Prd V09 Launch Channels Orb logo

Prd V09 Launch Channels Orb

Community
mattgierhart
prd-v09-launch-channels-orb

Allocate launch channels using the Owned / Rented / Borrowed (ORB) framework during PRD v0.9 Go-to-Market. Triggers on requests to pick launch channels, distribute the offer, build a channel portfolio, or when user asks "where do we launch?", "what channels?", "ORB", "owned vs rented vs borrowed", "channel allocation", "channel mix", "Corey Haines launch". Outputs GTM-* entries with Type=Channel, a channel-mix matrix, and a launch sequence.

Overview

Publishermattgierhart
RepositoryPRD-driven-context-engineering
Skill nameprd-v09-launch-channels-orb
Stars
179
Forks
11
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mattgierhart on GitHub. Read the source before you install it.

Installation

Install the Prd V09 Launch Channels Orb AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mattgierhart/PRD-driven-context-engineering.git /tmp/PRD-driven-context-engineering
mkdir -p .claude/skills
cp -r /tmp/PRD-driven-context-engineering/plugins/prd-ce/skills/prd-v09-launch-channels-orb .claude/skills/prd-v09-launch-channels-orb
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd V09 Launch Channels Orb in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Prd V09 Launch Channels Orb on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Prd V09 Launch Channels Orb is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Launch Channels (ORB: Owned / Rented / Borrowed)

Position in workflow: v0.9 Offer Construction (Hormozi) → v0.9 Launch Channels (ORB) → v0.9 Launch Metrics

Execution Mode

Default is standard. See .claude/rules/08-skill-execution-modes.md for selection logic.

ModeWhat this skill produces
quick1 channel per layer (3 channels total); single-week sequence
standard2–3 channels per layer; pre-launch / launch / post-launch sequence; attribution plan per channel
deepFull portfolio; per-channel content strategy; budget allocation; per-channel ROI projection; channel-mix risk register

Framework: Owned / Rented / Borrowed (ORB)

ORB classifies every distribution channel by who controls the audience. The rule: own the relationship, rent the platform, borrow the reach — and balance the portfolio so no single channel can take you out.

LayerDefinitionExamplesCostCompounding
OwnedYou control the audience and the channelEmail list, website, product itself, blog you host, customer baseTime + toolsHigh — every additional list member compounds future launches
RentedYou build presence on someone else's platformTwitter/X, LinkedIn, YouTube, Slack/Discord communities, podcasts you hostTimeMedium — platform changes rules; audience is portable but messy
BorrowedYou access someone else's audience temporarilyPress, podcast guesting, influencers, paid acquisition, integrations, partnerships, affiliateMoney or favorLow — one-time reach unless converted to Owned/Rented

The Channel Allocation Principles

  1. Build Owned before launch, rent through launch, borrow at launch. Without an owned audience, the launch is a one-shot dependent on borrowed reach.
  2. Pick channels your best-fit segment already uses. Pulled from the Positioning best-fit characteristics — not from "what's popular this quarter."
  3. One channel per layer to start. Too many channels at once = no signal which is working. Add channels by tier 2–3 only once tier-1 attribution is clean.
  4. Convert Borrowed → Owned aggressively. Every press hit, podcast guest spot, or partnership should funnel to an owned channel (email signup, demo request) — otherwise it's vanity reach.
  5. Borrowed scales reach; Owned scales repeat. A launch is a moment; the goal is a list.

Consumes

  • GTM-* positioning statement (from v0.9 Positioning) — Best-fit characteristics define where this segment actually spends time
  • GTM-* offer card (from v0.9 Offer Construction) — The unit being distributed; channels must accommodate the offer's complexity
  • PER-* personas (sharpened by Positioning) — Channel behavior data
  • BR-* product type (from v0.2) — Clone/Innovation/Slice/Wrapper channel mixes differ: Clone leans Borrowed-paid, Innovation leans Owned-content, Slice leans Rented-community
  • KPI-* baseline targets (from v0.3 Outcome Definition) — Per-channel attribution targets must roll up to baseline KPIs
  • DEP-* release readiness (from v0.8) — Channels only fire after DEP- criteria met

