nearly 13 years
Tokyo, Japan
Logistics · Marketplaces · Product · AI-enabled work
Operating focus
I work best inside complex systems where the problem is not simply a lack of data, but a lack of clarity.
That may mean understanding why forecast performance is improving while costs are moving in the wrong direction. It may mean connecting seller behaviour, network design, capacity, and execution into one operating view. It may also mean translating a manual analytical process into a repeatable AI-enabled workflow.
My role is to help teams move from fragmented signals and reactive reporting toward clearer operating models.
Outcomes
I help organisations:
The common thread is not a specific industry or job title. It is making complex commercial and operational systems easier to understand and run.
Approach
01
I connect metrics that are often reviewed separately. Forecast accuracy, actual volume, capacity, cost, seller behaviour, route design, and execution quality usually tell a more useful story together than they do independently.
02
Analysis only matters when it changes how the organisation operates. I build planning mechanisms, workflows, tools, and cross-functional routines that help teams make better decisions consistently.
03
I use coding assistants and agentic workflows as an extension of operational thinking. The objective is not to automate everything, but to reduce repetitive work, improve analytical depth, create stronger documentation, and give operators more time to apply judgment.
04
My work has consistently sat between operations, product, engineering, finance, design, commercial teams, sellers, logistics providers, and senior leadership.
Evidence
A rapidly scaling logistics program required stronger forecasting, network planning, stakeholder alignment, and cost control across multiple planning horizons.
Castlery needed to strengthen its digital product capabilities, improve eCommerce performance, connect online and offline customer journeys, and reduce the manual work involved in producing digital assets.
Brands operating across Southeast Asia needed a more connected logistics model across countries, marketplaces, and third-party logistics providers.
Alongside my formal roles, I have continued building practical experiments with Python, LLMs, coding assistants, and agents.
Now
My career so far has given me experience across several layers of the commercial and operational system:
The next stage is not a departure from that experience. It is an extension of it.
I want to explore what happens when experienced operators can also use coding assistants, agents, and lightweight software development to build the tools they need themselves.
That includes questions such as:
My direction is toward work that sits between domain expertise, operations, product thinking, and technical execution.
Not AI as a separate specialism, but AI as a new layer of operating capability.
Ideas
Contact
My role is to help teams move from fragmented signals and reactive reporting toward clearer operating models.