Building defensible moats by turning products into platforms — and platforms into ecosystems.
Models commoditize. Context compounds.
Durable advantage is rarely built from features. It is built from the architecture around them — APIs that embed, developers who adopt, data that compounds, ecosystems that refuse to unravel.
This has been the through-line of my work across Adobe, Okta, and Radiant Logic, and the focus of my doctoral research in innovation management: turning technically strong platforms into category-defining assets.
The Series
Four chapters, four operating contexts, one through-line: durable advantage comes from turning products into platforms, platforms into ecosystems, and ecosystems into compounding systems of context, trust, and execution.
Start from the beginning ↓At Adobe, I helped shape API strategy to make products more extensible, more embedded, and harder to displace. The moat was not the API surface itself; it was the ecosystem of workflows, partners, and integrations that formed around it. This integration layer became the strategic engine for M&A — enabling platform-level integration across Adobe's acquisition-driven cloud transformation, including Marketo, Magento, Workfront, Frame.io, and others.
At Okta, I helped define developer platform strategy to turn identity from an administrative function into an adoption motion. A developer platform creates leverage when builders choose it, extend it, and carry it into the enterprise.
During COVID, while leading product and technology at Radiant Logic, I started a parallel build: a doctorate focused on how firms create and capture value in open innovation ecosystems.
The core question: why do some firms in open ecosystems capture disproportionate value while others capture almost none? The answer — durable advantage accrues to the firms that architect the context, coordination, and trust layers others depend on — is the theory that now underwrites every chapter on this page.
Models commoditize. Context compounds. At Radiant Logic, the moat is the context layer itself. Every AI system is only as good as the context it runs on. For identity and security, that context is fragmented across dozens of sources — directories, IAM platforms, HR systems, device inventories, access logs. The moat isn't any single source; it's the unified identity data layer that makes all of them addressable in real time. At Radiant Logic, we built that layer. It's what turns generic AI into agentic security AI — because the context is already resolved, unified, and query-able. Data is the moat. Multiplayer AI is what you build on it.
In numbers: Joined as CPTO at $40M ARR. Took over as CEO at $50M. Led the company's transformation to $100M. Today, Radiant Logic serves 200 of the Fortune 500.
Identity is where the AI data moat gets built first. It will not be where it gets built last.
Research on how firms create and capture value from open innovation ecosystems, knowledge flows, and intangible assets.
A model for identity security where AI amplifies human expertise, coordinates fragmented tools and teams, and turns identity context into action.