Test & Control · AI Force Multiplication · Huntsville, AL
How this actually works.
No discovery phase, no transformation roadmap, no six-week ramp. Here is what two
weeks looks like, hour by hour, and what I need from you to do it.
A Workflow Teardown, day by day
Days 1–2 · Find the hours
Three conversations, forty-five minutes each, with the people who actually perform
the work — not their managers. I ask where the time goes, what breaks, and what
you'd be embarrassed to show me. That last question finds it every time.
Days 3–4 · Price it
I map the workflow and put a dollar figure on it at your wrap rate. Often this is
where the conversation changes, because nobody had added it up before.
Days 5–8 · Build
I build a working automation against your real process. Not a mockup, not a demo
environment — the actual thing, running on your inputs.
Days 9–10 · Hand it over
You get the running system, the source, a written map of the workflow, and an
honest account of what it does badly. Then you decide whether there's a second
conversation.
What I need from you
- Three to four hours total from the two or three people who do the work
- Access to a representative sample of the real inputs — sanitized is fine
- One person empowered to say "yes, that output is acceptable"
- Somewhere to put the result: a shared drive, a repo, a VM. Your call.
Where your data goes
You are wondering about this and you may be too polite to ask. So here it is
unprompted, because in this town it is the question that actually matters.
The default posture
I assume your data is sensitive until you tell me otherwise. Teardowns run on
sanitized or synthetic inputs by default — in my experience the exercise almost
never requires real controlled data to prove the workflow.
CUI and export-controlled work
Controlled Unclassified Information does not go into a commercial model endpoint,
on my engagements or anyone else's. If your workflow touches CUI or ITAR-controlled
technical data, we scope it one of three ways: run against sanitized inputs, run
inside your accredited boundary on your infrastructure, or don't build it yet. I
will tell you plainly which one applies, and I will tell you when the honest answer
is the third.
CMMC and your existing controls
Anything I build has to live inside the control set you already have to satisfy. If
a tool would create a new CMMC finding, that is a reason not to use the tool — not a
problem to be documented around later. If you don't yet have a written rule for
what your engineers may paste into an AI tool, that is its own engagement, and it is
usually the one to do first.
Shadow AI
Whatever your policy says, some of your engineers are already using these tools on
their phones. I would rather help you find out where and put a real boundary around
it than pretend the exposure starts the day you hire someone.
"You're one guy."
Correct, and it's the point. The person who scopes it is the person who builds it —
there's no bench to feed and no junior consultant learning on your budget.
Nothing is lost in a handoff between the person who understood the problem and the
person writing the code.
The real version of this objection is "what happens when you're gone," and it's
fair. That's why every engagement ships source and documentation you own outright,
and why Capability Transfer exists: at some point
the correct outcome is that your team doesn't need me.
Still have questions?
Ask them directly. I'd rather answer than have you guess.
Get in touch