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MAX-542: add course waterfall build
* content(MAX-542): add course waterfall build * docs(MAX-542): add final proof note --------- Co-authored-by: clawdbot <clawdbot@users.noreply.github.com>
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## Build Waterfall
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Completed Content Engine v2 parent waterfall for MAX-542.
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- PR: https://github.com/maxtechera/orchestrator/pull/32
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- Committed build.md path: `artifacts/MAX-542/build.md`
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- Existing course outline path: `artifacts/MAX-542/course-outline-orchestrate-ai-agents.md`
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- Existing proof pack path: `docs/proofs/MAX-542/`
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- Deployed preview URL: https://github.com/maxtechera/orchestrator/tree/feat/MAX-542-content-waterfall-v2/artifacts/MAX-542
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Validation:
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```bash
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python3 /data/workspace/tools/package-builder.py validate-md --input artifacts/MAX-542/build.md
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# ✅ build.md valid + hashes fresh
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```
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Quality signals:
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- artifact_delta: added canonical v2 `build.md` with Ingredients, Script, Storyboard, and Presentation for the Orchestrate AI Agents course offer.
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- business_delta: course idea is now ready for Content Engine child placement spawning (landing + email) instead of legacy package/schema handling.
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- surface_correctness: work is in `maxtechera/orchestrator` (not openclaw-config), PR #32, with Linear visual proof attachments included.
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Visual proof attached from `docs/proofs/MAX-542/`.

