29 years in enterprise tech, from telephony and VoIP through collaboration platforms, and into AI since 2018: LLM infrastructure, and now autonomous agents. Founder of one company, founding member of another, and the engineer behind the speech tech acquired by Cisco. Platforms shipped to global scale: 30M+ agent-driven summaries, LLM infrastructure at a 50B-tokens-per-month run rate. I sense where the market turns, name the category before it forms, and ship the product that arrives on time.
Today: one agent, one user, one task. Next: multi-agent systems that run cross-functional workflows end to end, with humans owning the judgment calls at explicit gates.
The winner won't have the best model; everyone rents the same models. The winner will own the org context layer: who owns what, who depends on whom, what was decided and why.
Enterprises don't buy autonomy; they buy governed autonomy. Audit trails, human gates, adversarial testing, and compliance readiness are what turn demos into deployments.
Every role, the outcome it shipped. No status without an outcome.
The failures are where the real learning compiled. Logged honestly, in the system's own words.
Not a skills list. A graph where each capability makes the others stronger.
A repeatable process, not a heroic sprint. This is how the loop actually runs.
Two paths, depending on what you're building.
The wedge into operational calling: an agent that beats the phone tree and builds a counterparty graph. Live working demo plus the applied founding-CPO thesis.
open → for any companyThe organizational concepts for the agentic era: the context graph, the sense-predict-act loop, and governed execution, as animated concept mocks.
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