← All work

01 · Life sciences

Making the missing work visible

I used a working prototype to reveal a pre-authoring workflow nobody had formally documented, then turned it into a product module.

  • AI product strategy
  • Complex workflows
  • Prototype in code
Working prototype 01 Life sciences

01 · Context and ambiguity

The useful problem was underneath the brief.

The brief asked us to improve clinical authoring, but each role described a different failure and the official process missed the work that happened before formal authoring began.

02 · Decisions

I made the system explicit before polishing the surface.

  1. I mapped the current workflow before defining a future state.
  2. I built a broad speculative prototype so experts could correct something concrete.
  3. I consolidated eight content areas into four authoring pillars.
  4. I carried product intent into code through a project-specific agent harness.

03 · Human and AI boundary

Automation got a lane. Judgment kept ownership.

AI scanned coverage, generated useful defaults, and surfaced questions. Clinical experts retained every consequential study decision.

04 · Working prototype

The artifact became the research surface.

The prototype behaved like the intended product, with representative data, linked states, and enough logic for stakeholders to expose missing dependencies.

05 · Outcome

What changed

Stakeholders recognized their informal one-pager in the prototype. That hidden workflow became the product’s newest module.

Engineering estimated the coded handoff avoided six to eight weeks of delivery effort.

Let’s make the system clear.

I work best where AI, complex workflows, and human judgment meet. If that sounds like your product, I would like to hear about it.