From manual agency to AI-native centaur, in four phases. Every phase is a self-contained, interactive deployment plan — check off tasks, watch the gates fill, and run the calculators. Pick your phase from the tabs below; your progress saves automatically in this browser.
What this is. The complete 1st Batch transformation, organized into four deployment phases that map to the four architecture layers. Each phase ships the part of the system that earns its keep before the next phase builds on top of it — revenue-touching delivery first, then automation, then strategy, then scale.
How to use it. Click a phase tab to open its full playbook. Tick a task and it saves on this device; the tab badge and the gate meters fill as you go. Each phase has its own calculator and a source cross-reference back to the underlying 1st Batch documents. Nothing is sent anywhere — progress lives only in your browser.
The phases deploy the architecture in the order that pays: Layers 3+4 (what serves clients) before Layer 2 (what automates it) before Layer 1 (the story) before scale. Strategy decks don't pay salaries — executed delivery does.
The whole point of the centaur model: as the system matures, Jake does less execution. ~20h → ~22h → ~11h across the 90-day transformation, then ~15h to run the next-90 scale cycle — while throughput climbs.
Each phase ends only when its gate criteria are met — a live client, a validated agent, a proven metric. The gate meters in each tab fill as you check off the tasks underneath them.
Phases 1–3 are tightly grounded in the 1st Batch source docs. Phase 4 is a forward projection beyond the documented 90-day plan — clearly flagged as such inside that tab.
| Role | Lives mostly in | What they own |
|---|---|---|
| Jake (Founder) | P1P2P3P4 | Approvals, gates, positioning, Go/No-Go. Responsible for little, accountable for all. |
| Brooklyn (CRM) | P1 | SNMS build, Conversation AI + NEPQ, the 14 workflows, vertical snapshots. |
| Trung Le (IT/Dev) | P1P2P4 | Website / Astro builds, IT infrastructure (DNS, webhooks, hosting), deployment + UAT, GHL snapshots. |
| Hung (AI Automation) | P2P3P4 | Agent fleet, orchestration harness, n8n automation, Command Center, agent prompts & wiring. |
| Nhu + Content | P1P3 | QueryMind pipeline, city pages, case-study flywheel, positioning copy. |
| Phanh (SEO) | P2 | SEO Sentinel system prompt + rubric, audit validation, organic SEO strategy. |
| Sang + Tung (Ads) | P1P2 | Meta + Google templates, Ad Arbitrage agent, paid lead channel. |
| Ngọc (HR) | P3 | Role cards, AI-native hiring rubric, OKR performance system. |
| Sales Manager | P3P4 | Core Four outbound, prospect list, conversions, expansion. |
| PM | P2P3P4 | Agent Registry, reporting, beta data, Go/No-Go prep, roadmap. |
How to roll this out so 11 people understand the architecture without drowning in 62 documents on Day 1. Each person reads only the 2–3 docs tied to their role.
Open the 1st Batch Master Index with department leads (Brooklyn, Nhu, Sang, Tung). Walk the 4-layer map. Frame it: “We start at Layers 3 and 4 — what serves clients and runs ops. Layers 1 and 2 come in Phase 2.”
Brooklyn: SNMS Ultimate CRM + Launchpad gaps. Nhu: QueryMind + content templates. Sang: Meta skills + Lead Gen Engine. Tung: Google Ads Knowledge Pack. Each lead reads only their docs.
Open SNMS Build Tutorial TeamPlay v4 — the 688-task board across 7 departments. Each person sees their task count, hard gates, and the 10-week timeline. Assign ClickUp tasks. Focus: “Here's what you own.”
Each Monday, review TeamPlay progress by department against the 4 hard gates (Week 1 docs, Week 2 content brief, Week 7 email, Week 7 Urable webhook). Track % complete against the timeline.
Reading 2–3 role-relevant docs instead of all 62 shrinks the Value Equation denominator to near-zero. Lower perceived effort → faster adoption. The rollout itself is designed as an offer the team will actually “buy.”
Get the CRM client-ready and the Skills Libraries into the team's hands. These two systems directly generate and retain revenue — nothing else ships until they work.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Configure Conversation AI Primary Bot — Auto-Pilot, 1s wait time, Knowledge Base seeded (web crawler + FAQ + service pricing) | Brooklyn | 3h | SNMS Ultimate CRM → AI Config / P1 | |
| Build NEPQ Flow Builder qualification — 4 Capture nodes: Situation → Problem → Implication → Need Payoff | Brooklyn | 4h | SNMS Ultimate CRM → Pillar 2 | |
| Activate WF-01 (Speed-to-Lead), WF-02 (Appointment Confirmed), WF-03 (No-Show Recovery) — test all triggers | Brooklyn | 3h | SNMS Ultimate CRM → Workflows | |
| Approve the 21-capability tech stack (18 native GHL + 3 third-party: Instantly.ai, Postmaster, Urable bridge) | Jake | 1.5h | SNMS Ultimate CRM → Tech Stack | |
| Rank the 21 net-new Launchpad tutorials by revenue impact (AI Employee differentiators first) | Jake | 1.5h | Customer Launchpad → Gap Analysis | |
| Record first 3 AI-Employee differentiator videos: Voice AI, Conversation AI Auto-Pilot, Reviews AI | Nhu + Minh Chau | 4h | Customer Launchpad → Coverage Matrix |
The CRM is the delivery vehicle. Until it works for one client, nothing else matters. On a $1,200 ceramic ticket at ~$200 CAC, payback is well under one month — LTV:CAC clears the 3:1 bar on the first job.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Deploy Google Ads Knowledge Pack — Tung completes the agency-customization column for 1 client (200+ keywords available) | Tung | 3h | GA Knowledge Pack | |
| Deploy Meta skills — Sang completes agency column for Lead Gen Engine + Campaign Accelerator (8-agent pipeline) | Sang | 3h | Meta skills suite | |
| Nhu maps the QueryMind flow (topical map → brief → CQS audit → article) for 1 client | Nhu | 2h | QueryMind → 4 pipelines | |
| Design delivers Brand Board (D.7) Week 1 — upstream of all 17 Canva snapshot templates | Nam + Le | 6h | TeamPlay v4 → Dept 05 | |
| Jake reviews all completed agency columns, flags variances against skill defaults | Jake | 1.5h | All Skills Library files |
Skills Libraries are the playbooks that let the team deliver without Jake. The 4-column cascade transfers knowledge from skill defaults through to client-specific execution — the system that converts the founder from operator to reviewer.