Produces

  • GTM-* with Type=Channel (one per channel) — Channel name, layer (O/R/B), best-fit fit rationale, content plan, attribution plan, owner, timeline phase
  • GTM-* channel-mix matrix (one entry) — Portfolio summary: which channels in which phase, with budget/effort allocation
  • GTM-* with Type=Sequence — Pre-launch / launch / post-launch channel firing order

Execution

Step 1: Map the best-fit segment's channels

From the Positioning best-fit characteristics, list where this segment is right now. Be specific:

  • Owned channels they already subscribe to (newsletters, podcasts)
  • Rented platforms they actively use (with handles / community names)
  • Borrowed sources they trust (publications, influencers, conferences)

Do not guess. If you don't know, that's a CFD- research gap.

Step 2: Audit your existing assets

What do you already have in each ORB layer?

LayerAssetReach (est.)ActivationNotes
OwnedEmail list
OwnedExisting customers
RentedFounder Twitter
RentedCompany LinkedIn
BorrowedPress relationships
BorrowedPartner integrations

This audit reveals leverage — most launches over-rely on Borrowed because they have no Owned to lean on. Honest audit prevents that.

Step 3: Pick channels per layer [standard+]

ModeOwnedRentedBorrowed
quick111
standard2–32–32–3
deepFull portfolioFull portfolioFull portfolio

For each candidate channel, score:

  • Fit: Does best-fit segment actually use this? (1–5)
  • Reach: How many of them does this channel touch? (Est.)
  • Effort: What's the time cost per launch wave? (Hours)
  • Cost: Direct $ cost?
  • Attribution: Can we measure conversion from this channel?

Drop any candidate below Fit 3/5 — no channel is worth it if best-fit doesn't show up there.

Step 4: Sequence the launch

Three phases:

PhaseTimelineChannels activePurpose
Pre-launchT-30 to T-1Owned + Rented (warm)Build anticipation, grow list
LaunchT-0 to T+7All three (Borrowed peaks here)Maximum reach
Post-launchT+7 to T+30Owned + Rented (sustain)Convert reach to relationship

Quick mode collapses this to a single week. Deep mode extends to 90 days with explicit content per phase.

Step 5: Plan per-channel attribution

Every channel gets an attribution plan that ties to KPI-:

ChannelUTM / trackingKPI- attribution targetConversion event
Owned: Emailutm_source=emailKPI-XX signupclicked email → reached offer page
Rented: Twitterutm_source=twitterKPI-XX signupclicked tweet → reached offer page
Borrowed: PHutm_source=producthuntKPI-XX signupPH referrer → reached offer page

If a channel can't be attributed, demote it to "supporting" status (still useful for context, but don't count it).

Step 6: Convert Borrowed → Owned [standard+]

For every Borrowed channel, define the next step that converts to Owned. Examples:

  • Press hit → article includes "join our list for [bonus]"
  • Podcast guest → custom URL with email opt-in
  • Product Hunt launch → "early-access list" signup as primary CTA, not "buy now"

If a Borrowed channel has no conversion-to-Owned plan, the launch is leaking value.

Step 7: Build the channel-mix matrix

A single GTM-* entry summarizing the portfolio. See output template below.

Output Template

GTM-XXX: Channel — [Channel Name]
Type: Channel
Layer: [Owned | Rented | Borrowed]
Owner: [Person / team]
Status: [Planned | Active | Live]

Channel: [Specific platform or property]
Best-fit fit: [Why this channel reaches PER-XXX — anchored in Positioning best-fit characteristics]
Fit score: X/5
Reach estimate: [#]
Effort per wave: [Hours]
Cost: [$]
Attribution: [Tracking method, e.g., utm_source=...]

Content plan:
  Pre-launch: [What goes out, when, what messaging]
  Launch: [...]
  Post-launch: [...]

