Snowball Sprint
From idea to AI POC your customers actually want to buy. In weeks, not months.
For leaders who are ready to build AI that their customers want to buy.
If your organization:
Wants a validated POC before spending millions
Needs to escape POC hell and pick the right use case
Requires clear ROI and data readiness modeling
Is ready to move with urgency
If your team is hearing "Show me AI works" — this is the answer.
How it Works
The Sprint includes the 3-Day AI Strategy Workshop → plus 2-12 weeks of rapid iteration—rolling 1-2 of your top initiatives forward from validated strategy to customer-tested POC.
Week 1 — Workshop: Ideate + Frame
We align on strategy, select the highest-value use case, validate data readiness, and create your AI roadmap.
(Details on Workshop page →)
Weeks 2-3+ — Iterate + Launch
Create the initial AI-driven RAG-enabled POC in Python.
Across 6-8 customer sessions, we:
Test the prototype with your customers
Identify what works, what fails, and what's missing
Rapidly iterate and improve the POC in code
Validate data flows, prompts, agent logic, and UI
Document "When can I buy this?" signals
Each iteration adds functionality, features, and momentum—the snowball grows as it rolls down the hill.
By the end, you have a proven POC, a clear go/no-go decision, and a roadmap grounded in customer evidence—not hope.
What You’ll Get
“I want to buy this. How much is it?” enthusiasm from your customers.
Typical deliverables:
Everything you get from the AI Strategy Workshop PLUS:
Fully functional AI POC in Python using your real data
Clear Go / No-Go recommendation
Complete source code, documentation, and agent architecture diagrams
2-3 Build → Test → Iterate cycles
6-8 customer validation sessions (with recordings)
Executive-ready "What We Learned" summary with “Strategic Next Steps.”
60 days of async support
Everything is designed to prevent the 85% AI failure rate by actively iterating on the initial design until we create the AI solution your customers want to buy.
Investment
$95,000 - $450,000
Timeline: 2-12 weeks
Depending on scope, number of POCs, and how much your internal team gets involved in building, designing, and user-testing.
Training Add-On (Highly Recommended)
“I want to buy this. How much is it?” enthusiasm from your customers.
While we're running the Sprint, it makes sense to train your team—so you're not dependent on me for every future initiative.
Unlike the McKinseys of the world, my business model isn't execution dependency.
It's long-term strategic partnership →
A Snowball Sprint is an excellent opportunity for hands-on training and can be included with little or no additional cost.
"Greg doesn't just talk about innovation—he gets his hands dirty to make it happen. He shepherded the first production-ready POC with multiple agents and laid the foundation for Sumo's AI direction. If you get the chance to work with Greg, take it."
— Brandon Borodach
Field CTO, Abstract Security
"Greg can transform a simple idea into a state-of-the-art experience. Greg's laser focus on users and letting them decide good from bad differentiates him... His in-depth understanding of technology stacks positions him into the most needed leadership space between designers and developers."
— Tejaswi Redkar
CEO & Founder (former Cisco, AppDynamics, Sumo)
"Greg consistently pushes boundaries—not just in design, but in validating AI product-market fit directly with customers to ensure every feature solved a real-world problem. I'd work with him again in a heartbeat."
— Catherine Davis
VP Product Management, Addigy
"Greg consistently works to advance practical, customer-focused solutions. His work on RAG file creation significantly improved the quality of multi-agent responses, making our AI-powered tools more reliable and useful for end users."
— Steve Berube
Technology Leader, Sumo Logic
Let’s Talk
In 30 minutes, we’ll talk through your AI challenges and see whether Snowball Sprint is the right fit. No pitch — just an honest conversation… and I’ll share a few insights, whether or not we end up working together.