Turn the working CRM + Skills Libraries into a repeatable onboarding system across all 5 verticals: ceramic coating, PPF, window tint, interior detailing, and fleet.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Build 5 vertical-specific SNMS snapshots (ceramic, PPF, tint, interior, fleet) with pre-loaded workflows + pricing | Brooklyn | 6h | SNMS Ultimate CRM → Data Model | |
| Configure the 4-Campaign Revenue Engine per vertical (C-1 ASC+, C-2 Manual ABO, C-3 Creative Lab, C-4 Retarget) | Sang | 5h | Meta Campaign + Lead Gen | |
| Build Google Ads templates: keyword clusters + negative lists per vertical | Tung | 4h | GA Keyword Architect | |
| Create a content-brief template per vertical via QueryMind topical map → CQS pipeline | Nhu | 3h | QueryMind pipeline | |
| IT: Urable → GHL inbound-webhook bridge built and tested on 1 live client | Trung Le | 4h | TeamPlay v4 → Dept 04 |
Five reusable vertical snapshots mean every new client starts from a proven template, not a blank page. Less effort per onboard, less variance in delivery, faster speed-to-value — the numerator of the Value Equation rises while the denominator falls.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Configure the Pattern C template with entity-authority schema (JSON-LD, sameAs, potentialAction) | Jake | 3h | Pattern C templates | |
| Produce the first 5 city pages using the Pattern C template + QueryMind brief | Nhu + Tran | 5h | City-page templates | |
| Koray City Page Auditor QA pass — 6 CQS-aligned dimensions scored on all 5 pages | Jake | 1h | Koray Auditor + Consensus Audit skills | |
| Design builds city-page visual assets (Nam: hero images; Le: map / location graphics) | Nam + Le | 4h | TeamPlay v4 → Dept 05 |
Pattern C city pages are the SEO deliverable franchises buy. Seeing 5 live, schema-rich, CQS-scored pages inside their first two weeks spikes the Dream Outcome × Perceived Likelihood side of the equation — the strongest retention signal there is.
Build the monthly reporting rhythm and prove the whole stack works end-to-end. This is the “Track Attendance” horseman of Hormozi's Five Horsemen of Retention.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Configure Monthly Report Index — the WF4 hub with the Managed-Agent MVP task pipeline | Jake | 3h | Monthly Report Index | |
| Build the client-facing Monthly Report template with per-pillar KPI dashboards + MoM deltas | Jake | 2h | Monthly Report — Jake | |
| Sang + Tung populate the first live report with Meta + Google Ads performance data (1 client) | Sang + Tung | 3h | Meta Perf Hub + GA Auditor skills | |
| Nhu populates the SEO section — rankings, traffic, content velocity, QueryMind throughput | Nhu | 2h | QueryMind QA | |
| Brooklyn populates the CRM section — lead flow, conversion rates, workflow trigger counts, AI response metrics | Brooklyn | 2h | SNMS Ultimate CRM → Go Live |
The monthly report is the single most powerful retention tool. Clients who see measured progress stay; clients who don't, churn. At ~$1.75/run via SEO Sentinel vs. ~3h of manual work, the report pays for itself on the first client and removes the most common reason agencies lose accounts.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Select 1 existing client as the “proof case” — run full Centaur delivery across all 7 pillars | Jake | 2h | AI driven agency → 7 Pillars | |
| Measure: time-to-first-deliverable, team hours vs. old process, client-satisfaction signal | Jake | 2h | 90-D Transfo → criteria | |
| All department leads document blockers, process gaps, and “what I wish I had” for Phase 2 input | All leads | 1h ea | TeamPlay v4 → all depts | |
| Jake compiles the Phase 1 retrospective — what worked, what broke, what to systematize in Phase 2 | Jake | 2h | Master Index → L3+L4 |
Phase 1 doesn't just deploy systems — it activates two stacked money models. Layer the four offer types so LTV climbs and CAC is recovered fast. Toggle between the detailing-client engine (what SNMS sells for the shop) and the agency's own offer (what SEO Navigator sells to the shop).
Conversation AI books it in 30 sec. Penny-gap volume play — gets the vehicle (and owner) in the bay.
The thing they buy. NEPQ flow qualifies; close-rate target 35%+.
Classic “can't have coating without paint protection” pairing. Lifts average ticket sharply.
GHL Payments split. Captures the no-yet buyer instead of losing them.
3-year post-purchase nurture, tiered VIP, referral trigger links. Repeat-rate target 60%+.
The SNMS 6-Pillar engine raises customer lifetime value from the industry's ~$150 to $850+ by chaining attraction → core → upsell → continuity. Phase 1 ships the CRM workflows (WF-01…WF-14) that make every stage automatic.
Lead magnet. Consumable in <15 min, shows the gap, opens the conversation.
Half of Detailers Roadmap's $5,500–$9,250 — same quality, owned by the client.
The full 7-pillar ecosystem. Where the real LTV lives.
One pillar (e.g. Google Ads only) for budget-constrained shops; expand later.
The Phase 2 productized layer. Agent swarm runs delivery; margin triples.
The Hybrid OS is the second premium product to the same client base — Stage 5 of the Scaling Roadmap. It's gated to Phase 2 on purpose: don't sell the autonomous layer until the agent fleet is running. Phase 1 proves the manual version first.
Live LTV, payback, and LTV:CAC for either money model. Defaults are grounded in the source docs — ceramic AOV, 55% service margin, agency Hybrid OS retainer. Drag the sliders to pressure-test the numbers before you commit budget.
Below 3:1, you're buying revenue at a loss once overhead is counted. The agency model runs subscription LTV = (monthly profit ÷ churn); the client model runs transactional LTV = AOV × margin × lifetime purchases. Both are wired into the toggle above.
