Founder, Shank Strategy Ops — operational strategy, execution systems, and deterministic decision tooling.
I build calm, high-signal systems for organizations that need to move from insight to execution without chaos. My work centers on operational reality: risk visibility, bounded decision systems, and tools that hold up under pressure.
This GitHub hosts open-source and research projects that support that work: local-first utilities, deterministic engines, and small, well-documented systems designed to turn messy inputs into auditable outcomes.
| 🚀 Focus | 🧭 Approach | 📌 Outcomes |
|---|---|---|
| Utility automation, knowledge architecture, calm technology, and systems experiments. | Start with intent, ship in small slices, measure what matters, prefer boring tech where it keeps teams fast. | Clearer decisions, searchable context, confident releases, and less operational noise. |
- Document distillers that compress messy notes, Markdown, and transcripts into reusable structure.
- Decision-support helpers that turn evidence into clear, shareable narratives.
- Operational noise reduction that tames alerts, handoffs, and status churn so teams act on signal instead of volume.
- Research-to-shipping loops that move insights into tickets, specs, and experiments without losing intent.
- DX improvements that sharpen defaults, documentation, and traceability.
- Intent first — define the win condition and failure modes before building.
- Slice delivery — ship iteratively with visible milestones and rollback paths.
- Design for calm — reduce cognitive load and make the next action obvious.
- Docs as infrastructure — names, context, and decisions that survive handoff.
- Research-driven framing before code.
- Tight feedback loops with stakeholders and users.
- Documentation and demos for every deliverable.
- Targeted experiments where learning is asymmetric.
If you need systems that reduce noise, preserve context, and stay out of the way, I’m interested in building them.