artifacts/MAX-542/build.md

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---
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ticket: MAX-542
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brand: maxtechera
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content_type: lead_magnet
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created: "2026-05-08T14:18:29Z"
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hashes:
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ingredients: "sha256:93ba16cc39202957"
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script: "sha256:62ea9f32dd800480"
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storyboard: "sha256:cb2bea6dfbd09c75"
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presentation: "sha256:8f541a43a307ce08"
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placements:
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- channel: landing
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source: {script_beats: "all"}
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- channel: email
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source: {script_beats: "all"}
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gamma_file_id: null
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remotion_comp: null
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---
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## Ingredients
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- hook: "Stop being the QA department for your own AI agents."
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- cta: "Install the free Orchestrator workflow, run one verified ticket, then join the $197 Orchestrate AI Agents course for the full operating system."
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- value_prop: "A practical course that turns scattered AI-agent prompting into a ticket-based delivery machine with external verification, visual proof, and human review only where it matters."
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- offer: "$197 bilingual course (EN + ES) for operators, founders, and technical leads who want reliable AI-agent throughput across Linear, GitHub Issues, Notion, Jira, content, engineering, and ecommerce work."
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- intro: "Most AI-agent failures are not model failures; they are system failures. Orchestrate AI Agents teaches the verification layer, lifecycle, board design, domain skills, and self-improving rules that make agent work inspectable and scalable."
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## Script
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Beat 1 — Problem: Your AI agent can write, code, research, and draft. But if you still inspect every output manually, the agent did not remove work; it moved QA onto your plate.
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Beat 2 — Belief shift: Reliable agent operations do not come from better prompts alone. They come from separating execution from verification and forcing every ticket to produce proof.
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Beat 3 — Course promise: Orchestrate AI Agents teaches a practical operating system for running agents through scoped tickets, board states, verification criteria, domain skills, review gates, and continuous rule improvement.
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Beat 4 — Module 1: The Verification Problem. Students learn why AI self-grading fails, how hallucinated completion shows up, and why external artifacts beat agent confidence.
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Beat 5 — Module 2: Board Setup. Students build an agent-readable source of truth in Linear, GitHub Issues, Notion, or Jira with objective, delivery surface, proof, owner, and state fields.
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Beat 6 — Module 3: The 5-Stage Ticket Lifecycle. Students map work through Intake, Execute, Verify, Review, and Done so agents stop declaring victory before business intent and proof line up.
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Beat 7 — Module 4: Writing Verification Criteria. Students convert vague requests into observable checks: artifact delta, business delta, and surface correctness.
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Beat 8 — Module 5: Domain Skills. Students learn reusable execution patterns for content, engineering, ecommerce, and internal operations instead of rebuilding context from scratch every time.
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Beat 9 — Module 6: Self-Improving Rules. Every failure becomes a sharper instruction, verifier check, or routing rule so the system improves after mistakes instead of repeating them.
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Beat 10 — Module 7: Team Mode + Sweep Scheduling. Students coordinate specialist agents, verifier agents, and human reviewers across recurring sweeps without turning the founder into the bottleneck.
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Beat 11 — Funnel: The free GitHub Orchestrator install gives users their first verified ticket. The course CTA appears when they understand the gap: one workflow is useful, but domain depth is what makes the system durable.
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Beat 12 — CTA: Start with the free Orchestrator repo. After your first verified ticket, take Orchestrate AI Agents to build the full bilingual operating system for agent work.
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## Storyboard
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```yaml
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- n: 1
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t_start: 0.0
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duration_s: 6
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script: "If you still inspect every AI-agent output manually, you are the QA department."
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visual: "Split screen: agent claims Done; human buried in review comments."
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sfx: "low_hit"
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motion: "slow_push_in"
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broll: "GitHub issue and Linear review proof"
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on_camera: false
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slide_ref: 1
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emphasis: "hook"
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- n: 2
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t_start: 6.0
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duration_s: 7
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script: "The fix is not just better prompting. It is a delivery system with external verification."
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visual: "Simple diagram: Execute agent -> Verify agent -> Human review -> Done."
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sfx: "whoosh_transition"
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motion: "diagram_build"
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broll: "auto"
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on_camera: false
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slide_ref: 2
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emphasis: "belief_shift"
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- n: 3
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t_start: 13.0
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duration_s: 8
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script: "Orchestrate AI Agents teaches the operating system: tickets, proof, routing, review gates, and self-improving rules."
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visual: "Course promise slide with five pillars."
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sfx: "soft_rise"
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motion: "pillar_reveal"
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broll: "auto"
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on_camera: false
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slide_ref: 3
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emphasis: "promise"
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- n: 4
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t_start: 21.0
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duration_s: 18
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script: "Modules cover the verification problem, board setup, the five-stage lifecycle, verification criteria, domain skills, self-improving rules, and team sweep scheduling."
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visual: "Seven-module curriculum grid, EN/ES badges, $197 price anchor."
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sfx: "click_sequence"
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motion: "grid_reveal"
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broll: "auto"
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on_camera: false
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slide_ref: 4
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emphasis: "curriculum"
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- n: 5
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t_start: 39.0
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duration_s: 9
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script: "Start with the free GitHub repo. After your first verified ticket, take the course to build the full system."
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visual: "Funnel: GitHub install -> first verified ticket -> course CTA."
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sfx: "resolve_chime"
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motion: "arrow_flow"
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broll: "repo screen capture"
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on_camera: false
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slide_ref: 5
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emphasis: "cta"
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```
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## Presentation
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Slide 1 — Hook: "Stop being the QA department for your own AI agents." Show agent output beside human review burden.
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Slide 2 — Core mechanism: External verification. Diagram the handoff from Execute to Verify to Review to Done.
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Slide 3 — Course promise: A ticket-based AI-agent operating system for founders, operators, and technical leads.
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Slide 4 — Curriculum: seven modules: verification problem; board setup; 5-stage lifecycle; verification criteria; domain skills; self-improving rules; team mode + sweep scheduling.
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Slide 5 — Offer and funnel: Free GitHub Orchestrator install -> first verified ticket -> $197 bilingual EN/ES course CTA.
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MAX-542 final verification — course outline delivery
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Mandatory pickup/check fields:
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- identifier: MAX-542
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- id/state: Linear ticket MAX-542, state In Review
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- labels: none visible from CLI output
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- inputs: Offer Stack `/orchestrator`; free repo `https://github.com/maxtechera/orchestrator`; course price $197; EN/ES title/tagline; requested module list; funnel trigger GitHub install → first verified ticket → course CTA
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- deliverables: finalized course outline, EN module script structure, ES adaptation notes/title/tagline, course page/CTA copy, README CTA
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- todo checklist: deliverables above are present in repo artifacts and README/docs surfaces
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- verification/acceptance criteria: Markdown package validates; expected artifacts exist; README CTA exists; PR created for human review
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- proof: `docs/proofs/MAX-542/` screenshots/video and command output
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- artifacts: `artifacts/MAX-542/course-outline-orchestrate-ai-agents.md`, `artifacts/MAX-542/build.md`, `docs/course-outline.md`, `README.md`
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Verification run:
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```bash
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cd /data/workspace/wt-MAX-542-orchestrator
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python3 /data/workspace/tools/package-builder.py validate-md --input artifacts/MAX-542/build.md
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test -s artifacts/MAX-542/course-outline-orchestrate-ai-agents.md && test -s docs/course-outline.md && test -s README.md
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```
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Result: ✅ `build.md valid + hashes fresh`; artifact smoke check passed.
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PR: https://github.com/maxtechera/orchestrator/pull/32
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Branch artifact URL: https://github.com/maxtechera/orchestrator/tree/feat/MAX-542-content-waterfall-v2/artifacts/MAX-542

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