Who is Responsible, Accountable, Consulted, and Informed across the six Phase 1 workstreams. Jake is Accountable everywhere (the founder owns the outcome) but Responsible almost nowhere — the point of Phase 1 is to make that true.
| Workstream | Jake | Brooklyn | Nhu / Content | Sang | Tung | Design | Trung Le (IT) |
|---|---|---|---|---|---|---|---|
| CRM build & AI config | A | R | I | I | I | C | C |
| Skills Library cascade | A | C | R | R | R | I | I |
| Vertical onboarding snapshots | A | R | C | R | R | C | C |
| Pattern C city pages | A | I | R | I | I | R | I |
| Monthly reporting pipeline | R | C | C | C | C | I | C |
| Urable ↔ GHL integration | A | C | I | I | I | I | R |
The honest risks tracked in the strategic vision, plus the execution risks specific to a 21-day deployment. Each carries a likelihood, an impact, and a mitigation already wired into the plan.
If Jake stays Responsible (not just Accountable), the whole Stabilize thesis collapses and throughput caps at his calendar.
Mitigation: Gate 2 explicitly requires a team-only onboarding with zero Jake involvement. The RACI matrix keeps Jake out of the Responsible column on 5 of 6 workstreams.
Conversation AI or the NEPQ flow looks configured but fails on a real lead — the delivery vehicle stalls and every downstream sprint inherits the debt.
Mitigation: Gate 1 demands a live client with 3 tested workflows, not a demo. The 42 TeamPlay test cases run before go-live.
Trung's DNS/deliverability work (Dept 04) blocks Sang's email, which blocks Nhu's newsletters, which block Brooklyn's CRM campaigns. One slip cascades.
Mitigation: The dependency map below front-loads DNS and the Brand Board to Week 1. Both are critical-path and tracked as hard gates.
Heavy reliance on Managed Agents + Claude Skills. A pricing or feature change would expose the model. (Tracked in the strategic vision.)
Mitigation: Skill definitions are portable to other frontier models; all client data lives in GHL / WordPress / ClickUp, not Anthropic infrastructure. Phase 1 stays manual — agent dependency is a Phase 2 concern.
62 documents and a 688-task board can paralyze an 11-person team if dropped all at once.
Mitigation: The Team Introduction Sequence gives each person only their 2–3 docs. Weekly 15-min standups track against gates, not the full backlog.
The one chain that determines whether Phase 1 ships on time. It runs straight through the TeamPlay v4 board's hard gates — technical plumbing unblocks email, which unblocks content, which feeds the CRM.
DKIM / SPF / DMARC + Urable webhook
Warm-up, inbox placement
50 newsletters, 375 SMS
WF-01…WF-14 enrolled
Every sprint traces back to specific 1st Batch documents. Links resolve to the real files in this folder.
| Sprint | Primary source documents | Layer |
|---|---|---|
| S-1A | SNMS Ultimate CRM, Customer Launchpad | L3 · Service Delivery |
| S-1B | Google Ads Skills, Meta Skills, QueryMind, TeamPlay v4 | L3 L4 |
| S-2A | SNMS (Data Model), Meta Campaign Accelerator, Google Ads Keyword Architect, TeamPlay (Dept 04) | L3 L4 |
| S-2B | Pattern C templates, Schema Generator, TeamPlay (Dept 05) | L3 |
| S-3A | Monthly Report Index, Monthly Report — Jake, Performance Hub + Auditor skills | L4 · Operations |
| S-3B | AI driven agency (7 Pillars), 90-D Transfo, Master Index | L3 L4 |
After Gate 3 passes, Phase 2 deploys Layer 2 (Technical Architecture): the 6-agent Managed-Agent fleet, the n8n automation playbook, and the productized Hybrid OS retainer.
Four things must be true before a single agent runs. Confirm these in the Day-0 kickoff so Week 1 isn't spent chasing access.
Anthropic Managed Agents beta access confirmed, beta header set, and the $0.08/session-hour pricing model understood. Sprint 1 test budget ~$50–100 approved.
SEO Utils MCP reachable; external API keys ready (Apify, Firecrawl, Google Maps, OpenAI, Gemini, Perplexity); ClickUp status trigger + Slack slash-command path scoped.
Hung owns AI automation (harness, agents, n8n). Trung (IT) owns infrastructure + website/Astro. Phanh owns Sentinel's system prompt + rubric. Jake approves spend + the architecture map. PM owns the ClickUp Agent Registry.
Phase 1 must be green: CRM live, repeatable onboarding, monthly reporting working. Layer 2 automates these proven manual processes — don't automate what isn't yet proven.
Building the agent fleet before the manual model is proven is the classic premature-optimization trap. Phase 1 earned the right to automate; Phase 2 cashes it in. Readiness checks keep the order honest.
Build the reusable orchestration harness once, then deploy SEO Sentinel v1 as the proof agent. This is the hard week — the abstraction built here is what makes agents 2–6 trivial.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Build the dispatcher + config-file pattern (./agents/<name>.json: agent_id, kickoff prompt, ClickUp fields, delivery channels) | Hung | 6h | Reuse PRD — Orchestration | |
| Implement session lifecycle state machine + SSE event handling with reconnect logic | Hung | 5h | Reuse PRD → lifecycle | |
| Add idempotency, logging, and the HITL gate handler (stubbed for v1 — goes live with PM Pulse in Week 3) | Hung | 4h | Reuse PRD → HITL | |
| Deploy to VPS and pass the 7-test integration suite | Hung | 3h | Reuse PRD → tests | |
| Approve Anthropic API spend budget (~$50–100 Sprint 1) + sign off on the harness architecture | Jake | 1h | PRD Local Automation |
The harness is the leverage. Built properly once for Sentinel, it carries Catalyst, Revenue Relay, Ad Arbitrage, Build Bot, and PM Pulse for free. The abstraction pays for itself on the second agent — classic “better beats more.”
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Create the SEO Sentinel agent + environment config; wire 5 modules (GBP, On-Page, Geographic grid, Citations, AI Visibility) via bash + SEO Utils MCP | Hung | 5h | PRD Local Automation → §7 | |
| Phanh writes the v1 system prompt + scoring rubric (coverage, accuracy, structure) | Phanh | 3h | SEO Lead Handoff | |
| Wire triggers: ClickUp status → “Ready” and Slack slash-command; output posts to Slack + updates the ClickUp task | Hung | 3h | PRD → triggers | |
| Run T1 + T2 dry runs on a synthetic client; iterate the system prompt with the Phanh | Phanh | 2h | PRD → testing |
Sentinel is read-only on purpose: the riskiest thing an agent can do is publish. Prove accuracy on audits first, earn trust, then graduate to client-facing actions behind HITL gates. ~$1.75/run vs. ~3 analyst hours is the unit win that funds the whole fleet.
