Veterans + AI Playbook

The Plan: April 16-30

You've got a strong thesis, a real network, and a window right now where the right moves compound. Three tracks running in parallel. All three matter. None of them wait on anyone.

Track 1: Learn the Landscape

Today proved you can build rapport and hold a room. Justin said the coffee was "critical." That's your strength. The next step is pairing that presence with the depth to walk someone through the thesis cold, on your feet, in your own words.

Start with these three sections from this page:

1. Read The Thesis. The hypothesis in one page. Internalize this first.
2. Read The Market. 23 competitors mapped. Nobody owns the upper-right quadrant. 12-18 month window.
3. Read The Business Model. How the consultancy flywheel works. Employer pain tiers. Veteran-to-role matching.

Then go deeper:

4. Read Oregon Landscape. WorkSource, state funding, local orgs, employer list.
5. Read Curriculum Model. Why Alpha School's 2.3x model matters. LearnAIR's gaps. What we build on top.
6. Ref Conversation Scripts. Pull these up before any employer, VSO, or veteran conversation.
7. Ref Target Contacts. Five named Oregon employers with decision-maker profiles.

By end of week 2, the bar is: someone asks you "why veterans and AI, and what have you found?" and you give a 5-minute answer that hits the competitive gap, the funding landscape, the employer demand, and your network advantage. Your words, your conviction.

What from this list do you already feel strongest on? That's where you spend the least time. Go deep on the gaps.

Track 2: Have Conversations and Find Warm Leads

Your Rolodex is real. You've named Honor Foundation, BreakLine, Deloitte Veterans, BetterUp, Mission 22. Those aren't cold leads. Those are people who know you or are one degree away.

Two purposes here. First, these conversations sharpen the thesis. You learn what they're seeing, what's working, what's not. Second, some of these lead somewhere: a partnership, a role, a paid engagement. Both outcomes are good.

Next week: two more conversations, plus start the job search.

Put feelers out for roles. Your background (Marine officer, Deloitte consulting, therapy/coaching, Forest Service) positions you for:

• Veteran workforce program roles. Program management at orgs like Hire Heroes USA, American Corporate Partners, or similar.
• Defense/gov consulting. Your clearance background + consulting experience.
• Ed-tech / workforce development. Program leads at companies building AI training.
• Health/wellness coaching. Leveraging your therapy and holotropic background.

LinkedIn, your network, direct outreach. The goal isn't to land something in two weeks. The goal is to have motion so you're not waiting by the phone.

These conversations are yours regardless of what happens with LearnAIR. If they say yes, you walk in with fresh network intel and external validation. If they say no or stall, you already have momentum.

Which two from your network feel like the most natural first calls? Go with your gut there.

Track 3: Push the Thesis Forward

LearnAIR is one vehicle for the veterans + AI thesis. It might be the right one. It might not. Either way, the thesis gets sharper by working it.

By end of week 2, the bar is: you've talked to at least one person at WorkSource or Mission 22, you've floated the idea to someone in your F3 network, and you've built or walked through at least one agent workflow yourself.

Where LearnAIR Fits

LearnAIR is on standby until next week. Here's the honest picture:

• Justin is warm, curious, and wants to move. He's also gated on bank paperwork (SBA loan), Teresa hasn't read the email, and the rest of the team doesn't know about the veteran pivot yet. Multiple things need to line up on their side before this moves.
• The do-or-die disclosure from this morning is real. They need profit before Q4. That's urgency, and it's worth understanding what that means for how they'd resource this vertical. A startup investing in a new bet feels different than a startup that needs this bet to survive.
• Justin sees you in a leadership role. That's genuine and it's earned. The question worth sitting with: does the current structure (contractor, no equity, no W2) match the role he's describing? If you're leading, what does leading actually look like inside their model?
• Decision comes next week. If yes, you walk in stronger because you've been moving on all three tracks. If no or more delay, you already have momentum and you're not starting from zero.

The Week at a Glance

April 16-18: Start here, one per track

Then build from there:

April 21-25 (next week)

You have a strong thesis, a real network, and three months to make something happen. The worst thing you can do right now is wait. The best thing you can do is be in motion on all three tracks so that when the next conversation happens, whether it's with Justin, with Honor Foundation, or with a hiring manager, you're not presenting a deck. You're telling them what you've already started doing.

What feels like the highest energy move for you right now? Start there.

Stay moving.

The Thesis

Strategic clarity. Read this first.

The One Proof Point

3 employer discovery conversations. The question isn't "would you hire an AI operations supervisor?" It's:

1. Where are you at with AI adoption?
2. What's working, what's not?
3. Where's the gap between what your team can do and what you need them to do?
4. If that gap had a name, what would you call it?
5. What would it be worth to close it?

If three different employers describe a problem that sounds like "my people are using AI but nobody's governing the outputs," we've validated demand. If they describe something different, the thesis adapts.

The Consultancy Framing

We are not employees. We are not volunteers. We are a consultancy that owns its IP.

• Protects the IP already built
• Two-way doors with partners instead of one-way doors (employment)
• Allows taking the same IP to other partners (Deloitte, BreakLine, direct to employers)
• De-risks relationships while still in discovery
• Positions as partners, not hires

Key People + Competencies

What the Program Needs That's Still Weak

• Sales. The biggest gap. The employer discovery calls are the first reps.
• Curriculum delivery. Can design it. Who teaches it? The natural candidate is the person who ramps on AI fastest.
• Veteran recruiting. Who finds the first cohort? Easter Seals HVRP connection and BreakLine network are the two leads.

The Market

23 competitors mapped. The gap is real. The window is 12-18 months.

Competitor Landscape (Key Players)

Positioning Matrix

Two axes: veteran-specificity (horizontal) and AI depth (vertical).

