A half-day intensive for executives and senior leaders. Stop guessing on AI bets — leave with a clear strategy, a platform roadmap, and the frameworks to keep making the right calls.
The gap isn't technical talent — it's strategic clarity. Leaders approve AI budgets without a platform thesis. They buy vendor tools that don't compose. They hire ML engineers before they have a data strategy. This workshop exists to close that gap.
Each module is a working session — not a lecture. You leave with something usable, not just notes.
Move beyond hype. Learn how to identify your highest-leverage AI opportunities, prioritize initiatives by business impact, and build a roadmap that actually ships.
Understand the real difference between bolting on AI features and building an AI platform. Learn what a production-grade AI stack looks like — without needing to be an engineer.
The three-way decision most organizations get wrong. A decision framework for when to use APIs, fine-tune your own models, or build proprietary systems — and what each costs in reality.
Define metrics that matter — not vanity benchmarks. Learn how to measure AI system performance, model drift, and business value in the language your board actually understands.
AI transformation fails at the people layer, not the tech layer. Assess your team's readiness, identify skill gaps, and design the org structure that sustains AI development long-term.
Cut through the sales noise. A structured process for evaluating AI vendors, LLM providers, and tooling — so you stop paying for capability you don't need and don't miss what you do.
Every session produces concrete artifacts your team can use the next day.
A written strategy capturing your top AI opportunities, prioritized initiatives, and 90-day next steps — ready to present to your board or leadership team.
A phased technical roadmap for your AI platform — with clear decision points, milestone definitions, and criteria for when to hire, embed, or scale back.
Reusable scorecards and decision trees for evaluating vendors, prioritizing AI bets, and making build-vs-buy calls — so you're not reinventing the process each time.
This isn't for individual contributors or engineers learning to code. It's for the people who set direction, allocate budget, and are accountable for AI outcomes.
The leaders who get AI right aren't the ones who understand transformers — they're the ones who've built a platform thesis, know where to draw the line between vendor and proprietary, and have an org that can actually execute. That's what this workshop teaches.
No. This workshop is for organizations that have already decided to invest in AI and need a clear strategy for doing it well. We skip the "what is AI" basics and go straight to decisions, tradeoffs, and implementation.
Private sessions are capped at 12 participants to ensure real discussion and working sessions, not passive listening. Cohort sessions run with up to 20 across organizations.
Both. Virtual sessions run on Zoom with interactive tools. In-person sessions are available in select cities or at your offices worldwide.
We send a pre-workshop brief (30 min) that captures your current AI initiatives, stack, and top strategic questions. This lets us tailor the session to your specific context.
We're builders, not slide-deck consultants. Every framework we teach is one we use when embedding into engineering teams. You get practitioner-tested approaches, not theoretical models.
Private sessions book 2–4 weeks out. Tell us a bit about your org and we'll find a format that fits your team.
We respond within 1 business day. No sales scripts.
