Product & Systems Strategy · 2023–Present
Making a Complex System Feel Like One Conversation
AI-assisted product & systems strategy for an identity-rich platform
Context
As founder of an AI-powered venture (later supported by NSF funding), I owned the experience strategy for a web platform whose value depends on a genuinely complex underlying model — many interacting inputs that combine into a personalized result. The concepts are powerful but easy to overwhelm a first-time user with.
Problem
The system’s depth was its differentiator and its biggest usability risk. A literal, all-at-once interface would expose too many variables and stall people at the exact moment they should feel momentum. The design problem was sequencing, not decoration: how do you reveal a complex model progressively so the first session feels like one guided conversation rather than a form to survive?
Constraints
- The underlying scoring/logic is proprietary — the UX had to communicate value without exposing the model.
- Backend intelligence was evolving in parallel, so parts of the experience had to be designed against stubbed/expected data.
- Small team, fast cadence — decisions had to be legible enough for engineers to build directly from them.
- Accessibility and clarity were non-negotiable for a diverse first-time audience.
Approach
- Mapped the full journey first, then aggressively sequenced it — separating "must decide now" from "can resume later" so the required path stays short.
- Designed the complexity as progressive disclosure: each step asks for one thing, explains why it matters, and shows the payoff before asking for more.
- Modeled explicit states (empty, pending, returning) so the experience holds up before the backend is fully live.
- Wrote the flows as clear, reviewable specifications engineers could implement without guessing intent.
Key decisions
- Split identity/appearance choices from deeper "interview"-style depth so users get a quick win first and depth stays optional and resumable.
- Represented the still-evolving intelligence with honest pending states instead of fake precision, so the UI never over-promises.
- Kept a single accent/identity signal consistent across the whole journey so a complex product still reads as one coherent world.
Use of AI
I used AI-assisted workflows throughout — rapid ideation, drafting interaction copy, exploring alternative flows, and modeling content — while holding a hard quality bar on usability, accuracy, and ethics. AI accelerated exploration; judgment about what shipped stayed human.
Accessibility & ethics
Designed for a diverse first-time audience: staged cognitive load, plain-language step framing, honest pending/empty states, and interface controls for text scaling, reduced motion, and higher contrast so the experience adapts to the person rather than the reverse.
Outcome
- A short required path with resumable depth — the complex model reaches the user as a guided sequence, not a wall of inputs.
- Specifications concrete enough that engineering could build directly from them, reducing back-and-forth.
- A pattern language (staged reveal, consistent identity signal, honest states) reused across multiple product surfaces. [add metric: e.g., completion or time-to-first-value once measured]
Reflection
The hardest part of a complex product isn’t adding features — it’s deciding what a person is allowed to ignore, and when. Designing the sequence and the "not yet" states was where most of the usability actually came from.