Cash in the harness abstraction: plug in Content Catalyst and Revenue Relay via config files, no new orchestration code. In parallel, stand up the n8n playbook as the no-Managed-Agent fallback path.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Drop in catalyst.json — wire Content Catalyst to QueryMind MCP (brief gen, meta optimization, AEO scoring) | Hung | 3h | Reuse PRD → config pattern | |
| Content Lead writes Catalyst's system prompt + rubric; validate brief output vs. a reference brief | Nhu | 3h | QueryMind pipelines | |
| Drop in revenue-relay.json — wire Revenue Relay to GoHighLevel MCP (follow-up sequences, lead scoring) | Hung | 3h | SNMS CRM + Reuse PRD | |
| Confirm the zero-code claim: log the diff — only config files added, dispatcher untouched | Jake | 1h | Reuse PRD → acceptance |
Agent #1 took a week. Agents #2 and #3 take a config file each. That curve is the entire thesis of Layer 2 — build the system, then the marginal cost of capacity collapses toward zero.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Build the 4 n8n modules: GBP Intelligence (44-point), On-Page Engine, Geographic grid (9/25-pt via Apify), Citation/NAP | Hung | 6h | Local SEO Automation Playbook | |
| Wire the pipeline: web form → n8n parallel APIs → Code scoring → OpenAI HTML report → SendGrid → Airtable | Hung | 4h | n8n Playbook → flow | |
| Phanh validates n8n report output parity against a Sentinel run on the same client | Phanh | 2h | n8n Playbook |
Two paths to the same outcome (Managed Agent + n8n) is risk reversal at the infrastructure level. If Anthropic pricing or features shift, delivery doesn't stop — the n8n path keeps the SEO audits flowing.
Complete the fleet (Ad Arbitrage, Build Bot), then deploy PM Pulse — the coordinator that delegates to specialists and activates the HITL gates for client-facing output. Wire it all into the Unified Command Center.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Deploy Ad Arbitrage (ad-arbitrage.json) — Google + Meta reporting, copy variants, audit reports; Sang/Tung write its rubric | Sang + Tung | 3h | Manage Agent SEO swarm | |
| Deploy Build Bot (build-bot.json) — migrations, schema audits, Lighthouse + Playwright UAT | Hung | 3h | Manage Agent SEO | |
| Deploy PM Pulse coordinator — multi-agent delegation, output synthesis, Slack posting | Hung | 4h | AI Orchestration diagram | |
| Activate + test the HITL Slack gate on a client-facing deliverable (email draft / GBP post) — nothing ships without approval | Jake | 2h | Reuse PRD → HITL |
PM Pulse is where agents start producing client-facing work, so the HITL gate goes live here. The centaur model holds: AI throughput, human approval before anything reaches a client. Speed without a quality gate is just faster mistakes.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Stand up the Unified Command Center (ClickUp + Slack) across the 7 workstreams | Hung | 4h | Automating Agency Workflows | |
| Build the ClickUp Agent Registry v1 — agent_id, owner, scope, cost/run, last run, status per agent | PM | 3h | SN Workstream PM | |
| Define governance: spend caps per agent, escalation paths, and the weekly agent-fleet review cadence | PM | 2h | SN Workstream PM → governance |
The Command Center turns six invisible cloud agents into a dashboard a human can run. Cost-per-run, accuracy, and hours saved are visible per agent — the basis for the Phase 2 graduation metrics and every optimization that follows.
Turn the working swarm into a sellable product, enroll the first 2 beta clients, and prove the graduation metrics: SOP accuracy ≥90%, fleet accuracy ≥85%, and ≥30% hour reduction.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Package the Hybrid OS offer — scope, deliverables, price anchor vs. Detailers Roadmap, guarantee | Jake | 3h | AI driven agency → Hybrid OS | |
| Build the Hybrid OS GHL snapshot (the productized delivery container) | Trung Le | 5h | 90-D Transfo → G4 Hybrid OS | |
| Enroll 2 beta clients — one call each, grandfather pricing in exchange for feedback | Jake | 2h | 90-D Transfo → beta |
A second premium product to the same client base is the highest-leverage LTV:CAC move there is. The swarm already runs delivery, so gross margin on the Hybrid OS is structurally higher — that's the “triple the margin” claim made real.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Run the 12-agent parallel UAT (239 of 334 checks automated, ~40 min, ~$9.65/run) on both beta clients | Trung Le | 3h | AI driven agency → UAT | |
| Measure the bar: SOP accuracy ≥90%, fleet accuracy ≥85%, ≥30% hour reduction vs. manual | Jake | 2h | 90-D Transfo → criteria | |
| Compile the Phase 2 retrospective — what to optimize (Stage 6) and Phase 3 (Layer 1) input | Jake | 2h | Master Index → Layer 2 review |
Six Managed Agents on Anthropic infrastructure — one coordinator and five specialists — deployed in 8 days versus four weeks of DIY. Hours saved are weekly capacity recovered across the client book. Pricing is standard tokens + $0.08/session-hour, no idle charges.
Delegates to specialists, synthesizes their outputs, posts to Slack. Owns the HITL gate for client-facing deliverables.
Reports, audits, rank monitoring, AEO. Runs the 5 Local SEO modules at ~$1.75/run, replacing ~3h of analyst work.
Brief generation, meta optimization, AEO scoring — wired to QueryMind MCP.
GHL automation, follow-up sequences, lead scoring — wired to the GoHighLevel MCP.
Google + Meta reporting, ad-copy variants, audit reports across both ad platforms.
Site migrations, schema audits, Lighthouse + Playwright UAT runs.
The end-to-end chain for Agent #1, straight from the Master Index's Layer 2 pipeline. Each link is a real document — WHAT the agent does, HOW it's triggered, WHO owns the deliverables, and the n8n alternative path.
PRD Local Automation — 19-section spec, 5 modules
Reuse PRD — config pattern, SSE, HITL
SEO Lead Handoff — prompt + rubric
Local SEO Automation Playbook — 4 modules
Live payback and return for the fleet. Defaults are grounded in the source docs — SEO Sentinel replaces ~3 analyst hours at ~$1.75/run. Toggle to the fleet view to see total weekly capacity recovered in dollars.
