Thoughts on design, branding, and the creative process.
A vendor-neutral reference architecture for building governed, production-grade agentic systems: five capability layers, an A→B→C operating-model maturity path, a build-vs-buy decision rule, and the design principles that separate real transformation from AI theater.
A system for preventing drift in a growing agentic codebase
Jack Dorsey just cut Block's workforce in half — not because the business is struggling, but because Goose, their internal AI agent platform, made 6,000 people as productive as 10,000. Stock up 24%. Meanwhile, OpenClaw hit 234K GitHub stars in three months. TinyClaw recreated it in 400 lines of code. NullClaw runs on a 678KB binary. The developer community isn't debating whether multi-agent orchestration works anymore. The OpenClawification of the enterprise is coming. Every knowledge-work function — finance, legal, marketing, operations, HR — is built on workflows that can be decomposed into orchestrated, autonomous agent workloads. The companies that figure this out will operate like Block. The ones that don't will be forced into it reactively, on someone else's terms. I wrote about what it actually takes: the org redesign, the three-pillar governance framework, the technical architecture, and the ethical weight of what this means for millions of white-collar workers.
Every organization now building AI capabilities faces a version of this same question. Business units push for automation that eliminates human review. Clients ask for data usage that exceeds consent. Competitive pressure makes it tempting to move fast and defer the hard questions. The enterprises that will come out ahead are the ones that establish their AI use policy before the pressure arrives — not during a crisis negotiation with a powerful counterparty. The lesson for every AI strategy isn't complicated: know your line before someone tests it.
Why the “SaaS will be fine” argument misses the magnitude of what’s happening — and what actually comes next.
Right now, I'm watching multi-month projects collapse into days. My teams are building ontologies on top of enterprise data that allow agents to reason, generate insights, and automate end-to-end workflows. The companies that thrive in this environment won't just buy software — they'll build it. In that world, today's SaaS platforms don't disappear overnight. But their center of gravity changes. And the speed of that shift may surprise people.