Most experts can't get AI to stay consistent past the first few sessions. I close that gap — turning deep expertise into systems AI can apply reliably, and directing the build so the work actually ships.
Start the ConversationThe Real Problem
Most AI-assisted projects fall apart in the same place: the gap between what a model outputs and what actually holds up in the real world. AI drifts. A banned color creeps back. Two documents quietly disagree. A recommendation looks right in a walkthrough and breaks on contact with reality.
The skill isn't prompting. It's discipline — setting non-negotiable rules, auditing every new file against them, closing the loop with real-world results, and building a system portable enough that the next session, or the next collaborator, can pick it up without re-explaining months of decisions from scratch.
That's the work I've been doing. That's what I bring.
This isn't a list of tools. It's a methodology — built from directing an AI collaboration from first principles to shipped product.
Deep, idiosyncratic knowledge doesn't help a build until it's structured into a system a model can apply consistently. I do that translation — researching a category in depth and organizing it into a reference an AI can pull from correctly, every time, instead of reinventing it each session.
Left alone, AI drifts. I set the non-negotiable rules, then audit every new output against them. Consistency across months of work doesn't happen by default — it happens because someone is checking, and catching regressions before they ship.
AI will recommend all day. I test those recommendations in the real world and feed the results back in. That gap — between output and what actually holds up outside the chat — is where most AI-built products fall apart. It's the part I don't skip.
Every AI session starts cold. I build handoff systems — machine-readable briefs and human-readable ones — so a new session or a new collaborator can pick up the build in progress without re-explaining months of decisions from scratch.
Every decision gets judged the way a real user would actually encounter it — not the way it looks in a polished walkthrough. That discipline is the difference between a build that impresses in a meeting and one that performs in the field.
AI needs the same discipline a human team would: clear rules, real quality control, and someone willing to make the calls it can't make on its own. I treat it that way — and the builds I direct reflect it.
CigarSeek is a consumer-facing cigar recommendation product built entirely through directed AI collaboration — brand identity, marketing knowledge base, UI design, copywriting, and deployment, all directed from first principles.
It required building a structured marketing knowledge base from academic sources, establishing and enforcing a complete brand system, directing the design and copy through multiple rounds of real-world testing, and deploying across a live website — all while maintaining consistency across months of sessions.
It's not a prototype. It's a live, working product. That's the standard I hold myself to, and the standard I bring to every engagement.
See CigarSeek →A consumer discovery product that translates personal taste into precise cigar recommendations — built end-to-end through directed AI collaboration.
"If you've got deep expertise but no idea how to turn it into something buildable — or you're already using AI but can't get it to stay consistent past the first few sessions — that's the gap I work in."— Randy Polito, Founder · Volume 2 Consulting
AI Strategy & Direction is right for you if any of these sound familiar.
You know your domain cold but don't know how to structure that knowledge so AI can actually use it consistently. You need someone to do that translation and direct the build.
Your outputs look different every session. Rules you set get forgotten. Two documents quietly disagree. You need a system and someone to enforce it.
You've seen polished walkthroughs that break on contact with reality. You need someone who tests in the real world, closes the loop, and doesn't call it done until it actually works.
You're not looking for a list of tricks. You want a repeatable, portable process that works across sessions, collaborators, and projects — and someone who's already built one.
Let's talk about where you are, where you want to go, and whether AI Strategy & Direction is the right fit.
Work With Me