The dollar return is large, but the point isn't token savings — it's that ~165 hours/week of human capacity move from execution to judgment, relationships, and selling the Hybrid OS. That reallocation is what triples margin, not the $1.75 line item.
Phase 2 is the AI-automation buildout — Hung is Responsible for the technical spine (agents, harness, n8n); Trung (IT) owns infrastructure, deployment, and website/Astro builds. Jake stays Accountable and owns the two judgment calls that can't be delegated: spend approval and the HITL gate on client-facing output.
| Workstream | Jake | Hung (AI) | Phanh | Content (Nhu) | Ads (Sang/Tung) | PM |
|---|---|---|---|---|---|---|
| Orchestration harness | A | R | I | I | I | C |
| SEO Sentinel v1 | A | R | R | I | I | I |
| Fleet graduation (agents 2–5) | A | R | C | C | R | I |
| PM Pulse + HITL gates | R | R | C | C | C | A |
| Command Center + Registry | I | R | I | I | I | A |
| Hybrid OS productization | R | C | I | I | I | C |
Phase 2's risk profile is higher than Phase 1's — you're now dependent on a beta platform and shipping AI-produced work toward clients. Each risk has a mitigation already wired into the plan.
The fleet runs on Managed Agents (public beta). A pricing change, feature deprecation, or outage would hit delivery directly — this is the top risk named in the strategic vision.
Mitigation: The n8n playbook (Week 2) delivers the same SEO audits without Managed Agents. Skill definitions are portable to other frontier models; all client data lives in GHL / WordPress / ClickUp, never on Anthropic infrastructure.
Once PM Pulse produces email drafts or GBP posts, an unreviewed error reaches a client and damages trust.
Mitigation: HITL Slack gate is mandatory for any client-facing action (Week 3). Sentinel and the early agents are read-only by design — trust is earned on audits before agents touch published output.
Every agent plugs into one orchestration layer. A harness bug or VPS outage takes the whole fleet down at once.
Mitigation: 7-test integration suite gates the harness before any agent rides on it (Gate A). Idempotency + reconnect logic built in; the n8n path is an independent fallback for the highest-volume workflow.
Agents run, but outputs aren't reliable enough to graduate — the Phase 2 metric fails and beta clients get sub-par work.
Mitigation: Per-agent rubrics + side-by-side validation against reference outputs at each gate. Gate D blocks scaling until ≥85% fleet accuracy and ≥30% hour reduction are measured, not assumed.
Runaway runs or verbose prompts inflate spend beyond the ~$1.75/run economics.
Mitigation: $0.08/session-hour with no idle charges keeps the floor low. The Agent Registry sets per-agent spend caps and the Command Center surfaces cost-per-run weekly. Sprint 1 budget is a contained ~$50–100.
Every sprint traces to specific Layer 2 documents in the 1st Batch. Links resolve to the real files in this folder.
| Sprint | Primary source documents | Theme |
|---|---|---|
| S-1A | Reuse PRD — Agent Orchestration, PRD Local Automation | Managed Agent Arch |
| S-1B | PRD Local Automation, SEO Lead Handoff | Sentinel Pipeline |
| S-2A | Reuse PRD (config pattern), QueryMind, SNMS CRM | Managed Agent Arch |
| S-2B | Local SEO Automation Playbook (n8n) | Workflow Automation |
| S-3A | Manage Agent SEO (swarm), AI Orchestration, Reuse PRD (HITL) | Managed Agent Arch |
| S-3B | Automating Agency Workflows, SN Workstream PM | Workflow Automation |
| S-4A | AI driven agency (Hybrid OS), 90-D Transfo (G4) | Productization |
| S-4B | AI driven agency (UAT), Managed Agent — Monthly Report | Productization |
With delivery automated and the Hybrid OS proven on betas, Phase 3 deploys Layer 1 (Strategic North Star): positioning, the outbound → content flywheel, and the hiring plan — then scales beta clients to paying.
Phase 3 is the lightest phase for Jake (~11h) precisely because Phases 1–2 did the heavy lifting. Confirm these before you start telling the story.
Phase 2 Gate D green: 6-agent swarm coordinated through PM Pulse, Hybrid OS packaged, 2 beta clients live. You can't sell “AI-native” until it's true.
Beta outcomes, time-savings data, and UAT scores from Phase 2 are collected. Positioning runs on proof — raw, recent, numbered — not adjectives.
With delivery automated, the founder's job is positioning, the Go/No-Go call, and key relationships — not execution. ~11h across the month, by design.
Ngọc has the recruitment (Track A) and OKR (Track B) pipelines scaffolded so hiring can run on the same centaur model as delivery.
The 13 Proof Principles rank raw, recent, third-party-verified, numbered results above any claim. Phase 3 spends its energy turning the machine's real outputs into the story — not inventing a story and hoping the machine catches up.
Prove the fleet works with a Health Report, then rewrite the agency's story around it. Maps to the 90-Day plan's Weeks 9–10 (Agent Review + Positioning).
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Pillar leads collect per-agent data: accuracy rate, time saved, error types, override frequency (all 6 agents) | Pillar leads | 6h | 90-D Transfo → Wk 9–10 | |
| Jake writes Health Report v1 — total delivery-hour reduction vs. baseline; verdict against ≥85% / ≥30% | Jake | 3h | Managed Agent — Monthly Report | |
| IT applies prompt refinements + Skills wiring updates; PM updates the Agent Registry | Hung + PM | 3h | Reuse PRD |
The Health Report is both the optimization input (retrain the weak agents) and the marketing input (the numbers become the proof in the positioning). One artifact, two jobs — that's the leverage of measuring honestly.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Rewrite seonavigator.online About + services pages with AI-native messaging | Jake | 3h | AI driven agency → positioning | |
| Update the sales deck + proposals with the six-moat narrative and beta proof points | PM | 2h | SEO Transfo Exec Plan | |
| Content Lead drafts 3 social posts from the positioning brief (the “Rule of 100” engine starts here) | Nhu | 2h | AI driven agency → moat |
A brand is a bouquet of associations. Pair SEO Navigator with “first AI-native,” “half the price, full ecosystem,” and real detailing results. The positioning statement does the work: Detailers Roadmap builds a pretty site and walks away — we run the whole engine for less.
