Short, dated takes on what I am shipping and how I think about evidence-readiness for AI agents. Newest first. Full write-ups live in the case studies — this is the running log.
Published an ai-catalog.json following Agentic Resource Discovery (Google + Linux Foundation, Apache-2.0) — a machine-readable menu so agents and registries can find my live A2A agents and MCP server by capability, before invoking them. Adoption is near zero today; like OKF, it is an early bet that fits a site already built for agent discovery.
Google Cloud published the Open Knowledge Format (v0.1, June 2026) — vendor-neutral markdown with YAML frontmatter that an agent reads without scraping HTML. My profile, case studies, and role snapshots are now generated into an OKF bundle at /okf/. Nothing reads OKF yet; it is an early bet that matches what this site already is — a reference implementation, not a template.
A running log of short, dated, evidence-first takes on what I am shipping and how I reason about evidence-readiness for AI agents. The long-form proof stays in the case studies; this is the in-between.
It matches a counterparty name against a fresh public-list snapshot (OFAC / EU / UK) at request time, at no cost. It is a possible-match string check for triage — not a sanctions determination, and human review is still required. See the demo.
Strategic-risk triage, Middle Corridor deal risk, Kazakhstan market entry, CIS secondary-sanctions, agentic-interaction trust, and Gulf maritime exposure — sibling deployments to the four open-source skill repos. Portfolio-grade, illustrative usage; full analysis runs through the installable Agenda Intelligence MD MCP package.
Human pages plus JSON endpoints, agent discovery, and an MCP server — so an LLM or agent can read the profile as structured data, not scraped prose. The content is personal; the architecture is the part worth copying. Start at llms.txt.