Operations
Designing operational systems that flex under uncertainty—cadences, workflows, and decision architectures that mature.
Workflow Design
Most workflows were designed for human throughput. The best ones are now designed for human-AI collaboration.
I redesign operational workflows around the reality that AI can generate, synthesize, and execute at speeds no human team can match. The question isn't "how do we do this faster?" It's "what does this workflow look like when the bottleneck is human judgment, not human execution?"
The workflows I've built share a common pattern: clear handoff points between human and machine, explicit confidence thresholds for when a human needs to re-engage, and documentation systems that capture not just what was done, but what was decided and why.
Decision Architecture
Good operations isn't about eliminating decisions. It's about making the right ones explicit and the wrong ones expensive.
I've developed frameworks for operational decision-making that separate reversible decisions from irreversible ones, and that build in escalation paths for the cases where AI systems flag uncertainty.
The key insight: most operational failures aren't caused by bad decisions. They're caused by decisions that were never explicitly made—where inertia, convention, or automated systems chose a path that no human had actually evaluated.
Cadence & Ritual
The right meeting at the right frequency beats the perfect async system implemented wrong.
I design operational cadences that match the decision velocity of the organization, not the calendar. Weekly standups become biweekly when AI systems handle routine updates; monthly reviews become weekly when the competitive landscape shifts faster than the previous rhythm could capture.
The rituals I put in place serve a specific function: they create predictable moments for human judgment to enter systems that would otherwise run on autopilot. Without these, organizations drift. With too many, they drown in ceremony.