Build the lead machine on Hormozi's Core Four and Dennis Yu's Task Library, then close the loop: every won deal becomes a case study, every case study becomes content, every piece of content generates the next lead.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Build the outbound list (50–100 detailing shops) + warm-outreach ACA scripts and the 9-word cold email | Sales Mgr | 4h | TeamPlay → Dept 07 Sales | |
| Stand up the posted-content cadence: 70-20-10 hook rotation, Rule of 100 (100 min/day on marketing) | Nhu | 3h | Dennis Yu → Content Factory | |
| Point a small paid-ads budget at the new positioning (Ad Arbitrage agent generates variants) | Sang + Tung | 3h | AI driven agency → Pillars 3–4 |
Every business reaches buyers through exactly four channels. You don't need a fifth — you need to actually run the four, 100 units a day. Warm outreach converts ~10× cold, so start there, then layer content and paid on top.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Write the “won deal → case study” Definitive Article + QA checklist + Skill.md (the invocation methodology) | Nhu | 3h | Dennis Yu → Definitive Articles | |
| Publish the first 2 case studies from Phase 2 beta wins; Content Catalyst drafts, human approves (HITL) | Nhu + Minh Chau | 3h | AI driven agency → flywheel | |
| Wire the loop in ClickUp: deal marked “Won” auto-creates a case-study task in the content queue | PM | 2h | Automating Agency Workflows |
Every closed deal feeds the content engine; every publication feeds the schema graph; every update informs the ads. A traditional agency wires this with spreadsheets and loses the loop by month three. Dennis Yu's Meta Article step is what keeps it self-reinforcing.
Hire and manage for the AI-native model. Roll out HR Implementation 2026: role cards first, a hiring rubric that reserves 45% for AI-native dimensions, and OKRs that measure agent leverage — not output volume.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Finalize the 9 role cards (agents managed, human decisions, QA, escalation, accountability) — pilot done, 8 in parallel | Ngọc | 5h | HR Implementation 2026 → Phase 0.5 | |
| Build the hiring rubric: 45% AI-native (AI fluency, Agent-Manager capability, Ownership Operator, QA) + 55% role skills | Ngọc | 3h | HR Implementation 2026 → Track A | |
| Jake validates role cards + rubric; confirm Claude drafts, Ngọc reviews every output before it reaches a candidate | Jake | 1.5h | Who Wins in an AI Agent Economy |
Stage 6 says optimize the team you have before adding bodies. The Agent-Manager role card makes “better” concrete: every hire is measured on how well they command agents, not how much they personally produce. Reserve 45% of the score for that.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Stand up Track B OKR system in ClickUp; KPIs = hours recovered, override rate, agents managed (not output volume) | Ngọc | 3h | HR Implementation 2026 → Track B | |
| Run the Vista avatar pass: survey clients, sort by spend + retention, define the top-20% avatar to target | Jake | 2h | AI driven agency → ICP | |
| Brief the team on Ownership Operator culture; tie the avatar definition into outbound targeting (Week 2 engine) | PM | 1.5h | Who Wins in an AI Agent Economy |
The Vista method: survey everyone, find the 3–5 traits of your top spenders, then speak only to that avatar. Replacing the bottom 80% with more of the top 20% is a path to 5× growth — without serving a single additional logo.
Make the Go/No-Go call on the Hybrid OS, convert betas to paying, then ship the positioning video and the final scorecard. Maps to the 90-Day plan's Weeks 11–12 (Beta Evaluation + Video + Close).
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| PM collects beta feedback + prepares the Go/No-Go data (retention, outcome parity, delivery-cost reduction vs. DFY) | PM | 4h | 90-D Transfo → Wk 11–12 | |
| Jake writes the Go/No-Go memo; if Go, convert both betas to paying and outline the Tier 3 launch plan | Jake | 2.5h | AI driven agency → Hybrid OS | |
| If Go: PM builds the Tier 3 onboarding sequence from Jake's outline | PM | 3h | 90-D Transfo → Tier 3 |
If delivery costs drop ≥40% while outcomes hold, the Hybrid OS enters the virtuous cycle: premium price → quality customers → higher margin → reinvest in quality. That's the structural “triple margin” the centaur model promises — now proven on real betas, not a spreadsheet.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Record the 3-min positioning video: problem → solution → proof. One take, ship it | Jake | 2.5h | 90-D Transfo → Wk 11–12 | |
| Content Lead polishes + publishes the video and the 3 social posts; cross-check against Authority Hacker assets | Nhu | 4h | Authority Hacker → 7 Pillars | |
| Complete the final 90-day scorecard — score every metric, capture lessons, write the next 90-day plan | Jake | 2h | Master Index → full review |
One take, ship it. The scorecard isn't the finish line — it's the lookback that seeds the next 90-day cycle. Stage 7 (Categorize) begins where this ends: triage what's working, organize the swarm and the team, and run it again.
Positioning isn't adjectives; it's the defensible reasons a competitor can't catch you in 12 months. These six moats — straight from the strategic vision — are the spine of every sales page, proposal, and social post built this phase.
Koray Semantic Content Network + a proprietary 6-dimension scoring framework + AI Overview consensus. Built over 2+ years, tuned to detailing.
Coordinator + 5 specialists on Anthropic infra, 30+ Claude Skills, 6 MCP servers. Requires research-preview access + orchestration depth.
200+ detailing keywords pre-loaded, 450+ GHL templates, 6 hook archetypes validated on detailing ads. Generic agencies start from zero.
Distributed team + AI execution = half of Detailers Roadmap's price at triple the margin. Incumbents can't match without rebuilding delivery.
12-agent UAT covers 334 checks across every pillar in ~40 min at ~$9.65. A traditional agency burns ~20 human hours on the same scope.
The whole team is trained to manage AI agents. Copying the skills doesn't give you the team that can run them at scale — that's Week 3's work.
Hormozi's Core Four feed the pipeline; Dennis Yu's Task Library closes the loop. The output of delivery becomes the input to acquisition — a self-reinforcing engine, not a funnel that empties.