• Lower-right (saturated): Veteran career services, minimal AI content. Well-funded nonprofits.
• Left column (dominated): Deep AI training, generic audience. Tech giants with free/cheap certs.
• Upper-right (EMPTY): Deep AI workflow supervision, veteran-specific. This is the flag to plant.

Competitive Risks

Target Contacts: First 5 Employers

Real people at real companies. The contact phase starts here.

Conversation Scripts

Three scripts for three audiences. 25-35 minutes each. Signal extraction, not selling.

Oregon Landscape

Veterans, AI, employers, and funding in your backyard.

Top Findings

1. Oregon-NVIDIA $10M AI Partnership. Signed April 2025 by Gov. Kotek + Jensen Huang. AI Ambassador Program on campuses. An AI operations supervisor program aligns directly with the state's stated AI workforce priority.
2. East Cascades Works is the local workforce board. WIOA-designated entity for Bend/Deschutes County (10 counties). The right partner for federal workforce funding. HQ in Bend.
3. Health Elements AI is in Bend. AI-powered clinical data abstraction. Real AI company, BVC finalist. A concrete local employer for the "would you hire an AI-skilled veteran?" conversation.
4. Prineville data centers are 35 min from Bend. Meta (3.2M sq ft, $2B+) + Apple (3.2M sq ft). ~300 permanent jobs. Infrastructure jobs that need supervision.
5. COCC already has veteran infrastructure. STRIVE Program (free 8-week veteran entrepreneurship, Syracuse IVMF partnership). Justin won STRIVE there. Neither COCC nor OSU-Cascades offers AI operations training. Gap.

Veteran-Serving Organizations (Central Oregon)

• COVO (Central Oregon Veterans Outreach): 200+ veterans/month. Bend.
• WorkSource Bend: Nationally recognized for veteran services (NASWA award). Priority of Service for veterans.
• 541VETS: Digital resource library for rural Oregon veterans.
• East Cascades Works: Local workforce board for Central Oregon. Bend HQ.
• Easterseals Oregon: HVRP across 8 cities. Contact: hvrpreferrals@or.easterseals.com

Key Stats

• ~266,000 veterans in Oregon. ~10,000-12,000 in Deschutes County.
• ~90,000 veterans statewide in the 35-55 age bracket (prime placement cohort).
• Central Oregon tech employment grew 50% since 2018 (142% over past decade).
• Milken Institute ranked Bend-Redmond top 6 Best Performing Small Cities (2024).
• No active-duty bases. Veteran population is Guard/Reserve + post-service relocators.

The Business Model

Employer pain tiers, the consultancy flywheel, and veteran-to-role matching.

The Core Problem

Individual workers bought ChatGPT and got 10x more productive at their tasks. But the organization didn't change its processes, workflows, approval chains, or quality controls. Now you have powerful individuals operating in an organizational vacuum. Someone needs to supervise the AI ecosystem. That's the AI Ecosystem Supervisor.

Employer Pain Tiers

The Consultancy Flywheel

1. LearnAIR (or similar) trains a company on ChatGPT Team
2. You do an AI Ecosystem Assessment
3. Build governance framework + workflows
4. Company realizes they need a full-time person to maintain it
5. Place a veteran as AI Ecosystem Supervisor
6. Provide 90-day transition support
7. Consulting transitions to quarterly retainer. Repeat at next company.

Every consulting engagement generates demand for a veteran placement. Every veteran placement demonstrates the model works, generating referrals for more consulting.

Engagement Pricing

Veteran-to-Employer Matching

The naming advantage: No one has standardized what to call this role. The program that names it owns the category. The military rank mapping gives employers an instant credibility signal.

The Curriculum Model

Why Alpha School's 2.3x model matters. LearnAIR's gaps. What gets built on top.

Alpha School: The Load-Bearing Insight

Alpha School puts students in the top 0.1% on standardized tests (97th-99th percentile MAP, 1535 average SAT) with ~2 hours of AI-personalized academics per day. The rest is project-based learning. Results: 2.3x-2.6x national average growth rate.

For adults, the case is even stronger:

• Better executive function. Adults can sustain focus without extensive motivation scaffolding.
• Prior knowledge. AI can diagnostic-test and skip what's already known.
• Intrinsic motivation. Career advancement, income, mission (especially veterans) replace gamification.
• Less time available. A compressed model isn't nice-to-have, it's the only viable model for working adults.

LearnAIR's Foundation Series: What's Good, What's Missing

LearnAIR's Foundation Series is 3 live sessions x 1.5 hours each. Groups of 5-20. It covers ChatGPT basics, interface, prompting (DIRECT framework), personas, Custom GPTs, and agent mode. It produces real results: "John completed 4-6 months of work in one week."

Eight Gaps

1. No organizational coordination layer. Everything is individual. Zero discussion of what happens when 50 people each build their own setup.
2. ChatGPT-only, platform-locked. No model-agnostic thinking. No Claude, Gemini, or open-source.
3. No file system / version control. No git, no version history.
4. No CLI / terminal exposure. Everything is GUI.
5. No security / governance depth. Privacy toggles, but no output review workflows or approval chains.
6. No workforce transition framework. A skills course, not a transition program.
7. No measurement / outcomes. No framework for measuring ROI.
8. Troubleshooting is reactive, not systemic. Hallucinations treated as bugs, not architectural realities.

What We Build On Top

The Proposed Structure

Compress instruction. Expand practice. Never remove the guide.

Based on Alpha's architecture, applied to a veteran learning AI supervision:

After the 2-hour instruction block: hands-on practice with a guide present. Ratio: 1:2 or 1:3. For every hour of AI-delivered instruction, 2-3 hours of supervised practice. This maps to the 70-20-10 model: 70% experiential, 20% social, 10% formal.