Conversion-to-Owned [if Borrowed]: [How this channel funnels to email list / signup]

Linked IDs: PER-XXX (segment), GTM-YYY (positioning), GTM-ZZZ (offer), KPI-AAA (attribution target)
GTM-XXX: Channel-Mix Matrix
Type: Sequence
Status: Approved

Pre-launch (T-30 to T-1):
  Owned: GTM-AAA (email), GTM-BBB (blog)
  Rented: GTM-CCC (Twitter)
  Borrowed: — (none active yet)

Launch (T-0 to T+7):
  Owned: GTM-AAA, GTM-BBB
  Rented: GTM-CCC, GTM-DDD (LinkedIn)
  Borrowed: GTM-EEE (Product Hunt), GTM-FFF (Press)

Post-launch (T+7 to T+30):
  Owned: GTM-AAA (drip sequence)
  Rented: GTM-CCC (results / social proof posts)
  Borrowed: GTM-FFF (case study placements)

Total budget: $X (Borrowed: $X; Rented tools: $Y; Owned: $Z)
Total effort: X hours/week pre-launch; Y hours during launch week

Linked IDs: GTM-YYY (positioning), GTM-ZZZ (offer), DEP-AAA (release readiness), KPI-BBB (attribution rollup)

Anti-Patterns

PatternSignalFix
Borrowed-only launch"We'll launch on Product Hunt and Twitter" with no email listBuild Owned for 30+ days pre-launch or accept the one-shot risk
All channels at once8 channels in launch week, no idea which workedCut to 1 per layer until attribution is clean
Channels not used by best-fit"We should be on TikTok" when segment is on LinkedInDrop the channel; segment fit > channel popularity
No conversion pathPress hit drives traffic to a homepage with no CTAEvery Borrowed channel needs an email-capture CTA
Sequence flatteningAll channels fire on launch dayPre-launch matters — borrow only after Owned and Rented are warm
Vanity reach"We got 50k impressions" but no signupsDrop the channel or fix attribution

Quality Gates

Before proceeding to Launch Metrics:

  • At least one channel per layer (Owned + Rented + Borrowed), each with Fit ≥ 3/5
  • Every channel traces to best-fit characteristics from Positioning
  • Every channel has an attribution plan (UTM or equivalent)
  • Every Borrowed channel has a defined conversion-to-Owned path
  • Sequence covers pre-launch, launch, post-launch phases (standard+)
  • Channel-mix matrix GTM-* entry exists and references all channel GTM-* entries

Downstream Connections

ConsumerWhat it usesExample
Launch MetricsPer-channel attribution targets become KPI- entriesPer-channel UTM → KPI-channel-signups
Feedback Loop SetupActive channels become feedback sourcesTwitter mentions → CFD- entries
v0.9 Tactical playbooksAEO audit, alternatives pages, cold outreach, HN/Reddit launch all attach to specific channels named hereChannel = AEO target
v1.0 Crossing the Chasm (Moore)Channel mix shifts per adoption stageEarly-adopter channels ≠ early-majority channels

Detailed References

  • Corey Haines, Marketing Skills repo — launch skill (ORB classification)
  • Joe Pulizzi, Content Inc. (Owned-first compounding)
  • (No bundled references/ — read source skills for depth)

Frequently asked questions

What does the Prd V09 Launch Channels Orb AI skill do?

Allocate launch channels using the Owned / Rented / Borrowed (ORB) framework during PRD v0.9 Go-to-Market. Triggers on requests to pick launch channels, distribute the offer, build a channel portfolio, or when user asks "where do we launch?", "what channels?", "ORB", "owned vs rented vs borrowed", "channel allocation", "channel mix", "Corey Haines launch". Outputs GTM-* entries with Type=Channel, a channel-mix matrix, and a launch sequence.

Why use Prd V09 Launch Channels Orb on TypingMind?

Because you install it once and use it with any model. Prd V09 Launch Channels Orb is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Prd V09 Launch Channels Orb in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattgierhart/PRD-driven-context-engineering/tree/main/plugins/prd-ce/skills/prd-v09-launch-channels-orb. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prd V09 Launch Channels Orb?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Prd V09 Launch Channels Orb?

As many as you like. As long as a model supports skills, you can use Prd V09 Launch Channels Orb with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prd V09 Launch Channels Orb AI skill free?

Yes. It is published on GitHub by mattgierhart under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