Knowledge retrieval
Structuring style, sample-stage, issue, comment, action and result history so useful precedent can be found quickly.
AI & workflow systems
Using AI to reduce repetitive work without outsourcing technical judgment.
My interest in AI is practical: organize technical knowledge, improve retrieval, automate repetitive documentation and communication steps, and make professional workflows easier to operate.
Current direction
Automation around the technical professional.
The goal is not an AI pattern maker. The goal is a better system around pattern-making work.
Agent workflows
Exploring AI agents for research, documentation, structured checking, task routing and repetitive professional operations.
Email & communication support
Using AI to prepare, review and organize professional email handling while keeping the final technical meaning under human control.
Tool building
Developing small workflow concepts, databases and connected systems that turn scattered technical information into reusable working knowledge.
Boundary
Human accountability stays in the loop.
Fit, construction, fabric behaviour and production decisions can carry costly consequences. AI output should therefore be treated as a proposal, retrieval aid or checking layer—not as automatic truth.
My systems work focuses on traceability, evidence, confidence and privacy so the technical professional can see why information was retrieved and decide whether it applies.
Portfolio roadmap
From personal workflow to reusable systems.
Near term
Document and automate repeatable professional workflows: knowledge capture, technical notes, research, article publishing and structured opportunity tracking.
Next
Prototype garment-knowledge retrieval and evaluation workflows using public-safe or synthetic examples.
Longer term
Connect validated garment knowledge, pattern data and human review into an auditable technical-assistance system.
Explore the research direction →