sent.	End-to-end	Isolation, dedupe, attribution, retries, permissions, audit, idempotency and cleanup all pass
12	Publish one approved setter post plus channel variants only after the canary passes. Make WhatsApp the primary CTA and log every external URL/post ID, source code, state and evidence.	Recruiting + Supabase	Live post URLs and source codes reconcile to the database
13	Monitor WhatsApp and every screening gate continuously. Give every candidate an owner, complete evidence state and next action; pause added volume if any gate drops, duplicates or misroutes candidates.	WhatsApp + Walt + GHL	No orphaned conversation or screening session exists
14	Close today with exact counts for conversations, applications, systems passes/retries, voice samples, AI phone interviews, Walt decisions/interviews, referral codes/attributions, worker-trial states and referral rewards. Reconcile without double-counting.	Management review	Day-0 report, blockers and named next-action queue exist

Minimum viable result today: one approved role/knowledge packet; one secured Supabase recruitment ledger; one WhatsApp-first test conversation; one tested GHL handoff/form/workflow; one GitHub-backed Cloudflare page or tracked WhatsApp deep-link fail-safe; one idempotent n8n path or documented human fallback; one clean end-to-end canary; tracked public postings; and every response owned.

Do not bypass the first funnel: WhatsApp is the default path from job post to pre-screening. Direct GHL remains an accessibility/outage fallback. Supabase is the operational/evidence database; GHL remains authoritative for candidate CRM/workflow state.

Setter Screening Contract — Approved Defaults

Screening is designed to maximize qualified applications while resolving remediable technical or presentation issues before Walt needs to intervene. Passing all required gates advances directly to Walt’s live interview booking. Automated evidence never makes a permanent rejection.

Attempt contract: one initial attempt plus up to five remediation retries for each screening type. Return the exact failed measurement and corrective action. Platform outages, corrupt/missing media and low-confidence analysis do not consume a retry. An unresolved fifth retry creates a Walt review task with every attempt and evidence reference.

Objective systems readiness

Dimension	Hard minimum	Preferred / handling
Device + Chrome	Any form factor capable of a current stable Chrome browser and the real candidate/calling workflow	No brand, OS, age or price gate
Keyboard	Built-in, USB or reliable Bluetooth keyboard for sustained notes/data entry	Touchscreen-only does not pass
Headset/microphone	Intelligible audio without persistent clipping, echo, dropouts or speaker feedback	Wired preferred; stable Bluetooth allowed
Webcam	Functional basic video for Roam training	480p functional minimum; 720p preferred
Network	5 Mbps down / 2 Mbps up; median RTT ≤180 ms; jitter ≤40 ms; packet loss ≤2%	Preferred 10/5 Mbps, RTT ≤120 ms, jitter ≤30 ms, loss ≤1%
Stability	Three-minute WebRTC two-way and simulated-three-way audio test without repeated disconnects	Run on the actual work device/network
Schedule	At least 20 payroll hours inside the 14-hour daily call window	Proposed 9 AM–11 PM Eastern / 6 AM–8 PM Pacific, 7 days; live schedule readback required
Accounts	Working email and ability to receive payment through Zelle, Xoom or Remitly	Collect sensitive payout details only after the approved stage

Phone/tablet rule: not automatically rejected. Conditional pass requires a usable keyboard and successful Chrome, form/note-entry, calling-workspace, webcam/Roam and three-way-audio canary.

Required English voice sample

Record this 60–90 second passage on the intended work setup. Speak naturally; do not imitate an accent or dramatic sales voice.

“Hi, this is [first name] with Magnetic Energy. I’m reaching out because we’re speaking with homeowners in your area about ways they may be able to reduce energy costs and improve their homes. I’m not asking you to make a purchase today. My job is to make a brief introduction, ask a few questions, and, if it makes sense, connect you with an energy specialist who can explain the available options.

Are you the homeowner? About how much is your average electric bill? Have you considered solar, roofing, air conditioning, or another home-energy improvement?

I understand that you did not request this call, and I’ll keep it brief. Based on what you’ve shared, I’d like to connect you with a specialist now. If now is not convenient, we can schedule a better time. Which option works best for you?”

Optional Spanish bonus: speak for 20–30 seconds in your own words, introducing yourself and explaining that your role is to ask a few basic questions and connect interested homeowners with an energy specialist.

Voice-sample rubric

Dimension	Weight	Evidence
English intelligibility and native-level functional fluency	30	Consistently understandable; natural grammar/phrasing supports homeowner conversation. Record accent-related intelligibility impact only—never infer nationality, ethnicity or language background.
Clarity and articulation	20	Clean word formation and complete phrases without persistent mumbling
Tone and professional presence	20	Warm, credible, composed and appropriate for cold outbound introduction
Energy and engagement	15	Alert and interested without shouting, forced enthusiasm or flat delivery
Pace, cadence and confidence	10	Controlled pace, useful pauses, steady volume and limited avoidable hesitation
Audio quality	5	No persistent clipping, echo, dropouts, feedback or disruptive background interference

Voice pass recommendation: ≥75/100 overall; English intelligibility/functional fluency ≥24/30; clarity ≥14/20; audio quality ≥3/5; analysis confidence ≥0.75. Spanish is recorded as a separate strength and may add up to five bonus points only after the English hard gate passes.

Final live AI homeowner phone interview

A dedicated, non-primary recruiting Voice AI agent presents a cold homeowner scenario and versioned objections. It does not coach, reveal the rubric, reach unrelated contacts, use real homeowner data or create a real appointment. The candidate opens the call, earns attention, addresses the objection and seeks a clear live transfer or firm specialist appointment.

Each dimension receives a transcript-cited 0–5 rating: 0 absent/counterproductive; 1 weak; 2 inconsistent; 3 competent; 4 strong; 5 exceptional. Weighted points equal rating ÷ 5 × weight.

Dimension	Weight	Evidence focus
Intro / hook	15	Prompt, relevant opener that earns attention
Energy and enthusiasm	10	Engaged, alert, positive delivery
Focus and directness	10	Purposeful, concise and easy to follow
Warmth and friendliness	10	Empathy, listening and approachable tone
Persuasiveness	15	Connects need to a compelling next step
Trust factor	10	Credible, confident, transparent and dependable
Objection handling	15	Acknowledges, answers, checks resolution and preserves momentum
Resolution and closing	15	Clear live-transfer or appointment ask and decisive resolution

AI phone-interview pass recommendation: ≥75/100 overall; intro/hook, persuasiveness, objection handling and resolution/closing each ≥3/5; no dimension below 2/5; analysis confidence ≥0.75. Compliance is not a recruiting-score dimension or veto; separate safeguards remain outside the scorecard.

GHL progression

New Setter Prospect → WhatsApp Pre-Screening → Application Submitted → Systems Attempt N → Voice Attempt N → AI Homeowner Attempt N → Screening Passed / Book Walt Interview. Any rejection recommendation, uncertainty, conflict, low confidence or unresolved fifth retry routes to Needs Walt Review.

Closer mirror: apply the same source attribution, retry, evidence, privacy and Walt/authorized-human decision controls to the closer track, with its own role-specific GHL form, presentation exercise, rubric, onboarding and dedicated Analytics section.

Living operating plan: this page now defines the active setter launch sequence and the mirrored closer track. Updating this source does not itself send recruiting outreach, modify GHL/n8n, onboard or offboard a named person, process payroll or automate payment.