I build small, local-first systems that turn messy information into reusable structure.
| 🚀 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.
- Lightweight automation that removes repetitive overhead for product, research, and ops teams.
- DX improvements that sharpen defaults, documentation, and traceability.
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Information compression
Distilling notes, docs, and operational data into structured outputs with evidence trails. -
Operational noise reduction
Taming alerts, handoffs, and status churn so teams act on signal instead of volume. -
Research-to-shipping loops
Moving insights into tickets, specs, and experiments without losing intent.
- 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.