The Problem You're Already Living

You're using AI tools to keep up with impossible content demands. ChatGPT for that pitch deck. Claude for the grant proposal. Your team using whatever LLM they prefer for docs, social posts, and email drafts.

Here's what's actually happening:

Every AI interaction starts from zero—you spend 15-30 minutes rebuilding context that should be persistent. Different team members prompt differently, producing inconsistent brand voice. AI grabs forbidden language patterns from its training data: generic hype for your differentiated positioning, marketing fluff for your technical docs, savior language for your community-centered work.

You catch the problems reactively. "That doesn't sound like us." "We would never say it that way." "This contradicts our pitch deck." Five revision rounds later, you've spent more time fixing AI outputs than you saved using AI in the first place.

Meanwhile:

• Your founder's LinkedIn voice contradicts your institutional press releases
• Your developer docs are filled with "powerful solutions" language that makes engineers not trust you
• Your fundraising pitch decks, one-pagers, data room, website, etc and are misaligned confusing investors or donors
• Your grant proposals use different language than your impact reports
• Every new contractor takes three months to "learn how we sound"
• Every piece is custom instead of systematically generated

This isn't a prompt engineering problem. It's a systems architecture problem.

Why "Just Use AI Better" Doesn't Work

AI tools have no persistent memory of your organizational positioning, voice logic, or validation frameworks. Every interaction starts from zero. LLMs trained on millions of generic startup documents will make you sound generic unless you give them explicit system constraints.

Without those constraints:

• Claude writes your deck and makes you sound corporate when you're community-centered
• ChatGPT fills your technical docs with marketing bullshit
• Your AI-generated content violates your positioning because it doesn't know what language patterns you actively avoid
• Different team members get wildly different outputs from the same prompts
• Quality control stays reactive ("I don't like this") instead of systematic ("does this pass validation?")

You don't need better prompts. You need a communications operating system.

What CommsOS Actually Is

Like an operating system for your computer, CommsOS is the infrastructure layer that makes everything else work consistently.

It's not brand guidelines (subjective aesthetics that sit unused in Google Drive).
It's not content templates (static artifacts that become outdated).
It's executable specifications that answer three core questions:

1. VOICE LOGIC: When should different voices write? Decision trees with explicit override rules. Testable logic, not preferences.

2. POSITIONING CONSTRAINTS: What language violates differentiation? Pattern matching libraries. Forbidden language inventories. Brand archetype conflicts documented.

3. VALIDATION FRAMEWORKS: What claims require what proof? Evidence standards, not subjective quality. Proof point inventories. Capability boundaries.

What Changes With CommsOS

Before CommsOS:

• 15-30 minutes rebuilding context every AI interaction
• Generic outputs requiring complete rewrites
• 5+ revision rounds per piece
• Different team members producing inconsistent brand or organizational voice
• Contractors taking months to onboard
• Strategic positioning lost in tactical execution

After CommsOS:

• Load system into AI context once, use consistently
• On-brand outputs from first draft
• 1-2 revision rounds (for substance, not voice)
• Consistent organization voice across all team members and tools
• Contractors productive in days, not months
• Strategic positioning maintained systematically

Actual outcomes:

• Bast AI using CommsOS for $3M seed round communications
• The Human Layer using CommsOS for podcast production and knowledge garden maintenance
• JournoDAO using CommsOS for merging two legacy DAOs into a non-profit structure

CommsOS is infrastructure, not content production. I don't write your stuff—I build the system that ensures your stuff (and your team's stuff, and your AI's stuff) sounds coherent.

Who This Serves

You need CommsOS if:

• Small team (3-15 people) producing large-team content volume
• Already using AI tools—just getting inconsistent outputs
• Technical complexity requiring precision, not marketing fluff
• At inflection point: fundraising, team growth, market positioning shift
• Can't afford months for contractors to "learn how we sound"
• Impact narratives are your competitive advantage
• Mission-driven: nonprofit, B Corp, DAO, ethical emergent tech startups

You don't need CommsOS if:

• Content volume is low and founder writes everything personally
• Brand consistency doesn't matter to your stakeholders
• You have full-time communications team with bandwidth to spare
• Traditional agency model works for your budget and timeline

How CommsOS Works: Three Questions, Eight Components

Voice Logic: When should different voices write?

