Rod Amora

Co-founder, CTO & CAIO at Berry

How AI-native delivery changes the way a service firm actually runs.

I am Rod Amora, co-founder, CTO, and Chief AI Officer at Berry. I write about AI for service businesses: how firms rebuild delivery around it, what works in production, what fails, and how the firm changes when the model sticks.

My focus is service businesses with $1M to $20M in revenue. I study capacity, cost to deliver, and how firms grow revenue without matching headcount.

Proof points

4,000+ businesses
observed through delivery data
150+ franchise units
and growing
Since 2017
working with service businesses

Latest writing

  • 12 min read Updated

    AI Enablement Is a Loop, Not a Roadmap

    Every definition of AI enablement on page one of Google ends at "ready." Mine ends when a number in the business moves. We spent over 200 billion tokens on prototypes that went nowhere before one stuck, and that is the loop, not a roadmap you buy.

  • 12 min read Updated

    AI-Native Without Starting Over

    Somewhere in your firm there is an AI tool somebody quietly stopped using, and nobody told you. That is where AI adoption breaks, not in your legacy processes. Existing firms do go AI-native: real training, cheaper models under $500 a month, and somebody paying for the failed first tries.

  • 6 min read Updated

    You can afford more agents. You can't afford to watch them.

    I lost my thread four times a day while juggling more than ten tasks. Here is what working-memory and supervisory-control research explains, what it cannot, and the thread cap I am testing.

Go to the writing archive

Three questions I keep answering.

  1. AI applied to service businesses

    Where AI belongs in consulting, agencies, and professional services. Where it is vanity.

  2. AI-first service businesses

    How roles, stack, and economics change when delivery becomes AI-native.

  3. Operational reality of AI in service businesses

    What breaks between demo and production: cost, systems, failure, and when to skip AI.

Proofwork: six frameworks and tools for AI-native delivery.

The system behind the writing, built on one idea: AI only counts when you can prove it: in the work, and in the P&L. Where a firm sits. What to measure. Why implementations stall. A diagnostic that places your firm on the Ladder. A calculator that walks task-level gains through the leaks before they reach the P&L. And one that prices a finished piece of work rather than a token.

  1. The Delivery Model Ladder

    See how your firm delivers work today, from people using AI on isolated tasks to AI built into the delivery model. Your stage is based on how work runs, not which tools you bought.

  2. The Four Numbers

    Track the four numbers that show whether AI changed the business: cost to acquire, cost to deliver, retention, and price. Hours saved only matter when they move one of them.

  3. The Production Gap

    Find where an AI project gets stuck between a working demo and daily delivery. Each of the eleven failure modes includes an early warning sign and a practical next move.

  4. The AI Readiness Assessment

    Answer sixteen questions to place your firm on the Delivery Model Ladder. You get a short list of next moves based on how your work runs today.

  5. AI ROI Calculator for Service Firms

    Estimate how much AI may change delivery capacity, then see how review, approval, freed time, pricing, and firm knowledge affect what reaches the business.

  6. AI Token Cost Calculator

    Work out what your AI tokens cost at current model prices, then add the retries, the review, and the correction, because the number that decides anything is what one accepted task costs you.

Rod Amora

I am co-founder, CTO, and Chief AI Officer at Berry. Since 2017, I have watched hundreds of service firms adopt AI through a franchise network's delivery data spanning 4,000+ businesses and 150+ franchise units and growing. The About page holds the longer record of my work, books, and sources.

Read the full About page

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