Implementation

Find the bet worth making. Build the thing that makes it. Or hand you the plan.

Most AI consulting jumps straight to 'let's build a chatbot.' I don't. The biggest leverage usually shows up two questions earlier — what should we be building, and have we proven it works?

The method

Frame & Coach → Build & Teach → Read the Signal → Scale or Kill.

Every step is half work, half coaching. The leader and their team learn the frameworks and tools as we build — so when the engagement ends, the muscle stays.

Frame & Coach

Week 1. We map your business, your stack, your data — and write an opinionated thesis with two or three candidate bets. You learn the frameworks while we write it. Coaching starts here, not later.

Build & Teach

Weeks 2–3. Real code, real prompts, real configs — not slideware. You learn the tools while we ship: prompts, context, agents, harnesses. Cost of building has collapsed; we use that, and you learn how.

Read the Signal

Week 4. Real users, real data. You learn to tell AI signal from noise. We size validation to risk — not to bill more hours.

Scale or Kill

Week 5+. Three paths: build it together, hand off a plan your team owns, or kill it and bank the savings. By now you can make the next call without me in the room. That's the point.

Why this method

Cost of building has collapsed.

A working AI prototype that took a team a quarter in 2023 takes a builder a week now. So we don't validate before building — we build to validate. Faster, cheaper, more honest.

Sovereignty by default.

Every artifact — code, prompts, library, configs, infra — lives in a repo you own. Vanilla tools (Claude Code, GitHub, your cloud) so you can swap models, harnesses, or vendors as the market evolves.

The exit is the offer.

I don't optimize for retainer expansion. The cleanest engagement is one that ends with you running.

What you get

→ Written thesis document, branded with your context
→ Working prototype in a repo your team can poke at
→ Validation report with quantitative signal where possible
→ Scale plan: cost, time, team needs, vendor recommendations, build vs. buy
→ Decision log

Pricing

Thesis Sprint

$7,500–$18,000 fixed

Scope set on intro call.

Build & Hand-off

Scoped after Sprint

Typical engagements run $25,000–$95,000.

Plan-only hand-off

$0 additional

Included in Sprint deliverables. Your team builds, I'm available for spot consulting.

All deliverables are yours to keep. I bring the muscle. You keep the artifact.

Start with a Thesis Sprint.

Two weeks, fixed price, real artifact. By the end you'll know what to build, what to skip, and whether to use me to ship it.

Talk about a Sprint →