Four days. €2,000/day. We sit with your team, build 2–3 prototype workflows they can run on their own accounts, transfer the methodology, and hand IT a one-page spec for when they want to scale.
We're not your IT department. We won't pretend to ship into your corporate Salesforce in 4 days. What we deliver is *capability for the team* and *clarity for IT*.
But AI tooling changes weekly. Copilot got deployed and stalled. Vendor AI doesn't fit your workflow. Junior staff take six months to ramp on what the seniors carry in their heads. And the team that should be amplified is spending 40–60% of its time on workflows AI could handle ; if anyone knew how to wire it up *without* waiting on IT.
The people who know the customer best spend their days on repeatable workflows. AI can handle the repeat. They should be on judgment.
94% of Microsoft Copilot pilots fail to reach broad deployment (Gartner). Seats are paid for. Value isn't realised. The gap is methodology and team enablement, not licensing.
Last month it was Copilot. This month it's agents. Next month it's something else. Your team can't keep retooling around vendor cycles. They need substrate-independent methodology.
You want to try AI on a workflow. IT wants security review, data schema mapping, integration tickets. Six months later you're still scoping. The team needs to *prototype* now and hand IT a clear spec when they're ready to scale.
Domain knowledge is implicit. Workflows live in senior heads. We help you turn that implicit knowledge into workflows juniors can run on day one.
Every other AI engagement ends with you needing them again next quarter. Ours ends with your team running the playbook themselves. By design.
We don't lecture. We build alongside the people who know the work. The methodology is taught by doing.
Prototypes run on accessible tooling the team can actually access; personal Claude Pro or ChatGPT Plus accounts, n8n self-hosted, local Python; not your corporate prod stack. When you want to scale into prod, we hand you the spec for IT.
We sit with the team and run the dialectic on their actual workflows. Where does AI amplify? Where would it fail? The team learns the discipline by watching it applied to work they know intimately.
First prototype goes live on accessible tooling; personal Claude Pro / ChatGPT Plus, n8n, local Python. The team builds, we coach. No admin rights needed.
Prototypes two and three. Now the team is leading. We're catching failure modes with the dialectic. By end of day they're running it without us watching.
Methodology playbook is in the team's hands. Prototypes run on their accounts. We write a one-page production spec the team can hand IT when they're ready to scale. 30-day check-in scheduled. We walk out.
Side effect: the workflows the team prototypes are audit-ready by construction; every claim tagged by confidence, every decision traceable, every output reviewable. That's how the methodology runs. We don't sell it as the headline. It's just what happens.
The same methodology that caught a 1000× arithmetic error in our DeFi consulting work (RAAC, May 2026) before it shipped externally. Substrate-independent ; it ports across domains. After the Sprint, your team runs it on every AI workflow they build.
Construct the workflow. What it should do. How it ships.
Hit it at full strength. Where does the AI hallucinate, drift, or fail silently?
Map the network. What tools, data sources, and decision points the workflow touches.
Flip the assumption. What would the workflow look like if our starting frame is wrong?
Independent verification. Every load-bearing claim tagged by confidence level before output ships.
No premium-boutique anchoring, no opaque package pricing. Day rate, on the box, the same rate whether it's a Sprint or a retainer day.
Most engagements start with the Sprint and stop there. The Fractional CAIO is for teams that want monthly methodology supervision while they continue building. Coming in Year 2: a 12-week Graduate Cohort program for operators who want cross-functional AI talent at the ground floor.
7-agent verification pass + audit step corrected a published $27M protocol-owned-liquidity claim to $632K before it shipped externally. The methodology catches what consensus would smuggle through.
After we shipped a curator one-pager built through the four-lens dialectic with a synthesis that carried real contradictions onto the cover page instead of averaging them out. Calls ongoing.
877-line Builder report on calibration intelligence positioning. The discipline survived three iterations. It survives because it's about how teams think, not what they think about.
Every month you wait, the gap between what your seniors carry and what the AI can amplify widens. The team that learns the methodology this quarter ships better than the team that buys a fifth vendor next quarter.
We're at the Mediterranean Conference Centre 27–28 May. Bring a task your team does every week. We'll show you what we'd ship in 4 days, what your team would own after, and what the spec for IT would look like ; in five minutes, on paper.