Hey Beta Testers! I’m working on a tool that helps organizations manage, monitor, and plan their AI strategy. There is no goal any more, the field is entirely fluid and being nimble is the new normal. Contact Me if interested
- Boundary Mapping: Where Work Actually Belongs
Event Horizon creates a clear picture of functions and workflows
human‑primary, agent‑primary, or shared
based on real evidence and experiments rather than hype - Evidence-Oriented AI Decisions
The evidence layer collects research, case studies, internal logs, and experiments – treated as first‑class data with indicators for level of maturity. - Experiment Design as a Management Skill
Event Horizon helps teams design small, safe experiments around specific functions and funnels, with explicit hypotheses, guardrails, and reliability measures. Don’t just “try AI” – build repeatable patterns for agent involvement where it measurably improves outcomes. - Living Failure Models, Not Static Risk Lists
Modern AI doesn’t just fail obviously; it fails subtly, and those patterns change as models evolve. Event Horizon lets teams design targeted checks instead of forcing blind trust. - Attention Allocation in Agent-Rich Environments
Human attention is now the scarce resource. Leaders must decide where people should be deeply involved, where light sampling is enough, and where they can safely step back where agents are reliably better and well‑instrumented. - Trajectory Sensing and Org Evolution
Capabilities are moving fast, but not randomly. The “trajectory” of AI skills, where and if they’re working in the wild, how fast they’re improving, and which business functions they’re about to penetrate are all mapped by Event Horizon. - Value and Alignment Across Perspectives
Different layers of the organization value the same functions differently. How Product, Ops, and Leadership rank functions and AI use cases supports proactive org design: adding missing functions, re‑shaping roles, and updating seams before change is forced on the organization.