Beta or new client closes
Catalyst drafts, human approves
Warm · cold · content · paid
Meta Article → new leads
Where the flywheel takes revenue. Defaults assume the Hybrid OS retainer (~$1,750/mo) and the centaur capacity claim — the same small team can serve 50–100 clients. Drag to see MRR, annual run-rate, and whether 12-month growth stays within capacity.
Margins triple because AI runs ~70% of execution — so growth flows to profit, not payroll. The capacity check matters: when 12-month clients approach ~100, that's Stage 7 (Categorize / Specialize) territory, where you replace generalists with specialists rather than burning out the team.
Phase 3 is the founder's phase — positioning, the Go/No-Go call, and the avatar are his to own. But even here he's Responsible for only the irreducible judgment calls; Sales, Content, and HR carry the execution.
| Workstream | Jake | Sales Mgr | Content (Nhu) | Ngọc (HR) | PM | Ads |
|---|---|---|---|---|---|---|
| Fleet Health Report | R | I | I | I | C | C |
| Positioning & brand | A | C | R | I | R | I |
| Core Four lead engine | A | R | R | I | C | R |
| Content flywheel loop | I | I | R | I | A | I |
| Hiring & OKRs | A | I | I | R | C | I |
| Hybrid OS Go/No-Go | R | I | I | I | R | I |
Phase 3's risks are growth risks — the story, the pipeline, the team, and scale. Each has a mitigation already built into the plan.
Positioning, the Go/No-Go, and key relationships all sit with Jake. If sales never leaves his calendar, growth caps the moment he's busy — the exact bottleneck Phases 1–2 removed from delivery.
Mitigation: The Core Four engine + Sales Manager (Dept 07) + the automated content flywheel move top-of-funnel off Jake. He keeps only the high-judgment close and the Go/No-Go memo.
“AI-native” is becoming a crowded claim. If the story is adjectives without proof, it blends in and the price premium evaporates.
Mitigation: Positioning is anchored on the six concrete moats + real beta results (13 Proof Principles: raw, recent, numbered). Gate A blocks positioning until the Health Report proves the machine.
Winning faster than the swarm + team can absorb degrades outcomes — and a public AI-native promise makes quality slips very visible.
Mitigation: The Scale calculator's capacity check flags the ~100-client ceiling; HITL gates hold quality; Stage 7 (specialize) is the planned response to capacity, not heroics.
Hiring strong individual operators who can't manage agents rebuilds the old, non-leveraged agency one seat at a time.
Mitigation: Role cards precede rubrics; 45% of every hiring score is reserved for AI-native dimensions; KPIs measure agent leverage, not personal output.
Google's AI Overviews shrink organic click-through — a structural headwind for the SEO pillar's lead gen.
Mitigation: The Consensus Audit skill targets AIO eligibility, and positioning spans SEO + Ads + CRM, so downstream revenue doesn't depend on organic clicks alone.
Every sprint traces to specific Layer 1 documents in the 1st Batch. Links resolve to the real files in this folder.
| Sprint | Primary source documents | Theme |
|---|---|---|
| S-1A | 90-D Transfo (Wk 9–10), Managed Agent — Monthly Report | AI-Native Transformation |
| S-1B | AI driven agency (moat + positioning), SEO Transfo Exec Plan | AI-Native Transformation |
| S-2A | Dennis Yu — AI Agents Marketing, TeamPlay (Dept 07) | External Methodology |
| S-2B | Dennis Yu (Definitive/Meta), Automating Agency Workflows | External Methodology |
| S-3A | HR Implementation 2026, Who Wins in an AI Agent Economy | HR & Workforce |
| S-3B | HR Implementation 2026 (Track B), AI driven agency (ICP) | HR & Workforce |
| S-4A | 90-D Transfo (Wk 11–12), AI driven agency (Hybrid OS) | AI-Native Transformation |
| S-4B | 90-D Transfo (scorecard), Authority Hacker → 7 Pillars | External Methodology |
Phase 3 closes the loop. The three playbooks deploy the 1st Batch architecture bottom-up by revenue impact: serve clients, automate delivery, then amplify. Founder hours fall at every step.
Layers 3+4 · ~20h Jake · CRM + onboarding + reporting
Layer 2 · ~22h Jake · 6-agent swarm + Hybrid OS
Layer 1 · ~11h Jake · positioning + flywheel + team
Categorize · scale the avatar, specialize roles
Phases 1–3 deploy the documented 4-layer architecture and the 90-day plan. Phase 4 goes beyond the source docs into the post-transformation scale cycle. It's grounded where the docs point forward — the 50–100 client capacity claim, the “next 90-day plan” handoff, the Tier 3 launch, GHL SaaS mode, and Hormozi Stages 7–9 — but the specific targets and dates are projection. Treat the numbers as planning assumptions to pressure-test, not commitments.
Categorize the client base, double down on the avatar that pays, and specialize roles so the team can serve 50–100 clients on the staffing of ten without quality slipping.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Rank all clients by spend × retention; tag the top 20% and the bottom 20% (graduate, fix, or fire) | PM | 3h | Vista avatar (Phase 3 carry-over) | |
| Write the sharpened ICP one-pager (3–5 traits of the top spenders) and feed it to the Core Four engine | Jake | 2h | AI driven agency → ICP / moat | |
| Re-aim outbound + retargeting at the avatar; sunset or reprice the worst-fit accounts | Sales Mgr | 3h | Phase 3 → Core Four |
Replacing the bottom 80% with more of the top 20% is a path to 5× growth without serving a single extra logo. Concentration, not addition, is the Stage 7 move.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Finalize the remaining role cards; redefine generalist seats as specialist Agent-Manager roles | Ngọc | 4h | HR Implementation 2026 | |
| Capacity test: run the fleet against a simulated 50-client load; flag bottleneck agents to scale | Hung | 3h | Reuse PRD / Agent Registry | |
| Approve any specialist hire only against the 45%-AI-native rubric; document the capacity ceiling | Jake | 1.5h | HR Implementation 2026 → rubric |
At scale, generalists become the bottleneck. Replacing them with specialists — humans and agents alike — is how throughput keeps rising without quality falling.