• Company Overview: Canonical reference for what you are, what you do, why it matters
• Voice Extraction: How you actually sound when you're being yourselves
• Brand Voice Definition: Decision trees for when founder voice vs. institutional voice vs. technical voice writes

Positioning Constraints: What language violates differentiation?

• Audience Mapping: Who you serve, what they need, how they think
• Proof Points Inventory: Evidence organized for retrieval, not buried in past decks
• Forbidden Patterns: What you actively avoid (competitor language, industry clichés, archetype conflicts)

Validation Frameworks: What claims require what proof?

• Quality Checklists: How to evaluate whether communications work
• System Instructions: How to use this infrastructure with AI tools

Service Structure

CommsOS Build: 2-3 Week Implementation

What you get: Functioning CommsOS ready to load into AI tools, not theoretical framework.

Timeline: 2 weeks of working sessions—voice extraction workshops, system documentation in markdown, prompt libraries for Claude/ChatGPT/other LLMs, training on how to use the system.

Deliverables:

• 8-component knowledge base (company overview, voice extraction, organization voice, audience mapping, proof points, forbidden patterns, quality checklists, system instructions)
• Prompt system + libraries and loading instructions for your AI tools
• System architecture documented in markdown (portable across any AI tool, best used in Obsidian)
• Team training on implementation - 2 working sessions

Outcome: Your team can immediately use AI tools more effectively, contractors onboard faster, quality baseline rises across all communications.

Investment: $5,000
Beta pricing: $1,500 through March 30, 2026 for methodology refinement partners. Beta participants get the full infrastructure plus you help shape how this work evolves.

Capacity: 2-3 implementations quarterly

Fractional Advisory: System Evolution

What you get: Strategic guidance (10 hours/month) + implementation support as infrastructure evolves with your organization.

Focus:

• System evolution as organization grows
• Strategic communications advisory for inflection points
• Crisis communications support
• Implementation guidance for new use cases

Outcome: Infrastructure that evolves with organizational development, not static documentation that becomes outdated.

Investment: $3-5,000/month
Commitment: 3-month minimum engagement

Capacity: 2-3 concurrent advisory relationships maximum

Ready to see if I can help?

Why the Constraint?

2-3 clients maximum at any time.

This isn't artificial scarcity. This practice funds The Human Layer podcast and my creative work. More clients = diluted attention + compromised creative time. I protect both the quality of this work and the mission it serves.

Advisory practice, not agency scaling. No growth optimization. Just infrastructure that works—built by someone who's watched organizations collapse when they treat communications as cosmetic.

How to Work Together

This practice is intentionally small. 2-3 advisory clients maximum. No agency scaling. No growth optimization. Just systematic communications infrastructure that actually works—built by someone who's watched organizations collapse when they treat communications as cosmetic.

If you're ready to stop rebuilding context every AI interaction and start using your tools systematically:

Contact me for a quick 30 min sync to see if CommsOS can help your team

OR fill out this inquiry form and I'll reach out within 48 hours.

CommsOS Discovery + Support

$250/month (cancel anytime)

What You Get

Initial 60-minute diagnostic session: We figure out if CommsOS actually solves your problem. You get personalized gap analysis of where your communications break and clear recommendations on what to do about it.

Ongoing monthly access (if you stay subscribed):

• Monthly group office hours for implementation questions
• Async support between sessions
• Framework templates and documentation

Who This Serves

Curious referrals: Need to understand if this fits your problem before committing to full implementation.

Existing clients: Need a quick consult or focused support outside your advisory retainer.

The Path

Subscribe for one month, get diagnostic session. After that:

• Cancel if it's not a fit
• Stay subscribed for ongoing support while you self-implement
• Book full CommsOS Build ($250 credit per month subscribed, max $500)

Capacity

3-4 diagnostic sessions per month. Group office hours accommodate 8-10 participants.