
Applications
SparkBox
A specification for turning raw staff ideas into structured proposals.
SparkBox is an AI-assisted employee innovation platform that I specified and use as a reference application in executive programmes. There is no application code of my own: it is a specification and a teaching reference build.
The problem
The suggestion box in a large organisation collects raw ideas that managers cannot process. Ideas arrive in uneven prose, with no cost, benefit or owner attached, and most are never read closely.
What I built
The specification is the only artefact. An employee submits an idea in plain language. A hosted language model turns it into a structured proposal with a problem, a solution, a benefit, an effort and a category. Managers review it through a status workflow (Submitted, In Review, Solution Given or Rejected), and an Innovation Head dashboard tracks it to implementation. Role-based access and an admin “view as” feature are part of the design.
The documents describe a Base44 version used in teaching, and a planned self-hosted rebuild in React, Node, PostgreSQL and Prisma. No model is named.
How it performed
It has not been measured. I found no application code on either of my drives, no users and no results. It is a specification and a teaching reference build, not a deployed product.
What I learned
A specification is worth writing even when nothing gets built, because it forces the decisions: who submits, who reviews, what a structured idea must contain. In teaching, its value is as a brief that participants can build against. Its honest limit is that nobody has shown it improves the quality of ideas an organisation acts on.