Turn the SNMS + agent stack into a product other shops and agencies can buy — a second revenue line on top of the agency, sold via GHL SaaS mode / snapshot licensing.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Productize the SNMS snapshot for GHL SaaS mode; strip client-specific config, add setup wizard | Trung Le | 6h | SNMS Ultimate CRM · GHL SaaS mode | |
| Bundle the customer-facing Launchpad tutorials + Definitive Articles as the self-serve knowledge base | Trung + Content | 4h | Customer Launchpad · Dennis Yu | |
| Decide what's licensed vs. held back as the agency moat (keep QueryMind depth + done-for-you premium) | Jake | 2h | AI driven agency → moat |
The agency proves the system; the license sells it. GHL SaaS mode lowered the bar for anyone to launch — so the defensible move is to license the proven methodology + agent stack, while keeping the deepest moat (QueryMind, done-for-you) in-house.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Set license pricing tiers + offer stack (anchor against done-for-you; protect the premium) | Jake | 2h | Hormozi offer stack | |
| Sell the first 5–10 license seats to non-competing shops/markets; onboard via the wizard | Sales Mgr | 5h | Core Four (Phase 3) | |
| Stand up license support + churn tracking in the Command Center; define the success metric | PM | 3h | Automating Agency Workflows |
A license is recurring revenue at near-software margin. Even a handful of seats meaningfully lifts blended ARR — and the valuation multiple on recurring license revenue is higher than on services.
Take the proven engine into bigger TAM — adjacent verticals, new geographies, and multi-location / franchise accounts — then set up the next cycle (Stage 9, Capitalize).
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Select one adjacent vertical (e.g. PPF-heavy auto, wraps, or a parallel local-service niche) with similar AOV/intent | Jake | 2h | AI driven agency → TAM | |
| Clone QueryMind + skills for the new vertical; build the first topical map + city-page set | Nhu | 5h | QueryMind · Pattern C | |
| Land one multi-location/franchise account; template the rollout across its locations | Sales Mgr | 4h | Pattern C (franchise) |
The engine is vertical-tuned, so expansion is cloning, not invention. One adjacent vertical and one franchise account de-risk the move before committing budget to a full market push.
| Task | Owner | Hrs | Source | |
|---|---|---|---|---|
| Launch the outbound + content engine in one new metro/region; track CAC + close rate vs. home market | Sales Mgr | 4h | Core Four · Radius optimizer | |
| Compile the Next-90 scorecard: clients, blended MRR, license MRR, margin, capacity headroom | PM | 3h | Command Center · Registry | |
| Write the next 90-day plan + the Stage 9 “big bet” thesis (acquire a competitor, or invest in R&D) | Jake | 2h | Hormozi Stage 9 Capitalize |
Once the engine scales across verticals and geos, the next leverage is a single concentrated bet: acquire a competitor (Detailers Movement runs 55+ staff — you do it with ten) or invest in proprietary R&D. That thesis is the output of this cycle, the input to the next.
The 90-day transformation took the agency to Stage 6. Phase 4 is the climb from Stage 7 to Stage 9 — categorize, specialize, capitalize.
Triage and organize: concentrate on the avatar, specialize roles, license the system. This is the spine of Phase 4.
Replace generalists with specialists — human and agent. Begins inside M1 and carries into the next cycle.
Acquire a competitor or invest in R&D. The thesis is written in M3; the bet is placed in the next cycle.
Where two revenue lines take the business. Agency retainers + license seats → blended MRR, ARR, and a rough enterprise value at a 3× revenue multiple. Toggle agency-only vs. agency + license to see what the second line is worth.
Service revenue trades at a low multiple; recurring product/license revenue trades higher. Adding a license line doesn't just add MRR — it re-rates the whole business. The 3× here is a planning placeholder; real multiples depend on growth, retention, and mix.
Phase 4 splits cleanly: Jake owns the strategic calls, Sales owns expansion + license GTM, IT owns the product build, HR owns specialization.
| Workstream | Jake | Sales Mgr | Trung (IT) | Ngọc (HR) | PM | Content |
|---|---|---|---|---|---|---|
| Avatar concentration | A | R | I | I | R | I |
| Specialize roles | A | I | C | R | C | I |
| Productize / license build | A | I | R | I | C | R |
| License pricing + GTM | R | R | I | I | C | I |
| Vertical / geo expansion | A | R | I | I | C | R |
| Next-cycle / big bet | R | I | I | I | R | I |
Scale risks are different from build risks — dilution, cannibalization, and quality-at-volume. Each has a mitigation built into the movements above.
Winning faster than the fleet + team can absorb degrades outcomes — and a public AI-native promise makes slips very visible.
Mitigation: Gate A capacity-tests to ~50 clients before expansion; HITL gates hold quality; specialization (Stage 8) is the planned response, not heroics.
A cheap self-serve license could pull revenue from the high-margin done-for-you agency instead of adding to it.
Mitigation: The deepest moat (QueryMind depth, done-for-you) is held back from the license; pricing anchors the license below DFY; sell licenses to non-competing markets first.
If positioning, pricing, and key closes stay on Jake's calendar, scale caps the moment he's busy.
Mitigation: Sales Manager owns outbound + license GTM; the content flywheel feeds top-of-funnel; Jake keeps only the high-judgment close and the big-bet thesis.
An adjacent vertical or new geography may not convert like the proven detailing home market.
Mitigation: Expand by cloning, one vertical + one geo at a time; Gate C benchmarks CAC + close rate vs. home market before further spend.
Jumping to acquisition / heavy R&D (Stage 9) before the engine is proven at scale risks the whole business.
Mitigation: Phase 4 only writes the thesis; the bet is placed in the next cycle, gated on Stage 7–8 actually clearing first.
Phase 4 is forward projection, but each movement leans on something real in the 1st Batch. Where a row says “projection,” that's a planning assumption, not a documented plan.
| Movement | Grounded in | Basis |
|---|---|---|
| M1 Scale | AI driven agency, HR Implementation 2026 | Grounded 50–100 capacity, Vista avatar, specialize roles |
| M2 Productize | SNMS Ultimate CRM, Customer Launchpad | Partly projected GHL SaaS mode is referenced as a risk; licensing is the inverse play |
| M3 Expand | AI driven agency (TAM), 90-D Transfo (next-90) | Partly projected $7–12B TAM + “next 90-day plan” handoff; specific markets are projection |
| Stages 7–9 | Hormozi Scaling Roadmap (7–9, adapted) | Framework Categorize → Specialize → Capitalize |